From b827f03d56489419a3c0cf518b6f5f8b6b7e9a00 Mon Sep 17 00:00:00 2001
From: Hwang <hjhyoman1@gmail.com>
Date: Sun, 22 Feb 2026 18:05:14 +0900
Subject: [PATCH] source push

---
 __pycache__/database.cpython-312.pyc       |  Bin 0 -> 42862 bytes
 __pycache__/kis_short_ver1.cpython-312.pyc |  Bin 0 -> 120301 bytes
 __pycache__/ml_predictor.cpython-312.pyc   |  Bin 0 -> 12006 bytes
 __pycache__/risk_manager.cpython-312.pyc   |  Bin 0 -> 10502 bytes
 check_account_config.py                    |  103 +
 check_db.py                                |   28 +
 copy_env_row_to_latest.py                  |   40 +
 database.py                                |  872 ++++++
 init_db.py                                 |   78 +
 kis_long_ver1.py                           | 1668 ++++++++++
 kis_short_ver1.py                          | 3296 ++++++++++++++++++++
 ml_predictor.py                            |  229 ++
 modify_db_schema.py                        |   37 +
 quant_bot.db                               |  Bin 0 -> 77824 bytes
 risk_manager.py                            |  270 ++
 scripts/copy_env_row_to_latest.py          |    0
 update_env.py                              |  145 +
 update_env_short.py                        |  137 +
 update_env_simple.py                       |   83 +
 19 files changed, 6986 insertions(+)
 create mode 100644 __pycache__/database.cpython-312.pyc
 create mode 100644 __pycache__/kis_short_ver1.cpython-312.pyc
 create mode 100644 __pycache__/ml_predictor.cpython-312.pyc
 create mode 100644 __pycache__/risk_manager.cpython-312.pyc
 create mode 100644 check_account_config.py
 create mode 100644 check_db.py
 create mode 100644 copy_env_row_to_latest.py
 create mode 100644 database.py
 create mode 100644 init_db.py
 create mode 100644 kis_long_ver1.py
 create mode 100644 kis_short_ver1.py
 create mode 100644 ml_predictor.py
 create mode 100644 modify_db_schema.py
 create mode 100644 quant_bot.db
 create mode 100644 risk_manager.py
 create mode 100644 scripts/copy_env_row_to_latest.py
 create mode 100644 update_env.py
 create mode 100644 update_env_short.py
 create mode 100644 update_env_simple.py

diff --git a/__pycache__/database.cpython-312.pyc b/__pycache__/database.cpython-312.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..2bd586146453dffd12220809f9a2a104ec8d17bd
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diff --git a/check_account_config.py b/check_account_config.py
new file mode 100644
index 0000000..960437a
--- /dev/null
+++ b/check_account_config.py
@@ -0,0 +1,103 @@
+#!/usr/bin/env python3
+"""
+DB에서 계좌번호 설정 확인 스크립트
+- 현재 최신 env_config에서 계좌번호 관련 필드 조회
+- 모의/실전 구분 및 실제 읽히는 값 확인
+"""
+import sys
+from pathlib import Path
+
+SCRIPT_DIR = Path(__file__).resolve().parent
+sys.path.insert(0, str(SCRIPT_DIR))
+
+from database import TradeDB
+
+def main():
+    db = TradeDB(db_path=str(SCRIPT_DIR / "quant_bot.db"))
+    env_data = db.get_latest_env()
+    db.close()
+
+    if not env_data or not env_data.get("snapshot"):
+        print("❌ env_config에 데이터가 없습니다.")
+        return
+
+    snapshot = env_data["snapshot"]
+    print(f"📊 최신 env_config (id={env_data['id']}, created_at={env_data['created_at']})\n")
+
+    # 모의 여부
+    kis_mock = snapshot.get("KIS_MOCK", "").lower()
+    is_mock = kis_mock in ("true", "1", "yes")
+    print(f"🔹 KIS_MOCK = '{kis_mock}' → 모의투자: {is_mock}\n")
+
+    # 실전 계좌
+    print("📌 실전 계좌 (KIS_MOCK=false 시 사용):")
+    acc_no_real = snapshot.get("KIS_ACCOUNT_NO", "").strip()
+    acc_code_real = snapshot.get("KIS_ACCOUNT_CODE", "").strip() or "01"
+    print(f"  KIS_ACCOUNT_NO = '{acc_no_real}' ({len(acc_no_real)}자리)")
+    print(f"  KIS_ACCOUNT_CODE = '{acc_code_real}' ({len(acc_code_real)}자리)")
+    if acc_no_real:
+        digits_no = "".join(c for c in acc_no_real if c.isdigit())
+        print(f"  → 숫자만 추출: '{digits_no}' ({len(digits_no)}자리)")
+        if len(digits_no) >= 10:
+            print(f"  → CANO: '{digits_no[:8]}', ACNT_PRDT_CD: '{digits_no[8:10]}' ✅")
+        elif len(digits_no) == 8:
+            print(f"  → CANO: '{digits_no}', ACNT_PRDT_CD: '{acc_code_real.zfill(2)[:2]}' ✅")
+        else:
+            print(f"  → ⚠️ 8자리 미만: CANO='{digits_no.zfill(8)[:8]}', ACNT_PRDT_CD='{acc_code_real.zfill(2)[:2]}' (부족한 자리 0으로 채움)")
+    else:
+        print("  → ❌ 값이 비어있음!")
+
+    print()
+
+    # 모의 계좌
+    print("📌 모의 계좌 (KIS_MOCK=true 시 사용):")
+    acc_no_mock = snapshot.get("KIS_ACCOUNT_NO_MOCK", "").strip()
+    acc_code_mock = snapshot.get("KIS_ACCOUNT_CODE_MOCK", "").strip() or "01"
+    print(f"  KIS_ACCOUNT_NO_MOCK = '{acc_no_mock}' ({len(acc_no_mock)}자리)")
+    print(f"  KIS_ACCOUNT_CODE_MOCK = '{acc_code_mock}' ({len(acc_code_mock)}자리)")
+    if acc_no_mock:
+        digits_no = "".join(c for c in acc_no_mock if c.isdigit())
+        print(f"  → 숫자만 추출: '{digits_no}' ({len(digits_no)}자리)")
+        if len(digits_no) >= 10:
+            print(f"  → CANO: '{digits_no[:8]}', ACNT_PRDT_CD: '{digits_no[8:10]}' ✅")
+        elif len(digits_no) == 8:
+            print(f"  → CANO: '{digits_no}', ACNT_PRDT_CD: '{acc_code_mock.zfill(2)[:2]}' ✅")
+        else:
+            print(f"  → ⚠️ 8자리 미만: CANO='{digits_no.zfill(8)[:8]}', ACNT_PRDT_CD='{acc_code_mock.zfill(2)[:2]}' (부족한 자리 0으로 채움)")
+    else:
+        print("  → ❌ 값이 비어있음! (fallback: 실전 계좌 사용)")
+
+    print()
+
+    # 실제 사용될 계좌
+    print("🎯 실제 사용될 계좌:")
+    if is_mock:
+        final_no = acc_no_mock or acc_no_real
+        final_code = acc_code_mock if acc_no_mock else acc_code_real
+        print(f"  모의투자 모드 → KIS_ACCOUNT_NO_MOCK='{acc_no_mock}' 또는 KIS_ACCOUNT_NO='{acc_no_real}'")
+    else:
+        final_no = acc_no_real
+        final_code = acc_code_real
+        print(f"  실전투자 모드 → KIS_ACCOUNT_NO='{acc_no_real}'")
+    
+    if final_no:
+        digits_no = "".join(c for c in final_no if c.isdigit())
+        if len(digits_no) >= 10:
+            cano = digits_no[:8]
+            acnt = digits_no[8:10]
+        elif len(digits_no) == 8:
+            cano = digits_no
+            acnt = final_code.zfill(2)[:2]
+        else:
+            cano = digits_no.zfill(8)[:8]
+            acnt = final_code.zfill(2)[:2]
+        
+        if len(cano) == 8 and len(acnt) == 2:
+            print(f"  ✅ 최종: CANO={cano}, ACNT_PRDT_CD={acnt}")
+        else:
+            print(f"  ❌ 최종: CANO={cano}({len(cano)}자리), ACNT_PRDT_CD={acnt}({len(acnt)}자리) → OPSQ2000 발생 가능!")
+    else:
+        print("  ❌ 계좌번호가 비어있음 → OPSQ2000 발생!")
+
+if __name__ == "__main__":
+    main()
diff --git a/check_db.py b/check_db.py
new file mode 100644
index 0000000..0ddae4d
--- /dev/null
+++ b/check_db.py
@@ -0,0 +1,28 @@
+import sqlite3
+import os
+
+# 데이터베이스 파일 경로
+db_path = os.path.join(os.path.dirname(__file__), 'quant_bot.db')
+
+# 연결 생성
+conn = sqlite3.connect(db_path)
+cursor = conn.cursor()
+
+# 테이블 목록 조회
+cursor.execute("SELECT name FROM sqlite_master WHERE type='table';")
+tables = cursor.fetchall()
+
+print("Tables in database:")
+for table in tables:
+    print(f"  {table[0]}")
+
+# 각 테이블의 구조 조회
+for table in tables:
+    table_name = table[0]
+    print(f"\nStructure of {table_name}:")
+    cursor.execute(f"PRAGMA table_info({table_name});")
+    columns = cursor.fetchall()
+    for column in columns:
+        print(f"  {column[1]} ({column[2]}) - nullable: {column[3]}, primary key: {column[4]}")
+
+conn.close()
\ No newline at end of file
diff --git a/copy_env_row_to_latest.py b/copy_env_row_to_latest.py
new file mode 100644
index 0000000..0dab11e
--- /dev/null
+++ b/copy_env_row_to_latest.py
@@ -0,0 +1,40 @@
+#!/usr/bin/env python3
+"""
+env_config에서 지정한 id 행을 그대로 복사해 새 행으로 INSERT.
+→ 봇은 항상 id 최대(최신) 행만 쓰므로, 4번 내용이 곧 '최신 설정'이 됨.
+
+사용: python copy_env_row_to_latest.py [소스_id]
+  소스_id 기본값: 4
+"""
+import sys
+from pathlib import Path
+
+SCRIPT_DIR = Path(__file__).resolve().parent
+sys.path.insert(0, str(SCRIPT_DIR))
+
+from database import TradeDB, ENV_CONFIG_KEYS
+
+def main():
+    source_id = int(sys.argv[1]) if len(sys.argv) > 1 else 4
+    db_path = SCRIPT_DIR / "quant_bot.db"
+    db = TradeDB(db_path=str(db_path))
+
+    row = db.conn.execute("SELECT * FROM env_config WHERE id = ?", (source_id,)).fetchone()
+    if not row:
+        print(f"id={source_id} 행이 없습니다.")
+        db.close()
+        return
+
+    # id=4 내용으로 새 스냅샷 생성 (created_at만 현재 시각)
+    import datetime
+    snapshot = {k: (row[k] if row[k] is not None else "") for k in ENV_CONFIG_KEYS if k in row.keys()}
+    env_id = db.insert_env_snapshot(snapshot)
+    db.close()
+
+    if env_id:
+        print(f"✅ id={source_id} 내용을 새 행(id={env_id})으로 복사했습니다. 이제 최신 설정입니다.")
+    else:
+        print("❌ INSERT 실패")
+
+if __name__ == "__main__":
+    main()
diff --git a/database.py b/database.py
new file mode 100644
index 0000000..14e69a8
--- /dev/null
+++ b/database.py
@@ -0,0 +1,872 @@
+"""
+트레이딩 봇 데이터베이스 관리 모듈
+- SQLite 기반 데이터 무결성 보장 (JSON 대비 재시작 안전성 향상)
+- 활성 트레이딩 관리 (active_trades)
+- 매매 히스토리 관리 (trade_history)
+"""
+import json
+import sqlite3
+import datetime
+import logging
+from typing import Dict, List, Optional, Tuple
+
+logger = logging.getLogger("TradeDB")
+
+# env_config 테이블 컬럼 (키 하나당 컬럼 하나, 추가/삭제 시 여기와 CREATE TABLE만 수정)
+ENV_CONFIG_KEYS = (
+    "STOP_LOSS_PCT", "SHOULDER_CUT_PCT", "STOP_ATR_MULTIPLIER_TAIL", "TARGET_ATR_MULTIPLIER_TAIL",
+    "MAX_POSITION_PCT", "USE_SLOT_CAP", "SLOT_CAP_PCT", "MAX_STOCKS",
+    "USE_KELLY", "RISK_PCT_PER_TRADE", "MIN_POSITION_AMOUNT",
+    "USE_RISK_CHECK", "DAILY_STOP_LOSS_PCT", "CONSECUTIVE_LOSS_LIMIT",
+    "USE_BAN_SYSTEM", "BAN_HOURS", "USE_STOCK_FILTER", "RSI_OVERHEAT_THRESHOLD",
+    "MIN_RECOVERY_RATIO", "MAX_RECOVERY_RATIO",
+    "USE_TWAP", "TWAP_MIN_SPLIT", "TWAP_MAX_SPLIT", "TWAP_MIN_DELAY", "TWAP_MAX_DELAY",
+    "USE_ML_SIGNAL", "ML_MIN_PROBABILITY", "USE_NEWS_ANALYSIS", "NEWS_ANALYSIS_HOUR", "NEWS_MAX_COUNT",
+    "USE_QUICK_PROFIT_PROTECTION", "HIGH_PRICE_CHASE_THRESHOLD", "MAX_DAILY_CHANGE_PCT",
+    "MA20_MAX_ABOVE_PCT", "VOLUME_AVG_MULTIPLIER", "CANDLE_OPEN_PRICE_BUFFER",
+    "INTRADAY_INVESTOR_NET_BUY_THRESHOLD", "SIZE_CLASS_LARGE_MIN", "SIZE_CLASS_MID_MIN",
+    "USE_RANDOM_SPLIT", "FORCE_MARKET_OPEN", "TOTAL_DEPOSIT",
+    # POP/LOCK·금액 손절 관련 추가 키
+    "ROUND_TRIP_COST_PCT", "POP_NET_PCT", "LOCK_NET_PCT", "MAX_LOSS_PER_TRADE_KRW",
+    # 한투 API 관련 키 추가 (실전/모의 계좌 분리)
+    "KIS_APP_KEY_REAL", "KIS_APP_SECRET_REAL",
+    "KIS_APP_KEY_MOCK", "KIS_APP_SECRET_MOCK",
+    "KIS_ACCOUNT_NO_REAL", "KIS_ACCOUNT_CODE_REAL",           # 실전 계좌 (KIS_MOCK=false 시 사용)
+    "KIS_ACCOUNT_NO_MOCK", "KIS_ACCOUNT_CODE_MOCK",  # 모의 계좌 (KIS_MOCK=true 시 사용)
+    "KIS_MOCK",
+    # 단타 봇 전용 키
+    "TAKE_PROFIT_PCT", "MIN_DROP_RATE", "MIN_RECOVERY_RATIO_SHORT",
+    # 늘림목 봇 전용 키
+    "MAX_PER", "MAX_PEG", "MIN_GROWTH_PCT", "DCA_INTERVALS", "DCA_AMOUNTS",
+    # Mattermost 및 AI 리포트 관련 키
+    "MM_SERVER_URL", "MM_BOT_TOKEN_", "MATTERMOST_CHANNEL", "GEMINI_API_KEY",
+    # 봇별 Mattermost 채널 구분용 키
+    "KIS_SHORT_MM_CHANNEL", "KIS_LONG_MM_CHANNEL",
+)
+
+
+class TradeDB:
+    """
+    트레이딩 봇용 SQLite 데이터베이스 관리 클래스
+    """
+    def __init__(self, db_path="quant_bot.db"):
+        """
+        Args:
+            db_path: SQLite DB 파일 경로 (기본: quant_bot.db)
+        """
+        self.db_path = db_path
+        self.conn = sqlite3.connect(db_path, check_same_thread=False)
+        self.conn.row_factory = sqlite3.Row  # 딕셔너리처럼 접근 가능
+        self._create_tables()
+        logger.info(f"✅ TradeDB 초기화 완료: {db_path}")
+
+    def _create_tables(self):
+        """DB 테이블 생성 (없을 경우)"""
+        with self.conn:
+            # 1. 활성 트레이딩 테이블 (현재 보유 중이거나 매수 중인 종목)
+            self.conn.execute("""
+                CREATE TABLE IF NOT EXISTS active_trades (
+                    code TEXT PRIMARY KEY,       -- 종목코드
+                    name TEXT NOT NULL,          -- 종목명
+                    strategy TEXT,               -- 매매 전략 (TAIL_CATCH_3M 등)
+                    
+                    -- [가격 정보]
+                    avg_buy_price REAL NOT NULL, -- 평단가
+                    current_price REAL,          -- 현재가 (업데이트용)
+                    stop_price REAL,             -- 손절가
+                    target_price REAL,           -- 목표가
+                    max_price REAL,              -- 최고가 (트레일링 스탑용)
+                    atr_entry REAL,              -- 진입 시 ATR 변동성
+                    
+                    -- [수량 및 진행 상태 (분할매수용)]
+                    target_qty INTEGER NOT NULL, -- 목표 매수 수량
+                    current_qty INTEGER NOT NULL,-- 현재 체결 수량
+                    total_invested REAL,         -- 총 투입 금액 (수수료 제외)
+                    
+                    -- [상태 관리]
+                    status TEXT NOT NULL,        -- BUYING(매수중), HOLDING(보유중), SELLING(매도중)
+                    buy_date TEXT NOT NULL,      -- 첫 매수 시작 시간
+                    updated_at TEXT NOT NULL,    -- 마지막 업데이트 시간
+                    size_class TEXT              -- 대/중/소형 (매수 시점)
+                )
+            """)
+
+            # 2. 매매 기록 테이블 (손익 분석 & 켈리 공식용)
+            self.conn.execute("""
+                CREATE TABLE IF NOT EXISTS trade_history (
+                    id INTEGER PRIMARY KEY AUTOINCREMENT,
+                    code TEXT NOT NULL,
+                    name TEXT NOT NULL,
+                    strategy TEXT,
+                    buy_price REAL NOT NULL,     -- 평단가
+                    sell_price REAL NOT NULL,    -- 매도가
+                    qty INTEGER NOT NULL,        -- 수량
+                    profit_rate REAL NOT NULL,   -- 수익률 (%)
+                    realized_pnl REAL NOT NULL,  -- 실현 손익금 (원)
+                    hold_minutes INTEGER,        -- 보유 시간 (분)
+                    buy_date TEXT,               -- 매수 시작 시간
+                    sell_date TEXT NOT NULL,     -- 매도 완료 시간
+                    sell_reason TEXT,            -- 매도 사유
+                    env_snapshot TEXT,          -- 매도 시점 env (JSON)
+                    size_class TEXT              -- 대/중/소형 (변동성 구간)
+                )
+            """)
+            
+            # 3. 일일 손익 요약 테이블 (대시보드용)
+            self.conn.execute("""
+                CREATE TABLE IF NOT EXISTS daily_summary (
+                    date TEXT PRIMARY KEY,       -- 날짜 (YYYY-MM-DD)
+                    start_asset REAL,            -- 시작 자산
+                    end_asset REAL,              -- 종료 자산
+                    total_trades INTEGER,        -- 총 매매 횟수
+                    win_trades INTEGER,          -- 익절 횟수
+                    total_pnl REAL,              -- 총 손익
+                    win_rate REAL                -- 승률 (%)
+                )
+            """)
+            
+            # 4. 주문·체결 보강 테이블 (kt00007 / ka10076)
+            self.conn.execute("""
+                CREATE TABLE IF NOT EXISTS order_execution_history (
+                    id INTEGER PRIMARY KEY AUTOINCREMENT,
+                    source TEXT NOT NULL,        -- 'kt00007' or 'ka10076'
+                    ord_no TEXT,
+                    stk_cd TEXT,
+                    stk_nm TEXT,
+                    trde_tp TEXT,                -- 매매구분
+                    ord_qty TEXT,
+                    ord_uv TEXT,
+                    cntr_qty TEXT,
+                    cntr_uv TEXT,
+                    ord_tm TEXT,
+                    cnfm_tm TEXT,
+                    sell_tp TEXT,
+                    ord_dt TEXT,
+                    raw_json TEXT,
+                    fetched_at TEXT NOT NULL
+                )
+            """)
+
+            # 5. 매수 후보군 테이블 (target_universe 대체)
+            self.conn.execute("""
+                CREATE TABLE IF NOT EXISTS target_candidates (
+                    code TEXT PRIMARY KEY,       -- 종목코드
+                    name TEXT NOT NULL,          -- 종목명
+                    score REAL NOT NULL,         -- 개미털기 점수 (높을수록 좋음)
+                    price REAL NOT NULL,         -- 현재가
+                    scan_time TEXT NOT NULL,     -- 스캔 시간
+                    updated_at TEXT NOT NULL     -- 마지막 업데이트
+                )
+            """)
+
+            # 6. env 설정 전용 테이블 (관리자용, INSERT만 / 최신 1건 = 현재 설정, 키당 컬럼)
+            cols = ", ".join([f'"{k}" TEXT' for k in ENV_CONFIG_KEYS])
+            self.conn.execute(f"""
+                CREATE TABLE IF NOT EXISTS env_config (
+                    id INTEGER PRIMARY KEY AUTOINCREMENT,
+                    created_at TEXT NOT NULL,
+                    {cols}
+                )
+            """)
+            
+        self._migrate_add_columns()
+        self._migrate_env_config_to_columns()
+        logger.info("📊 DB 테이블 생성/확인 완료")
+
+    def _migrate_add_columns(self):
+        """기존 DB에 누락된 컬럼 추가 (한 번만)"""
+        try:
+            cur = self.conn.execute("PRAGMA table_info(trade_history)")
+            cols = [row[1] for row in cur.fetchall()]
+            if "env_snapshot" not in cols:
+                self.conn.execute("ALTER TABLE trade_history ADD COLUMN env_snapshot TEXT")
+                logger.info("📌 trade_history.env_snapshot 컬럼 추가")
+            if "size_class" not in cols:
+                self.conn.execute("ALTER TABLE trade_history ADD COLUMN size_class TEXT")
+                logger.info("📌 trade_history.size_class 컬럼 추가")
+        except Exception as e:
+            logger.debug(f"migrate trade_history: {e}")
+        try:
+            cur = self.conn.execute("PRAGMA table_info(active_trades)")
+            cols = [row[1] for row in cur.fetchall()]
+            if "size_class" not in cols:
+                self.conn.execute("ALTER TABLE active_trades ADD COLUMN size_class TEXT")
+                logger.info("📌 active_trades.size_class 컬럼 추가")
+        except Exception as e:
+            logger.debug(f"migrate active_trades: {e}")
+        # env_config 테이블에 ENV_CONFIG_KEYS에 정의된 컬럼 누락 시 추가
+        try:
+            cur = self.conn.execute("PRAGMA table_info(env_config)")
+            cols = [row[1] for row in cur.fetchall()]
+            for key in ENV_CONFIG_KEYS:
+                if key not in cols:
+                    self.conn.execute(f'ALTER TABLE env_config ADD COLUMN "{key}" TEXT')
+                    logger.info(f"📌 env_config.{key} 컬럼 추가")
+        except Exception as e:
+            logger.debug(f"migrate env_config columns: {e}")
+
+    def _migrate_env_config_to_columns(self):
+        """env_config가 예전 JSON 컬럼(snapshot_json)이면 컬럼 스키마로 이전"""
+        try:
+            cur = self.conn.execute("PRAGMA table_info(env_config)")
+            cols = [row[1] for row in cur.fetchall()]
+            if "snapshot_json" not in cols:
+                return
+            # 기존 데이터 백업 후 새 테이블로 이전
+            rows = self.conn.execute("SELECT id, created_at, snapshot_json FROM env_config ORDER BY id").fetchall()
+            col_defs = ", ".join([f'"{k}" TEXT' for k in ENV_CONFIG_KEYS])
+            self.conn.execute(f"""
+                CREATE TABLE IF NOT EXISTS env_config_new (
+                    id INTEGER PRIMARY KEY AUTOINCREMENT,
+                    created_at TEXT NOT NULL,
+                    {col_defs}
+                )
+            """)
+            key_list = ", ".join(f'"{k}"' for k in ENV_CONFIG_KEYS)
+            placeholders = ", ".join(["?"] * (1 + len(ENV_CONFIG_KEYS)))
+            for row in rows:
+                snap = json.loads(row["snapshot_json"]) if row["snapshot_json"] else {}
+                vals = [row["created_at"]] + [snap.get(k) for k in ENV_CONFIG_KEYS]
+                self.conn.execute(
+                    f"INSERT INTO env_config_new (created_at, {key_list}) VALUES ({placeholders})",
+                    vals,
+                )
+            self.conn.execute("DROP TABLE env_config")
+            self.conn.execute("ALTER TABLE env_config_new RENAME TO env_config")
+            self.conn.commit()
+            logger.info("📌 env_config: snapshot_json -> 컬럼 스키마 마이그레이션 완료")
+        except Exception as e:
+            logger.debug(f"migrate env_config: {e}")
+
+    # ============================================================
+    # [CRUD] Active Trades (활성 트레이딩 관리)
+    # ============================================================
+    
+    def upsert_trade(self, trade_data: Dict):
+        """
+        신규 매수하거나 정보 업데이트 (평단가, 수량 등)
+        
+        Args:
+            trade_data: 트레이드 정보 딕셔너리
+                필수: code, name, avg_buy_price, target_qty, current_qty, status
+                선택: strategy, stop_price, target_price, max_price, atr_entry, total_invested
+        """
+        now = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        
+        # 기본값 설정
+        code = trade_data.get('code')
+        if not code:
+            logger.error("종목코드 누락: upsert 실패")
+            return False
+            
+        size_class = trade_data.get('size_class')
+        sql = """
+            INSERT INTO active_trades (
+                code, name, strategy, avg_buy_price, current_price, stop_price, target_price,
+                max_price, atr_entry, target_qty, current_qty, total_invested,
+                status, buy_date, updated_at, size_class
+            ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+            ON CONFLICT(code) DO UPDATE SET
+                avg_buy_price = excluded.avg_buy_price,
+                current_price = excluded.current_price,
+                stop_price = COALESCE(excluded.stop_price, active_trades.stop_price),
+                target_price = COALESCE(excluded.target_price, active_trades.target_price),
+                atr_entry = COALESCE(excluded.atr_entry, active_trades.atr_entry),
+                current_qty = excluded.current_qty,
+                total_invested = excluded.total_invested,
+                max_price = MAX(active_trades.max_price, excluded.max_price),
+                status = excluded.status,
+                updated_at = excluded.updated_at,
+                size_class = COALESCE(excluded.size_class, active_trades.size_class)
+        """
+        params = (
+            code,
+            trade_data.get('name', 'Unknown'),
+            trade_data.get('strategy', 'MANUAL'),
+            trade_data.get('avg_buy_price') or trade_data.get('buy_price', 0),
+            trade_data.get('current_price', 0),
+            trade_data.get('stop_price', 0),
+            trade_data.get('target_price', 0),
+            trade_data.get('max_price', trade_data.get('buy_price', 0)),
+            trade_data.get('atr_at_entry') or trade_data.get('atr_entry', 0),
+            trade_data.get('target_qty', trade_data.get('qty', 0)),
+            trade_data.get('current_qty') or trade_data.get('qty', 0),
+            trade_data.get('total_invested', 0),
+            trade_data.get('status', 'HOLDING'),
+            trade_data.get('buy_date', now),
+            now,
+            size_class
+        )
+        
+        try:
+            with self.conn:
+                self.conn.execute(sql, params)
+            return True
+        except Exception as e:
+            logger.error(f"❌ upsert_trade 실패 ({code}): {e}")
+            return False
+
+    def get_active_trades(self):
+        """
+        활성 트레이딩 목록 조회 (봇 재시작 시 사용)
+        
+        Returns:
+            {종목코드: {trade_info}} 형태의 딕셔너리
+        """
+        try:
+            cursor = self.conn.execute("SELECT * FROM active_trades")
+            rows = cursor.fetchall()
+            
+            # 기존 JSON 포맷과 호환되도록 딕셔너리 변환
+            result = {}
+            for row in rows:
+                code = row['code']
+                result[code] = {
+                    'code': code,
+                    'name': row['name'],
+                    'strategy': row['strategy'],
+                    'buy_price': row['avg_buy_price'],  # JSON 호환
+                    'avg_buy_price': row['avg_buy_price'],
+                    'current_price': row['current_price'],
+                    'stop_price': row['stop_price'],
+                    'target_price': row['target_price'],
+                    'max_price': row['max_price'],
+                    'atr_at_entry': row['atr_entry'],
+                    'qty': row['current_qty'],  # JSON 호환
+                    'target_qty': row['target_qty'],
+                    'current_qty': row['current_qty'],
+                    'total_invested': row['total_invested'],
+                    'status': row['status'],
+                    'buy_date': row['buy_date'],
+                    'updated_at': row['updated_at'],
+                    'size_class': row['size_class'] if 'size_class' in row.keys() else None,
+                }
+            
+            logger.debug(f"📂 활성 트레이드 로드: {len(result)}개")
+            return result
+            
+        except Exception as e:
+            logger.error(f"❌ get_active_trades 실패: {e}")
+            return {}
+
+    def update_current_price(self, code: str, current_price: float):
+        """현재가 업데이트 (매도 판단용)"""
+        now = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        try:
+            with self.conn:
+                self.conn.execute(
+                    "UPDATE active_trades SET current_price=?, updated_at=? WHERE code=?",
+                    (current_price, now, code)
+                )
+        except Exception as e:
+            logger.error(f"❌ 현재가 업데이트 실패 ({code}): {e}")
+
+    def update_max_price(self, code: str, new_max_price: float):
+        """최고가 갱신 (트레일링 스탑용)"""
+        now = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        try:
+            with self.conn:
+                # 기존 max_price보다 클 때만 업데이트
+                self.conn.execute(
+                    """UPDATE active_trades 
+                       SET max_price = MAX(max_price, ?), updated_at = ?
+                       WHERE code = ?""",
+                    (new_max_price, now, code)
+                )
+        except Exception as e:
+            logger.error(f"❌ 최고가 갱신 실패 ({code}): {e}")
+
+    def close_trade(
+        self,
+        code: str,
+        sell_price: float,
+        sell_reason: str = "",
+        env_snapshot: str = None,
+        size_class: str = None,
+    ):
+        """
+        매도 완료 처리: active_trades 삭제 -> trade_history 이동 (INSERT만, env 스냅샷 포함)
+
+        Args:
+            code: 종목코드
+            sell_price: 매도가
+            sell_reason: 매도 사유
+            env_snapshot: 매도 시점 env JSON (백테스트/대시보드용)
+            size_class: 대/중/소형 (매수 시점 저장값)
+        """
+        try:
+            # 1. 활성 트레이드 정보 조회
+            cursor = self.conn.execute("SELECT * FROM active_trades WHERE code=?", (code,))
+            trade = cursor.fetchone()
+
+            if not trade:
+                logger.warning(f"⚠️ close_trade: {code} 종목이 active_trades에 없음")
+                return False
+
+            # 2. 손익 계산
+            buy_price = trade['avg_buy_price']
+            qty = trade['current_qty']
+            profit_rate = ((sell_price - buy_price) / buy_price) * 100 if buy_price > 0 else 0
+            realized_pnl = (sell_price - buy_price) * qty
+
+            # 3. 보유 시간 계산
+            buy_time = datetime.datetime.strptime(trade['buy_date'], '%Y-%m-%d %H:%M:%S')
+            sell_time = datetime.datetime.now()
+            hold_minutes = int((sell_time - buy_time).total_seconds() / 60)
+
+            # size_class는 active_trades에 있으면 그대로 사용
+            if size_class is None and 'size_class' in trade.keys() and trade['size_class']:
+                size_class = trade['size_class']
+
+            # 4. trade_history에 저장 (env_snapshot, size_class 포함 INSERT)
+            with self.conn:
+                self.conn.execute("""
+                    INSERT INTO trade_history (
+                        code, name, strategy, buy_price, sell_price, qty,
+                        profit_rate, realized_pnl, hold_minutes, buy_date, sell_date, sell_reason,
+                        env_snapshot, size_class
+                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                """, (
+                    trade['code'],
+                    trade['name'],
+                    trade['strategy'],
+                    buy_price,
+                    sell_price,
+                    qty,
+                    profit_rate,
+                    realized_pnl,
+                    hold_minutes,
+                    trade['buy_date'],
+                    sell_time.strftime('%Y-%m-%d %H:%M:%S'),
+                    sell_reason,
+                    env_snapshot,
+                    size_class,
+                ))
+
+                # 5. active_trades에서 삭제
+                self.conn.execute("DELETE FROM active_trades WHERE code=?", (code,))
+                
+            logger.info(f"✅ [{trade['name']}] 매매 종료: 수익률 {profit_rate:.2f}% ({realized_pnl:+,.0f}원)")
+            return True
+            
+        except Exception as e:
+            logger.error(f"❌ close_trade 실패 ({code}): {e}")
+            return False
+
+    def delete_active_trade(self, code: str):
+        """활성 트레이드 삭제 (긴급 정리용)"""
+        try:
+            with self.conn:
+                self.conn.execute("DELETE FROM active_trades WHERE code=?", (code,))
+            logger.info(f"🗑️ active_trade 삭제: {code}")
+            return True
+        except Exception as e:
+            logger.error(f"❌ 삭제 실패 ({code}): {e}")
+            return False
+
+    # ============================================================
+    # [보강] 주문·체결 이력 (kt00007 / ka10076)
+    # ============================================================
+
+    def insert_order_execution(
+        self, source: str, row: dict, ord_dt: str = None, sell_tp: str = None, raw_json: str = None
+    ):
+        """주문·체결 1건 INSERT (보강용, 이력만 쌓음)"""
+        now = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        try:
+            self.conn.execute("""
+                INSERT INTO order_execution_history (
+                    source, ord_no, stk_cd, stk_nm, trde_tp, ord_qty, ord_uv,
+                    cntr_qty, cntr_uv, ord_tm, cnfm_tm, sell_tp, ord_dt, raw_json, fetched_at
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+            """, (
+                source,
+                row.get('ord_no') or row.get('orig_ord_no'),
+                row.get('stk_cd', ''),
+                row.get('stk_nm', ''),
+                row.get('trde_tp', ''),
+                str(row.get('ord_qty', '') or row.get('cntr_qty', '')),
+                str(row.get('ord_uv', '') or row.get('ord_pric', '') or row.get('cntr_uv', '')),
+                str(row.get('cntr_qty', '') or row.get('cnfm_qty', '')),
+                str(row.get('cntr_uv', '') or row.get('cntr_pric', '')),
+                row.get('ord_tm', ''),
+                row.get('cnfm_tm', ''),
+                sell_tp or '',
+                ord_dt or '',
+                raw_json,
+                now,
+            ))
+            self.conn.commit()
+            return True
+        except Exception as e:
+            logger.debug(f"insert_order_execution: {e}")
+            return False
+
+    # ============================================================
+    # [분석] 켈리 공식 및 통계 계산
+    # ============================================================
+    
+    def calculate_half_kelly(self, recent_days: int = 30) -> float:
+        """
+        하프 켈리 공식 계산 (과거 매매 기록 기반)
+        
+        Args:
+            recent_days: 최근 N일 데이터만 사용
+            
+        Returns:
+            하프 켈리 비율 (0.0 ~ 1.0)
+            예: 0.15 리턴 -> "예수금의 15%씩 배팅하는 게 최적"
+        """
+        try:
+            # 최근 N일 데이터 조회
+            cutoff_date = (datetime.datetime.now() - datetime.timedelta(days=recent_days)).strftime('%Y-%m-%d')
+            
+            cursor = self.conn.execute(
+                "SELECT profit_rate FROM trade_history WHERE sell_date >= ? ORDER BY sell_date DESC",
+                (cutoff_date,)
+            )
+            rows = cursor.fetchall()
+            
+            if len(rows) < 20:  # 최소 20건 이상 필요
+                logger.warning(f"⚠️ 켈리 공식: 데이터 부족 ({len(rows)}건) -> 기본값 10% 리턴")
+                return 0.10
+            
+            # 승률 계산
+            wins = [r['profit_rate'] for r in rows if r['profit_rate'] > 0]
+            losses = [r['profit_rate'] for r in rows if r['profit_rate'] <= 0]
+            
+            total_count = len(rows)
+            win_count = len(wins)
+            win_rate = win_count / total_count
+            loss_rate = 1.0 - win_rate
+            
+            # 손익비 계산 (평균 수익 / 평균 손실)
+            if not wins or not losses:
+                logger.warning("⚠️ 켈리 공식: 승 또는 패만 있음 -> 기본값 10%")
+                return 0.10
+                
+            avg_win = sum(wins) / len(wins)
+            avg_loss = abs(sum(losses) / len(losses))
+            
+            if avg_loss == 0:
+                return 0.50  # 손실이 0이면 최대치
+            
+            odds = avg_win / avg_loss
+            
+            # 켈리 공식: f = (p * b - q) / b
+            # p=승률, b=손익비, q=패율
+            kelly_fraction = ((win_rate * odds) - loss_rate) / odds
+            
+            # 하프 켈리 (안전성 확보)
+            half_kelly = kelly_fraction * 0.5
+            
+            # 음수면 0 리턴 (통계적으로 지는 구조)
+            final_kelly = max(0.0, min(half_kelly, 0.5))  # 최대 50%로 제한
+            
+            logger.info(
+                f"📊 [켈리 분석] 승률:{win_rate*100:.1f}% | 손익비:{odds:.2f} | "
+                f"켈리:{kelly_fraction*100:.1f}% | 하프켈리:{final_kelly*100:.1f}%"
+            )
+            
+            return final_kelly
+            
+        except Exception as e:
+            logger.error(f"❌ 켈리 계산 실패: {e}")
+            return 0.10
+
+    def get_recent_performance(self, days: int = 7) -> Tuple[float, int, int]:
+        """
+        최근 N일 성과 조회
+        
+        Returns:
+            (총손익, 익절횟수, 손절횟수)
+        """
+        try:
+            cutoff = (datetime.datetime.now() - datetime.timedelta(days=days)).strftime('%Y-%m-%d')
+            
+            cursor = self.conn.execute(
+                "SELECT realized_pnl FROM trade_history WHERE sell_date >= ?",
+                (cutoff,)
+            )
+            rows = cursor.fetchall()
+            
+            total_pnl = sum([r['realized_pnl'] for r in rows])
+            wins = len([r for r in rows if r['realized_pnl'] > 0])
+            losses = len([r for r in rows if r['realized_pnl'] <= 0])
+            
+            return total_pnl, wins, losses
+            
+        except Exception as e:
+            logger.error(f"❌ 성과 조회 실패: {e}")
+            return 0.0, 0, 0
+
+    def get_trade_stats(self) -> Dict:
+        """전체 매매 통계"""
+        try:
+            cursor = self.conn.execute("""
+                SELECT 
+                    COUNT(*) as total,
+                    SUM(CASE WHEN profit_rate > 0 THEN 1 ELSE 0 END) as wins,
+                    AVG(profit_rate) as avg_profit_rate,
+                    SUM(realized_pnl) as total_pnl
+                FROM trade_history
+            """)
+            row = cursor.fetchone()
+            
+            return {
+                'total_trades': row['total'] or 0,
+                'win_trades': row['wins'] or 0,
+                'win_rate': (row['wins'] / row['total'] * 100) if row['total'] > 0 else 0,
+                'avg_profit_rate': row['avg_profit_rate'] or 0,
+                'total_pnl': row['total_pnl'] or 0
+            }
+        except Exception as e:
+            logger.error(f"❌ 통계 조회 실패: {e}")
+            return {}
+
+    # ============================================================
+    # [유틸] JSON 마이그레이션
+    # ============================================================
+    
+    def migrate_from_json(self, json_data: Dict):
+        """
+        기존 JSON 포트폴리오를 DB로 마이그레이션
+        
+        Args:
+            json_data: portfolio.json 내용 (딕셔너리)
+        """
+        count = 0
+        for code, info in json_data.items():
+            trade_data = info.copy()
+            trade_data['code'] = code
+            
+            # 필드 매핑 (JSON -> DB)
+            if 'target_qty' not in trade_data:
+                trade_data['target_qty'] = info.get('qty', 0)
+            if 'current_qty' not in trade_data:
+                trade_data['current_qty'] = info.get('qty', 0)
+            if 'total_invested' not in trade_data:
+                trade_data['total_invested'] = info.get('buy_price', 0) * info.get('qty', 0)
+            if 'status' not in trade_data:
+                trade_data['status'] = 'HOLDING'
+                
+            if self.upsert_trade(trade_data):
+                count += 1
+                
+        logger.info(f"✅ JSON -> DB 마이그레이션 완료: {count}개 종목")
+        return count
+
+    # ============================================================
+    # [CRUD] Target Candidates (매수 후보군 관리)
+    # ============================================================
+    
+    def update_target_candidates(self, candidates: List[Dict]):
+        """
+        매수 후보군 업데이트 (5분마다 호출)
+        
+        Args:
+            candidates: [{'code': '005930', 'name': '삼성전자', 'score': 5.2, 'price': 75000}, ...]
+        """
+        try:
+            scan_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            
+            # 기존 데이터 전체 삭제 (5분마다 새로 갱신)
+            with self.conn:
+                self.conn.execute("DELETE FROM target_candidates")
+                
+                # 새 후보군 삽입
+                for item in candidates:
+                    self.conn.execute("""
+                        INSERT INTO target_candidates (code, name, score, price, scan_time, updated_at)
+                        VALUES (?, ?, ?, ?, ?, ?)
+                    """, (
+                        item['code'],
+                        item['name'],
+                        item['score'],
+                        item['price'],
+                        scan_time,
+                        scan_time
+                    ))
+            
+            logger.info(f"✅ 매수 후보군 DB 저장: {len(candidates)}개")
+            return True
+            
+        except Exception as e:
+            logger.error(f"❌ 후보군 저장 실패: {e}")
+            return False
+
+    def add_target_candidate(self, candidate: Dict):
+        """
+        매수 후보군 개별 추가 (통과 즉시 저장용, UPSERT 방식)
+        - 500개 스캔 시 시간이 오래 걸려서 통과하는 즉시 DB에 저장
+        
+        Args:
+            candidate: {'code': '005930', 'name': '삼성전자', 'score': 5.2, 'price': 75000, ...}
+        """
+        try:
+            scan_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            
+            with self.conn:
+                # UPSERT: 있으면 업데이트, 없으면 삽입
+                self.conn.execute("""
+                    INSERT INTO target_candidates (code, name, score, price, scan_time, updated_at)
+                    VALUES (?, ?, ?, ?, ?, ?)
+                    ON CONFLICT(code) DO UPDATE SET
+                        name = excluded.name,
+                        score = excluded.score,
+                        price = excluded.price,
+                        scan_time = excluded.scan_time,
+                        updated_at = excluded.updated_at
+                """, (
+                    candidate['code'],
+                    candidate.get('name', ''),
+                    candidate.get('score', 0),
+                    candidate.get('price', 0),
+                    scan_time,
+                    scan_time
+                ))
+            
+            return True
+            
+        except Exception as e:
+            logger.debug(f"후보 개별 저장 실패({candidate.get('code', '')}): {e}")
+            return False
+    
+    def get_target_candidates(self) -> List[Dict]:
+        """
+        매수 후보군 조회 (점수 순)
+        
+        Returns:
+            [{'code': '005930', 'name': '삼성전자', 'score': 5.2, 'price': 75000}, ...]
+        """
+        try:
+            cursor = self.conn.execute("""
+                SELECT code, name, score, price, scan_time
+                FROM target_candidates
+                ORDER BY score DESC, price ASC
+            """)
+            rows = cursor.fetchall()
+            
+            result = []
+            for row in rows:
+                result.append({
+                    'code': row['code'],
+                    'name': row['name'],
+                    'score': row['score'],
+                    'price': row['price'],
+                    'scan_time': row['scan_time']
+                })
+            
+            return result
+            
+        except Exception as e:
+            logger.error(f"❌ 후보군 조회 실패: {e}")
+            return []
+    
+    def get_trades_by_date(self, date_str: str) -> List[Dict]:
+        """
+        특정 날짜의 매매 기록 조회
+        
+        Args:
+            date_str: 날짜 (YYYYMMDD)
+        
+        Returns:
+            매매 기록 리스트
+        """
+        try:
+            # YYYYMMDD -> YYYY-MM-DD 변환
+            date_formatted = f"{date_str[:4]}-{date_str[4:6]}-{date_str[6:]}"
+            
+            cursor = self.conn.execute("""
+                SELECT * FROM trade_history
+                WHERE DATE(sell_date) = ?
+                ORDER BY sell_date DESC
+            """, (date_formatted,))
+            
+            rows = cursor.fetchall()
+            
+            result = []
+            for row in rows:
+                result.append({
+                    'id': row['id'],
+                    'code': row['code'],
+                    'name': row['name'],
+                    'strategy': row['strategy'],
+                    'buy_price': row['buy_price'],
+                    'sell_price': row['sell_price'],
+                    'qty': row['qty'],
+                    'profit_rate': row['profit_rate'],
+                    'realized_pnl': row['realized_pnl'],
+                    'hold_minutes': row['hold_minutes'],
+                    'buy_date': row['buy_date'],
+                    'sell_date': row['sell_date'],
+                    'sell_reason': row['sell_reason']
+                })
+            
+            return result
+            
+        except Exception as e:
+            logger.error(f"❌ 날짜별 조회 실패: {e}")
+            return []
+
+    # ============================================================
+    # [env_config] 관리자용 env (INSERT만, 최신 1건 = 살아있는 값)
+    # ============================================================
+
+    def insert_env_snapshot(self, snapshot) -> Optional[int]:
+        """
+        env 설정 INSERT (UPDATE 없음). 관리자가 설정 변경할 때 호출.
+        snapshot: dict 또는 JSON 문자열. 키는 ENV_CONFIG_KEYS에 있는 것만 저장.
+        Returns:
+            새 행 id, 실패 시 None
+        """
+        try:
+            if isinstance(snapshot, str):
+                snapshot = json.loads(snapshot) if snapshot else {}
+            if not isinstance(snapshot, dict):
+                return None
+            now = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            key_list = ", ".join(f'"{k}"' for k in ENV_CONFIG_KEYS)
+            placeholders = ", ".join(["?"] * (1 + len(ENV_CONFIG_KEYS)))
+            vals = [now] + [snapshot.get(k) for k in ENV_CONFIG_KEYS]
+            cur = self.conn.execute(
+                f"INSERT INTO env_config (created_at, {key_list}) VALUES ({placeholders})",
+                vals,
+            )
+            self.conn.commit()
+            return cur.lastrowid
+        except Exception as e:
+            logger.error(f"❌ env_config INSERT 실패: {e}")
+            return None
+
+    def get_latest_env(self) -> Optional[Dict]:
+        """
+        살아있는 최신 env 1건 조회 (ORDER BY id DESC LIMIT 1).
+        Returns:
+            {"id": int, "created_at": str, "snapshot": dict} 또는 없으면 None
+        """
+        try:
+            row = self.conn.execute(
+                "SELECT * FROM env_config ORDER BY id DESC LIMIT 1"
+            ).fetchone()
+            if not row:
+                return None
+            snapshot = {
+                k: (row[k] if row[k] is not None else "")
+                for k in ENV_CONFIG_KEYS
+                if k in row.keys()
+            }
+            return {
+                "id": row["id"],
+                "created_at": row["created_at"],
+                "snapshot": snapshot,
+            }
+        except Exception as e:
+            logger.error(f"❌ env_config 최신 조회 실패: {e}")
+            return None
+
+    def close(self):
+        """DB 연결 종료"""
+        if self.conn:
+            self.conn.close()
+            logger.info("🔒 DB 연결 종료")
diff --git a/init_db.py b/init_db.py
new file mode 100644
index 0000000..4698dcb
--- /dev/null
+++ b/init_db.py
@@ -0,0 +1,78 @@
+"""
+KIS 봇용 DB 초기화 스크립트
+- DB 파일 생성 및 테이블 생성
+- 기본 env_config 삽입 (새 스냅샷 행 1개 INSERT)
+
+실행 시점: 자동 실행 없음. 최초 1회 또는 DB 새로 쓸 때만 수동 실행.
+  예: python kis_bot/init_db.py
+- 실행할 때마다 env_config에 새 행이 추가됨(INSERT만, 기존 행 수정 안 함).
+- 봇은 항상 '가장 최신 행(id 최대)'만 사용함.
+- 모의/실전 계좌 둘 다 넣으려면 아래 default_env에 KIS_ACCOUNT_NO(실전), KIS_ACCOUNT_NO_MOCK(모의) 값을 채워두고 실행하면 됨.
+"""
+import os
+import sys
+from pathlib import Path
+
+# 현재 디렉토리를 경로에 추가
+SCRIPT_DIR = Path(__file__).resolve().parent
+sys.path.insert(0, str(SCRIPT_DIR))
+
+from database import TradeDB
+
+def init_database():
+    """DB 초기화 및 기본 설정 삽입"""
+    db_path = SCRIPT_DIR / "quant_bot.db"
+    
+    print(f"📊 DB 초기화 시작: {db_path}")
+    
+    # DB 초기화 (테이블 생성)
+    db = TradeDB(db_path=str(db_path))
+    
+    # 기본 env_config 삽입
+    default_env = {
+        # 한투 API 설정
+        "KIS_APP_KEY": os.environ.get("KIS_APP_KEY", ""),
+        "KIS_APP_SECRET": os.environ.get("KIS_APP_SECRET", ""),
+        "KIS_ACCOUNT_NO": os.environ.get("KIS_ACCOUNT_NO", ""),
+        "KIS_ACCOUNT_CODE": os.environ.get("KIS_ACCOUNT_CODE", "01"),
+        "KIS_ACCOUNT_NO_MOCK": os.environ.get("KIS_ACCOUNT_NO_MOCK", ""),
+        "KIS_ACCOUNT_CODE_MOCK": os.environ.get("KIS_ACCOUNT_CODE_MOCK", "01"),
+        "KIS_MOCK": os.environ.get("KIS_MOCK", "true"),
+        
+        # 단타 봇 설정
+        "STOP_LOSS_PCT": "-0.03",
+        "TAKE_PROFIT_PCT": "0.05",
+        "MIN_DROP_RATE": "0.03",
+        "MIN_RECOVERY_RATIO_SHORT": "0.5",
+        "MAX_STOCKS": "3",
+        
+        # 늘림목 봇 설정
+        "MAX_PER": "25",
+        "MAX_PEG": "1.5",
+        "MIN_GROWTH_PCT": "10",
+        "MAX_POSITION_PCT": "0.20",
+        "STOP_LOSS_PCT": "-0.30",
+        "TAKE_PROFIT_PCT": "0.50",
+        
+        # 공통 설정
+        "USE_RISK_CHECK": "true",
+        "DAILY_STOP_LOSS_PCT": "-0.05",
+        "CONSECUTIVE_LOSS_LIMIT": "4",
+        "MAX_LOSS_PER_TRADE_KRW": "200000",
+        "USE_BAN_SYSTEM": "true",
+        "BAN_HOURS": "24",
+        "USE_STOCK_FILTER": "true",
+        "FORCE_MARKET_OPEN": "false",
+    }
+    
+    env_id = db.insert_env_snapshot(default_env)
+    if env_id:
+        print(f"✅ 기본 env_config 삽입 완료 (id: {env_id})")
+    else:
+        print("⚠️ env_config 삽입 실패")
+    
+    print(f"✅ DB 초기화 완료: {db_path}")
+    db.close()
+
+if __name__ == "__main__":
+    init_database()
diff --git a/kis_long_ver1.py b/kis_long_ver1.py
new file mode 100644
index 0000000..24e2b7f
--- /dev/null
+++ b/kis_long_ver1.py
@@ -0,0 +1,1668 @@
+"""
+KIS Long Trading Bot Ver1 - 늘림목 전략용 한투 API 트레이딩 시스템
+- 한국투자증권(KIS) Open API 사용
+- 장기 보유 + 분할 매수(늘림목) 전략
+- PER/PEG 기반 밸류에이션
+- kis_long_term_checker.py의 장기 전략을 참고하되, 늘림목 전략으로 수정
+"""
+
+import os
+import json
+import time
+import random
+import logging
+import datetime
+import hashlib
+import hmac
+import base64
+import warnings
+import asyncio
+from datetime import datetime as dt, timedelta
+from pathlib import Path
+from typing import List, Dict, Optional
+
+import pandas as pd
+import requests
+
+# DB 모듈 임포트
+from database import TradeDB
+
+# 로깅 설정 (먼저 초기화)
+logging.basicConfig(
+    format='[%(asctime)s] %(message)s',
+    datefmt='%H:%M:%S',
+    level=logging.INFO
+)
+logger = logging.getLogger("KISLongBot")
+
+# Gemini API (AI 리포트용)
+warnings.filterwarnings("ignore", message=".*google.generativeai.*")
+try:
+    import google.generativeai as genai
+    GEMINI_AVAILABLE = True
+except ImportError:
+    GEMINI_AVAILABLE = False
+    logger.warning("⚠️ google-generativeai 미설치 - AI 리포트 기능 사용 불가")
+
+# ML 예측 (선택적)
+try:
+    from ml_predictor import MLPredictor
+    ML_AVAILABLE = True
+except ImportError:
+    ML_AVAILABLE = False
+    logger.warning("⚠️ ml_predictor 미설치 - ML 예측 기능 사용 불가")
+
+# DB 초기화
+SCRIPT_DIR = Path(__file__).resolve().parent
+db = TradeDB(db_path=str(SCRIPT_DIR / "quant_bot.db"))
+
+# DB에서 환경변수 로드 (초기 버전: Mattermost/Gemini 설정용)
+def get_env_from_db(key, default=""):
+    """DB에서 환경변수 읽기 (초기화 단계)"""
+    env_data = db.get_latest_env()
+    if env_data and env_data.get("snapshot"):
+        return env_data["snapshot"].get(key, default)
+    return default
+
+# Mattermost 설정
+MM_SERVER_URL = get_env_from_db("MM_SERVER_URL", "https://mattermost.hoonfam.org")
+MM_BOT_TOKEN = get_env_from_db("MM_BOT_TOKEN_", "").strip()
+MM_CONFIG_FILE = SCRIPT_DIR / "mm_config.json"
+# 기본 채널(alias) + 롱/늘림목 봇 전용 채널(alias)
+MM_CHANNEL_DEFAULT = get_env_from_db("MATTERMOST_CHANNEL", "stock")
+MM_CHANNEL_LONG = get_env_from_db("KIS_LONG_MM_CHANNEL", MM_CHANNEL_DEFAULT)
+
+# Gemini API 설정 (기존 google.generativeai 그대로 유지; 추후 google.genai로 마이그레이션 가능)
+GEMINI_API_KEY = get_env_from_db("GEMINI_API_KEY", "").strip()
+if GEMINI_API_KEY and 'GEMINI_AVAILABLE' in globals() and GEMINI_AVAILABLE:
+    try:
+        genai.configure(api_key=GEMINI_API_KEY)
+        gemini_model = genai.GenerativeModel('gemini-2.5-flash')
+    except Exception as e:
+        logger.warning(f"⚠️ Gemini 초기화 실패: {e}")
+        gemini_model = None
+else:
+    gemini_model = None
+
+def get_env_float(key, default):
+    """환경변수를 float로 변환 (DB 우선)"""
+    value = get_env_from_db(key, str(default))
+    if isinstance(value, str) and "#" in value:
+        value = value.split("#")[0].strip()
+    try:
+        return float(value) if value else default
+    except (ValueError, TypeError):
+        return default
+
+def get_env_int(key, default):
+    """환경변수를 int로 변환 (DB 우선)"""
+    value = get_env_from_db(key, str(default))
+    if isinstance(value, str) and "#" in value:
+        value = value.split("#")[0].strip()
+    try:
+        return int(value) if value else default
+    except (ValueError, TypeError):
+        return default
+
+def get_env_bool(key, default=False):
+    """환경변수를 bool로 변환 (DB 우선)"""
+    value = get_env_from_db(key, str(default)).lower()
+    return value in ("true", "1", "yes")
+
+# ============================================================
+# 한투(KIS) API 클라이언트 (kis_long_term_checker.py 참고)
+# ============================================================
+KIS_TOKEN_CACHE_PATH = SCRIPT_DIR / ".kis_token_cache.json"
+KIS_TOKEN_EXPIRE_MARGIN_SEC = 300
+
+
+def _load_kis_token_cache(mock):
+    """캐시 파일에서 토큰 로드"""
+    if not KIS_TOKEN_CACHE_PATH.exists():
+        return None
+    try:
+        with open(KIS_TOKEN_CACHE_PATH, "r", encoding="utf-8") as f:
+            cache = json.load(f)
+        if cache.get("mock") != mock:
+            return None
+        token = cache.get("access_token")
+        expired_str = cache.get("access_token_token_expired") or cache.get("expires_at")
+        if not token or not expired_str:
+            return None
+        try:
+            expired_dt = dt.strptime(expired_str.strip()[:19], "%Y-%m-%d %H:%M:%S")
+        except ValueError:
+            return None
+        if dt.now() >= expired_dt - timedelta(seconds=KIS_TOKEN_EXPIRE_MARGIN_SEC):
+            return None
+        return token
+    except Exception:
+        return None
+
+
+def _save_kis_token_cache(access_token, access_token_token_expired, mock):
+    """토큰 캐시 저장"""
+    try:
+        with open(KIS_TOKEN_CACHE_PATH, "w", encoding="utf-8") as f:
+            json.dump({
+                "access_token": access_token,
+                "access_token_token_expired": access_token_token_expired,
+                "mock": mock,
+            }, f, ensure_ascii=False, indent=0)
+    except Exception:
+        pass
+
+
+class KISClientWithOrder:
+    """주문 기능이 추가된 KIS 클라이언트"""
+    def __init__(self, mock=None):
+        # DB에서 환경변수 읽기
+        self.app_key = get_env_from_db("KIS_APP_KEY", "").strip()
+        self.app_secret = get_env_from_db("KIS_APP_SECRET", "").strip()
+        # 모의 여부 결정
+        if mock is not None:
+            use_mock = mock
+        else:
+            use_mock = get_env_bool("KIS_MOCK", True)
+        
+        # 계좌번호: 모의/실전 분리 (사용자가 8자리로 직접 입력)
+        if use_mock:
+            raw_no_mock = get_env_from_db("KIS_ACCOUNT_NO_MOCK", "").strip()
+            raw_code_mock = get_env_from_db("KIS_ACCOUNT_CODE_MOCK", "").strip()
+            if raw_no_mock:
+                raw_no = raw_no_mock
+                if raw_code_mock:
+                    raw_code = raw_code_mock
+                else:
+                    raw_code = "01"
+            else:
+                raw_no = get_env_from_db("KIS_ACCOUNT_NO", "").strip()
+                raw_code = get_env_from_db("KIS_ACCOUNT_CODE", "01").strip()
+                if not raw_code:
+                    raw_code = "01"
+        else:
+            raw_no = get_env_from_db("KIS_ACCOUNT_NO", "").strip()
+            raw_code = get_env_from_db("KIS_ACCOUNT_CODE", "01").strip()
+            if not raw_code:
+                raw_code = "01"
+        
+        # DB 값 그대로 사용 (10자리면 앞8/뒤2만 분리)
+        if len(raw_no) >= 10:
+            self.acc_no = raw_no[:8]
+            self.acc_code = raw_no[8:10]
+        else:
+            self.acc_no = raw_no
+            if len(raw_code) >= 2:
+                self.acc_code = raw_code[:2]
+            else:
+                self.acc_code = "01"
+            if len(self.acc_no) != 8:
+                logger.warning("⚠️ 계좌번호 CANO 8자리 아님: '%s'(%s자리). DB 확인.", self.acc_no, len(self.acc_no))
+        
+        if len(self.acc_no) != 8 or len(self.acc_code) != 2:
+            logger.error(
+                "❌ 계좌번호 형식 오류: CANO=%s(%s자리), ACNT_PRDT_CD=%s(%s자리) → OPSQ2000 발생. "
+                "모의면 KIS_ACCOUNT_NO_MOCK/KIS_ACCOUNT_CODE_MOCK, 실전이면 KIS_ACCOUNT_NO/KIS_ACCOUNT_CODE 확인.",
+                self.acc_no, len(self.acc_no), self.acc_code, len(self.acc_code)
+            )
+        else:
+            logger.info("✅ 한투 계좌 CANO=%s, ACNT_PRDT_CD=%s (모의=%s)", self.acc_no, self.acc_code, use_mock)
+        self.mock = use_mock
+        # 모의(True)=모의 URL, 실전(False)=실전 URL (self.mock 사용, 인자 mock은 None일 수 있음)
+        if self.mock is True:
+            self.base_url = "https://openapivts.koreainvestment.com:29443"
+        else:
+            self.base_url = "https://openapi.koreainvestment.com:9443"
+        self.access_token = None
+        self._auth()
+    
+    def _auth(self):
+        """접근 토큰 발급"""
+        if not self.app_key or not self.app_secret:
+            raise ValueError("KIS_APP_KEY, KIS_APP_SECRET 설정 필요")
+        
+        cached = _load_kis_token_cache(self.mock)
+        if cached:
+            self.access_token = cached
+            logger.info("한투 토큰 캐시 사용 (%s)", "모의" if self.mock else "실전")
+            return
+        
+        url = f"{self.base_url}/oauth2/tokenP"
+        body = {"grant_type": "client_credentials", "appkey": self.app_key, "appsecret": self.app_secret}
+        try:
+            r = requests.post(url, json=body, timeout=10)
+            data = r.json()
+            if "access_token" in data:
+                self.access_token = data["access_token"]
+                expired = data.get("access_token_token_expired") or ""
+                _save_kis_token_cache(self.access_token, expired, self.mock)
+                logger.info("한투 토큰 발급 완료 (%s)", "모의" if self.mock else "실전")
+            else:
+                raise RuntimeError("한투 토큰 발급 실패")
+        except Exception as e:
+            logger.error("한투 인증 예외: %s", e)
+            raise
+    
+    def _get_hashkey(self, body):
+        """해시키(Hashkey) 발급 - POST 요청 시 body 무결성 검증용"""
+        try:
+            url = f"{self.base_url}/uapi/hashkey"
+            headers = {
+                "content-type": "application/json",
+                "appkey": self.app_key,
+                "appsecret": self.app_secret,
+            }
+            r = requests.post(url, headers=headers, json=body, timeout=5)
+            if r.status_code == 200:
+                data = r.json()
+                if data.get("rt_cd") == "0":
+                    return data.get("HASH")
+            return None
+        except Exception as e:
+            logger.debug(f"해시키 발급 실패: {e}")
+            return None
+
+    def _headers(self, tr_id, hashkey=None):
+        """API 호출용 헤더"""
+        headers = {
+            "content-type": "application/json; charset=utf-8",
+            "authorization": f"Bearer {self.access_token}",
+            "appkey": self.app_key,
+            "appsecret": self.app_secret,
+            "tr_id": tr_id,
+        }
+        if hashkey:
+            headers["hashkey"] = hashkey
+        return headers
+    
+    def _get(self, path, tr_id, params, max_retries=3):
+        """GET 요청. 429 시 지수 백오프 재시도"""
+        url = f"{self.base_url}{path}"
+        for attempt in range(max_retries):
+            try:
+                r = requests.get(url, headers=self._headers(tr_id), params=params, timeout=15)
+                if r.status_code == 429:
+                    wait_time = (2 ** attempt) + random.uniform(0.5, 1.5)
+                    logger.warning(f"⏳ API 호출 제한 (429) -> {wait_time:.1f}초 대기 후 재시도 ({attempt+1}/{max_retries})")
+                    time.sleep(wait_time)
+                    continue
+                if r.status_code == 200:
+                    j = r.json()
+                    if j.get("rt_cd") == "0":
+                        return r
+                    elif "초과" in str(j.get("msg1", "")) or "과부하" in str(j.get("msg1", "")):
+                        wait_time = (2 ** attempt) + random.uniform(0.5, 1.5)
+                        logger.warning(f"⏳ API 과부하 -> {wait_time:.1f}초 대기 후 재시도")
+                        time.sleep(wait_time)
+                        continue
+                return r
+            except requests.exceptions.RequestException as e:
+                if attempt < max_retries - 1:
+                    wait_time = (2 ** attempt) + random.uniform(0.5, 1.5)
+                    logger.warning(f"⚠️ 네트워크 에러 -> {wait_time:.1f}초 대기 후 재시도: {e}")
+                    time.sleep(wait_time)
+                else:
+                    logger.error(f"❌ GET 요청 실패 ({path}): {e}")
+        return r
+    
+    def inquire_price(self, stock_code):
+        """주식 현재가 시세 조회 [v1_국내주식-008]"""
+        r = self._get(
+            "/uapi/domestic-stock/v1/quotations/inquire-price",
+            "FHKST01010100",
+            {"FID_COND_MRKT_DIV_CODE": "J", "FID_INPUT_ISCD": stock_code},
+        )
+        if r.status_code != 200:
+            return None
+        j = r.json()
+        if j.get("rt_cd") != "0":
+            return None
+        return j.get("output")
+    
+    def get_orderbook(self, stock_code):
+        """호가 조회 [v1_국내주식-009]"""
+        try:
+            r = self._get(
+                "/uapi/domestic-stock/v1/quotations/inquire-asking-price-exp-ccn",
+                "FHKST01010200",
+                {
+                    "FID_COND_MRKT_DIV_CODE": "J",
+                    "FID_INPUT_ISCD": stock_code,
+                },
+            )
+            if r.status_code != 200:
+                return None
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                return None
+            return j.get("output")
+        except Exception as e:
+            logger.error(f"호가 조회 실패({stock_code}): {e}")
+            return None
+    
+    def get_account_evaluation(self):
+        """계좌 평가 잔고 조회 [v1_국내주식-011]. 모의=VTTC8494R, 실전=TTTC8494R."""
+        if self.mock is True:
+            tr_id = "VTTC8494R"
+        else:
+            tr_id = "TTTC8494R"
+        try:
+            r = self._get(
+                "/uapi/domestic-stock/v1/trading/inquire-balance-rlz-pl",
+                tr_id,
+                {
+                    "CANO": self.acc_no,
+                    "ACNT_PRDT_CD": self.acc_code,
+                    "AFHR_FLPR_YN": "N",
+                    "OFL_YN": "",
+                    "INQR_DVSN": "01",
+                    "UNPR_DVSN": "01",
+                    "FUND_STTL_ICLD_YN": "N",
+                    "FNCG_AMT_AUTO_RDPT_YN": "N",
+                    "PRCS_DVSN": "01",
+                    "CTX_AREA_FK100": "",
+                    "CTX_AREA_NK100": "",
+                },
+            )
+            if r.status_code != 200:
+                return None
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                return None
+            return j
+        except Exception as e:
+            logger.error(f"계좌 평가 조회 실패: {e}")
+            return None
+    
+    def inquire_daily_itemchartprice(self, stock_code, start_ymd, end_ymd, period="D", adj="1"):
+        """국내주식 기간별 시세(일봉)"""
+        r = self._get(
+            "/uapi/domestic-stock/v1/quotations/inquire-daily-itemchartprice",
+            "FHKST03010100",
+            {
+                "FID_COND_MRKT_DIV_CODE": "J",
+                "FID_INPUT_ISCD": stock_code,
+                "FID_INPUT_DATE_1": start_ymd,
+                "FID_INPUT_DATE_2": end_ymd,
+                "FID_PERIOD_DIV_CODE": period,
+                "FID_ORG_ADJ_PRC": adj,
+            },
+        )
+        if r.status_code != 200:
+            return [], []
+        j = r.json()
+        if j.get("rt_cd") != "0":
+            return [], []
+        out1 = j.get("output1") or {}
+        out2 = j.get("output2") or []
+        return out1, out2
+    
+    def finance_financial_ratio(self, stock_code, fid_div_cls_code="0"):
+        """국내주식 재무비율"""
+        try:
+            r = self._get(
+                "/uapi/domestic-stock/v1/finance/financial-ratio",
+                "FHKST66430300",
+                {
+                    "FID_DIV_CLS_CODE": fid_div_cls_code,
+                    "FID_COND_MRKT_DIV_CODE": "J",
+                    "FID_INPUT_ISCD": stock_code,
+                },
+            )
+            if r.status_code != 200:
+                return None
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                return None
+            out = j.get("output")
+            if isinstance(out, list) and out:
+                return out[0]
+            return out if isinstance(out, dict) else None
+        except Exception:
+            return None
+    
+    def finance_growth_ratio(self, stock_code, fid_div_cls_code="0"):
+        """국내주식 성장성비율"""
+        try:
+            r = self._get(
+                "/uapi/domestic-stock/v1/finance/growth-ratio",
+                "FHKST66430800",
+                {
+                    "FID_INPUT_ISCD": stock_code,
+                    "FID_DIV_CLS_CODE": fid_div_cls_code,
+                    "FID_COND_MRKT_DIV_CODE": "J",
+                },
+            )
+            if r.status_code != 200:
+                return None
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                return None
+            out = j.get("output")
+            if isinstance(out, list) and out:
+                return out[0]
+            return out if isinstance(out, dict) else None
+        except Exception:
+            return None
+
+    def _post(self, path, tr_id, body, use_hashkey=True, max_retries=3):
+        """POST 요청. 해시키 사용 및 429 시 지수 백오프 재시도"""
+        url = f"{self.base_url}{path}"
+        hashkey = None
+        
+        if use_hashkey:
+            hashkey = self._get_hashkey(body)
+            if not hashkey:
+                logger.debug("해시키 발급 실패, 해시키 없이 진행")
+        
+        for attempt in range(max_retries):
+            try:
+                r = requests.post(url, headers=self._headers(tr_id, hashkey), json=body, timeout=15)
+                if r.status_code == 429:
+                    wait_time = (2 ** attempt) + random.uniform(0.5, 1.5)
+                    logger.warning(f"⏳ API 호출 제한 (429) -> {wait_time:.1f}초 대기 후 재시도 ({attempt+1}/{max_retries})")
+                    time.sleep(wait_time)
+                    if use_hashkey:
+                        hashkey = self._get_hashkey(body)
+                    continue
+                if r.status_code == 200:
+                    j = r.json()
+                    if j.get("rt_cd") == "0":
+                        return r
+                    elif "초과" in str(j.get("msg1", "")) or "과부하" in str(j.get("msg1", "")):
+                        wait_time = (2 ** attempt) + random.uniform(0.5, 1.5)
+                        logger.warning(f"⏳ API 과부하 -> {wait_time:.1f}초 대기 후 재시도")
+                        time.sleep(wait_time)
+                        if use_hashkey:
+                            hashkey = self._get_hashkey(body)
+                        continue
+                return r
+            except requests.exceptions.RequestException as e:
+                if attempt < max_retries - 1:
+                    wait_time = (2 ** attempt) + random.uniform(0.5, 1.5)
+                    logger.warning(f"⚠️ 네트워크 에러 -> {wait_time:.1f}초 대기 후 재시도: {e}")
+                    time.sleep(wait_time)
+                else:
+                    logger.error(f"❌ POST 요청 실패 ({path}): {e}")
+        return r
+
+    def buy_order(self, code, qty, price=0, order_type="01"):
+        """매수 주문 (모의=VTTC0802U, 실전=TTTC0802U) - 고급 주문 타입 지원"""
+        try:
+            if self.mock:
+                tr_id = "VTTC0802U"
+            else:
+                tr_id = "TTTC0802U"
+            body = {
+                "CANO": self.acc_no,
+                "ACNT_PRDT_CD": self.acc_code,
+                "PDNO": code,
+                "ORD_DVSN": order_type,
+                "ORD_QTY": str(qty),
+                "ORD_UNPR": str(price) if price > 0 else "0",
+            }
+            r = self._post(
+                "/uapi/domestic-stock/v1/trading/order-cash",
+                tr_id,
+                body,
+                use_hashkey=True
+            )
+            if r.status_code != 200:
+                logger.error(f"매수 주문 HTTP 에러: {r.status_code}")
+                return False
+            j = r.json()
+            if j.get("rt_cd") == "0":
+                ord_no = j.get("output", {}).get("ODNO", "")
+                logger.info(f"✅ 매수 주문 성공: {code} {qty}주 (주문번호: {ord_no})")
+                return True
+            else:
+                logger.error(f"매수 주문 실패: {j.get('msg1', '알 수 없음')}")
+                return False
+        except Exception as e:
+            logger.error(f"매수 주문 예외({code}): {e}")
+            return False
+
+    def buy_market_order(self, code, qty):
+        """시장가 매수 주문 (간편 메서드)"""
+        return self.buy_order(code, qty, price=0, order_type="01")
+
+    def sell_order(self, code, qty, price=0, order_type="01"):
+        """매도 주문 (모의=VTTC0801U, 실전=TTTC0801U) - 고급 주문 타입 지원"""
+        try:
+            if self.mock:
+                tr_id = "VTTC0801U"
+            else:
+                tr_id = "TTTC0801U"
+            body = {
+                "CANO": self.acc_no,
+                "ACNT_PRDT_CD": self.acc_code,
+                "PDNO": code,
+                "ORD_DVSN": order_type,
+                "ORD_QTY": str(qty),
+                "ORD_UNPR": str(price) if price > 0 else "0",
+            }
+            r = self._post(
+                "/uapi/domestic-stock/v1/trading/order-cash",
+                tr_id,
+                body,
+                use_hashkey=True
+            )
+            if r.status_code != 200:
+                logger.error(f"매도 주문 HTTP 에러: {r.status_code}")
+                return False
+            j = r.json()
+            if j.get("rt_cd") == "0":
+                ord_no = j.get("output", {}).get("ODNO", "")
+                logger.info(f"✅ 매도 주문 성공: {code} {qty}주 (주문번호: {ord_no})")
+                return True
+            else:
+                logger.error(f"매도 주문 실패: {j.get('msg1', '알 수 없음')}")
+                return False
+        except Exception as e:
+            logger.error(f"매도 주문 예외({code}): {e}")
+            return False
+
+    def sell_market_order(self, code, qty):
+        """시장가 매도 주문 (간편 메서드)"""
+        return self.sell_order(code, qty, price=0, order_type="01")
+    
+    def inquire_prices_batch(self, stock_codes: List[str]):
+        """다중 종목 현재가 일괄 조회 (최대 20개)"""
+        if not stock_codes or len(stock_codes) > 20:
+            logger.warning("종목 코드는 1~20개만 가능")
+            return {}
+        
+        result = {}
+        # 한투 API는 다중 종목 조회를 지원하지 않으므로 순차 조회
+        for code in stock_codes:
+            try:
+                price_data = self.inquire_price(code)
+                if price_data:
+                    result[code] = price_data
+                time.sleep(random.uniform(0.1, 0.3))
+            except Exception as e:
+                logger.debug(f"종목 조회 실패({code}): {e}")
+                continue
+        
+        return result
+    
+    def get_investor_trend(self, stock_code, days=5):
+        """외국인/기관 매매 동향 조회"""
+        try:
+            end_dt = dt.now()
+            start_dt = end_dt - timedelta(days=days + 10)
+            start_ymd = start_dt.strftime("%Y%m%d")
+            end_ymd = end_dt.strftime("%Y%m%d")
+            
+            _, out2 = self.inquire_daily_itemchartprice(stock_code, start_ymd, end_ymd, "D", "1")
+            if not out2:
+                return None
+            
+            foreign_sum = 0
+            org_sum = 0
+            
+            for item in out2[:days]:
+                try:
+                    foreign_raw = item.get("frgn_ntby_qty") or item.get("frgn_ntby_shnu") or "0"
+                    foreign_net = int(float(str(foreign_raw).replace(",", "").replace("+", "").replace("-", "")))
+                    if str(foreign_raw).startswith("-"):
+                        foreign_net = -foreign_net
+                    
+                    org_raw = item.get("orgn_ntby_qty") or "0"
+                    org_net = int(float(str(org_raw).replace(",", "").replace("+", "").replace("-", "")))
+                    if str(org_raw).startswith("-"):
+                        org_net = -org_net
+                    
+                    foreign_sum += foreign_net
+                    org_sum += org_net
+                except:
+                    continue
+            
+            return {
+                "foreign_net_buy": foreign_sum,
+                "org_net_buy": org_sum,
+                "total_net_buy": foreign_sum + org_sum,
+            }
+        except Exception as e:
+            logger.error(f"외국인/기관 동향 조회 실패({stock_code}): {e}")
+            return None
+
+
+# ============================================================
+# 헬퍼 함수들 (kis_long_term_checker.py 참고)
+# ============================================================
+def get_kis_daily_chart(client, stock_code, max_days=65, exchange=None):
+    """한투 일봉 조회 후 DataFrame 반환"""
+    end_dt = dt.now()
+    end_ymd = end_dt.strftime("%Y%m%d")
+    
+    if exchange:
+        return pd.DataFrame()  # 해외 종목은 미구현
+    
+    start_dt = end_dt - timedelta(days=max_days + 30)
+    start_ymd = start_dt.strftime("%Y%m%d")
+    _, out2 = client.inquire_daily_itemchartprice(stock_code, start_ymd, end_ymd, "D", "1")
+    if not out2:
+        return pd.DataFrame()
+    
+    rows = []
+    for b in out2:
+        try:
+            date_str = (b.get("stck_bsop_date") or "").strip()
+            close_p = abs(float(str(b.get("stck_clpr") or "0").replace(",", "")))
+            open_p = abs(float(str(b.get("stck_oprc") or "0").replace(",", "")))
+            high_p = abs(float(str(b.get("stck_hgpr") or "0").replace(",", "")))
+            low_p = abs(float(str(b.get("stck_lwpr") or "0").replace(",", "")))
+            vol = int(float(str(b.get("acml_vol") or "0").replace(",", "")))
+        except (TypeError, ValueError):
+            continue
+        if date_str and close_p > 0:
+            rows.append({"dt": date_str, "open": open_p, "high": high_p, "low": low_p, "close": close_p, "volume": vol})
+    
+    if not rows:
+        return pd.DataFrame()
+    df = pd.DataFrame(rows)
+    df = df.sort_values("dt").reset_index(drop=True)
+    df["MA20"] = df["close"].rolling(window=20).mean()
+    df["MA60"] = df["close"].rolling(window=60).mean()
+    return df
+
+
+def calculate_volatility(df, period=20):
+    """변동성 계산 (20일 표준편차 / 평균 * 100)"""
+    if df is None or df.empty or len(df) < period:
+        return None
+    try:
+        returns = df["close"].pct_change().dropna()
+        volatility = returns.tail(period).std() * 100
+        return round(volatility, 2) if pd.notna(volatility) else None
+    except Exception:
+        return None
+
+
+def get_kis_per_eps_peg(client, stock_code, current_price):
+    """한투 재무비율·성장성비율로 PER, EPS, 성장률, PEG 계산"""
+    try:
+        fin = client.finance_financial_ratio(stock_code, "0")
+        growth = client.finance_growth_ratio(stock_code, "0")
+        time.sleep(random.uniform(1, 2))
+        
+        per, eps = None, None
+        if fin:
+            try:
+                eps_raw = fin.get("eps") or fin.get("EPS")
+                if eps_raw is not None:
+                    eps = float(str(eps_raw).replace(",", "").strip())
+                per_raw = fin.get("per") or fin.get("PER")
+                if per_raw is not None:
+                    per = float(str(per_raw).replace(",", "").strip())
+            except (TypeError, ValueError):
+                pass
+            if per is None and eps is not None and eps > 0 and current_price and current_price > 0:
+                per = current_price / eps
+        if per is not None and per <= 0:
+            per = None
+        
+        growth_pct = None
+        if growth:
+            for key in ("bsop_prfi_inrt", "ntin_inrt", "grs"):
+                val = growth.get(key)
+                if val is not None:
+                    try:
+                        growth_pct = float(str(val).replace(",", "").strip())
+                        if growth_pct != 0:
+                            break
+                    except (TypeError, ValueError):
+                        continue
+        if fin and growth_pct is None:
+            growth_pct = fin.get("ntin_inrt") or fin.get("bsop_prfi_inrt")
+            if growth_pct is not None:
+                try:
+                    growth_pct = float(str(growth_pct).replace(",", "").strip())
+                except (TypeError, ValueError):
+                    growth_pct = None
+        
+        peg = None
+        if per is not None and growth_pct is not None and growth_pct > 0:
+            peg = round(per / growth_pct, 2)
+        
+        return {"per": per, "eps": eps, "growth_pct": growth_pct, "peg": peg}
+    except Exception as e:
+        logger.error(f"PER/PEG 계산 실패 {stock_code}: {e}")
+        return {"per": None, "eps": None, "growth_pct": None, "peg": None}
+
+
+# ============================================================
+# Mattermost 봇 클래스
+# ============================================================
+class MattermostBot:
+    """Mattermost 알림 봇"""
+    def __init__(self):
+        self.api_url = f"{MM_SERVER_URL.rstrip('/')}/api/v4/posts"
+        self.headers = {
+            "Authorization": f"Bearer {MM_BOT_TOKEN}",
+            "Content-Type": "application/json"
+        }
+        self.channels = self._load_channels()
+
+    def _load_channels(self):
+        """채널 설정 로드"""
+        try:
+            if MM_CONFIG_FILE.exists():
+                with open(MM_CONFIG_FILE, 'r', encoding='utf-8') as f:
+                    return json.load(f).get("channels", {})
+            return {}
+        except Exception as e:
+            logger.error(f"⚠️ MM 설정 로드 실패: {e}")
+            return {}
+
+    def send(self, channel_alias, message):
+        """메시지 전송"""
+        channel_id = self.channels.get(channel_alias)
+        if not channel_id:
+            logger.warning(f"❌ '{channel_alias}' 채널 ID 없음")
+            return False
+
+        payload = {"channel_id": channel_id, "message": message}
+        try:
+            res = requests.post(self.api_url, headers=self.headers, json=payload, timeout=3)
+            res.raise_for_status()
+            return True
+        except Exception as e:
+            logger.error(f"❌ MM 전송 에러: {e}")
+            return False
+
+
+# ============================================================
+# 늘림목 트레이딩 봇
+# ============================================================
+class LongTradingBot:
+    """늘림목 전략 트레이딩 봇 - 장기 보유 + 분할 매수"""
+    def __init__(self):
+        self.db = db
+        self.client = KISClientWithOrder()
+        
+        # Mattermost 초기화
+        self.mm = MattermostBot()
+        # 롱/늘림목 봇 전용 채널(alias) 우선 사용, 없으면 기본 채널 사용
+        self.mm_channel = MM_CHANNEL_LONG
+        
+        # 전략 파라미터 (DB에서 읽기)
+        self.max_per = get_env_float("MAX_PER", 25)
+        self.max_peg = get_env_float("MAX_PEG", 1.5)
+        self.min_growth_pct = get_env_float("MIN_GROWTH_PCT", 10)
+        
+        # 늘림목 파라미터
+        dca_intervals_str = get_env_from_db("DCA_INTERVALS", "0,-0.05,-0.10,-0.15,-0.20")
+        self.dca_intervals = [float(x.strip()) for x in dca_intervals_str.split(",") if x.strip()]
+        dca_amounts_str = get_env_from_db("DCA_AMOUNTS", "100000,100000,100000,100000,100000")
+        self.dca_amounts = [int(x.strip()) for x in dca_amounts_str.split(",") if x.strip()]
+        self.max_position_pct = get_env_float("MAX_POSITION_PCT", 0.20)
+        
+        # 손절/익절
+        self.stop_loss_pct = get_env_float("STOP_LOSS_PCT", -0.30)
+        self.take_profit_pct = get_env_float("TAKE_PROFIT_PCT", 0.50)
+        
+        # DB에서 활성 트레이드 로드
+        self.holdings = {}
+        active_trades = self.db.get_active_trades()
+        for code, trade in active_trades.items():
+            # 분할 매수 정보 복원 (간단화)
+            self.holdings[code] = {
+                "buy_prices": [trade.get("avg_buy_price", 0)],
+                "qtys": [trade.get("current_qty", 0)],
+                "total_qty": trade.get("current_qty", 0),
+                "avg_price": trade.get("avg_buy_price", 0),
+                "first_buy_date": trade.get("buy_date", dt.now().strftime("%Y-%m-%d %H:%M:%S")),
+                "name": trade.get("name", code),
+            }
+        
+        # 관심 종목 리스트 (JSON 파일에서 로드)
+        self.watchlist_path = SCRIPT_DIR / "long_term_watchlist.json"
+        self.watchlist = self._load_watchlist()
+        
+        # 초기 자산 조회
+        self._update_assets()
+        
+        # 비동기 태스크 관리
+        self._report_task = None
+        self._asset_task = None
+        
+    def _load_watchlist(self):
+        """관심 종목 리스트 로드"""
+        if not self.watchlist_path.exists():
+            logger.warning(f"관심 종목 파일 없음: {self.watchlist_path}")
+            return []
+        
+        try:
+            with open(self.watchlist_path, "r", encoding="utf-8") as f:
+                data = json.load(f)
+            return data.get("items", [])
+        except Exception as e:
+            logger.error(f"관심 종목 로드 실패: {e}")
+            return []
+
+    def _update_assets(self):
+        """자산 정보 업데이트"""
+        try:
+            balance = self.client.get_account_evaluation()
+            if balance:
+                output1 = balance.get("output1", {})
+                self.current_cash = float(output1.get("dnca_tot_amt", 0))
+                # 보유 종목 평가액 계산
+                holdings_value = 0
+                for code, holding in self.holdings.items():
+                    price_data = self.client.inquire_price(code)
+                    if price_data:
+                        current_price = abs(float(price_data.get("stck_prpr", 0)))
+                        holdings_value += current_price * holding["total_qty"]
+                
+                self.current_total_asset = self.current_cash + holdings_value
+                
+                # 오늘 첫 실행 시 시작 자산 저장
+                if self.start_day_asset == 0:
+                    self.start_day_asset = self.current_total_asset
+        except Exception as e:
+            logger.error(f"자산 정보 업데이트 실패: {e}")
+    
+    def _update_account_light(self, profit_val=0):
+        """
+        경량 계좌 갱신 (매수/매도 직후 즉시 호출!)
+        - API 부하를 줄이기 위해 예수금 + 보유 종목 평가액만 빠르게 계산
+        - 총자산 = 예수금 + 보유 종목 평가액 (+ 손익 반영)
+        """
+        try:
+            balance = self.client.get_account_evaluation()
+            if balance:
+                output1 = balance.get("output1", {})
+                new_cash = float(output1.get("dnca_tot_amt", 0))
+                
+                # 예수금 업데이트 (0원이 아닐 때만, 또는 초기화 시)
+                if new_cash > 0 or self.current_cash == 0:
+                    self.current_cash = new_cash
+                
+                # 보유 종목 평가액 계산 (빠른 버전: 로컬 holdings 사용)
+                holdings_value = 0
+                for code, holding in self.holdings.items():
+                    # output2에서 보유 종목 정보 확인 (더 빠름)
+                    output2 = balance.get("output2", [])
+                    for item in output2:
+                        if item.get("pdno", "").strip() == code:
+                            # API에서 받은 평가액 사용
+                            evlu_amt = float(item.get("evlu_amt", 0))  # 평가금액
+                            holdings_value += evlu_amt
+                            break
+                    else:
+                        # output2에 없으면 로컬 계산 (fallback)
+                        price_data = self.client.inquire_price(code)
+                        if price_data:
+                            current_price = abs(float(price_data.get("stck_prpr", 0)))
+                            holdings_value += current_price * holding["total_qty"]
+                
+                # 총자산 계산 (손익 반영)
+                self.current_total_asset = self.current_cash + holdings_value
+                if profit_val != 0:
+                    self.current_total_asset += profit_val
+                
+                logger.debug(f"💵 [경량갱신] 예수금: {self.current_cash:,.0f}원 | 총자산: {self.current_total_asset:,.0f}원")
+                return True
+        except Exception as e:
+            logger.error(f"❌ 경량 갱신 실패: {e}")
+        return False
+    
+    def _update_cash_only(self):
+        """예수금만 빠르게 업데이트 (하위 호환성용, _update_account_light 사용 권장)"""
+        return self._update_account_light(profit_val=0)
+    
+    def _seconds_until_next_5min(self):
+        """다음 5분 정각까지 남은 초 계산"""
+        now = dt.now()
+        next_min = ((now.minute // 5) + 1) * 5
+        if next_min >= 60:
+            next_time = now.replace(hour=now.hour + 1, minute=0, second=0, microsecond=0)
+        else:
+            next_time = now.replace(minute=next_min, second=0, microsecond=0)
+        return (next_time - now).total_seconds()
+    
+    async def _report_scheduler(self):
+        """리포트 전송 스케줄러 (비동기 백그라운드)"""
+        while True:
+            try:
+                await asyncio.sleep(60)  # 1분마다 체크
+                now = dt.now()
+                
+                # 13:00 - 오전 리포트 + AI 리포트
+                if now.hour == 13 and now.minute == 0 and not self.morning_report_sent:
+                    loop = asyncio.get_event_loop()
+                    await loop.run_in_executor(None, self.send_morning_report)
+                    await loop.run_in_executor(None, self.send_ai_report)
+                
+                # 15:15 - 장마감 전 리포트
+                elif now.hour == 15 and now.minute == 15 and not self.closing_report_sent:
+                    loop = asyncio.get_event_loop()
+                    await loop.run_in_executor(None, self.send_closing_report)
+                
+                # 15:35 - 최종 리포트
+                elif now.hour == 15 and now.minute == 35 and not self.final_report_sent:
+                    loop = asyncio.get_event_loop()
+                    await loop.run_in_executor(None, self.send_final_report)
+                
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.error(f"❌ [리포트 스케줄러] 에러: {e}")
+                await asyncio.sleep(60)
+    
+    async def _asset_update_scheduler(self):
+        """자산 정보 업데이트 스케줄러 (30분마다, 비동기 백그라운드)"""
+        while True:
+            try:
+                await asyncio.sleep(60)  # 1분마다 체크
+                now = dt.now()
+                
+                # 30분마다 자산 업데이트
+                if now.minute % 30 == 0:
+                    loop = asyncio.get_event_loop()
+                    await loop.run_in_executor(None, self._update_assets)
+                    await asyncio.sleep(60)  # 업데이트 후 1분 대기 (중복 방지)
+                
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.error(f"❌ [자산 업데이트 스케줄러] 에러: {e}")
+                await asyncio.sleep(60)
+    
+    def send_mm(self, msg):
+        """Mattermost 알림 전송"""
+        try:
+            self.mm.send(self.mm_channel, msg)
+        except Exception as e:
+            logger.error(f"❌ MM 전송 에러: {e}")
+    
+    def check_market_status(self):
+        """장 운영 시간 체크"""
+        # FORCE_MARKET_OPEN 플래그 확인 (테스트용)
+        force_open = get_env_bool("FORCE_MARKET_OPEN", False)
+        if force_open:
+            logger.debug("🔓 FORCE_MARKET_OPEN=true - 장 상태 무시하고 계속 진행")
+            return True
+        
+        # 정상 장 운영 시간 체크
+        now = dt.now()
+        if not (datetime.time(8, 30) <= now.time() <= datetime.time(16, 0)):
+            return False
+        if now.weekday() >= 5:  # 주말
+            return False
+        return True
+    
+    def send_morning_report(self):
+        """오전 장 뜸할 때 리포트 (13:00)"""
+        if self.morning_report_sent:
+            return
+        
+        self._update_assets()
+        day_pnl = self.current_total_asset - self.start_day_asset
+        day_pnl_pct = (day_pnl / self.start_day_asset * 100) if self.start_day_asset > 0 else 0
+        
+        msg = f"""📊 **[오전 장 현황 - 13:00]**
+- 당일 시작: {self.start_day_asset:,.0f}원
+- 현재 자산: {self.current_total_asset:,.0f}원
+- 당일 손익: {day_pnl:+,.0f}원 ({day_pnl_pct:+.2f}%)
+- 보유 종목: {len(self.holdings)}개"""
+        
+        self.send_mm(msg)
+        self.morning_report_sent = True
+        logger.info("📊 오전 리포트 전송 완료")
+    
+    def send_closing_report(self):
+        """장마감 전 리포트 (15:15)"""
+        if self.closing_report_sent:
+            return
+        
+        self._update_assets()
+        day_pnl = self.current_total_asset - self.start_day_asset
+        day_pnl_pct = (day_pnl / self.start_day_asset * 100) if self.start_day_asset > 0 else 0
+        
+        msg = f"""📈 **[장마감 전 현황 - 15:15]**
+- 당일 손익: {day_pnl:+,.0f}원 ({day_pnl_pct:+.2f}%)
+- 현재 자산: {self.current_total_asset:,.0f}원
+- 보유 종목: {len(self.holdings)}개
+- 예수금: {self.current_cash:,.0f}원"""
+        
+        self.send_mm(msg)
+        self.closing_report_sent = True
+        logger.info("📈 장마감 전 리포트 전송 완료")
+    
+    def send_final_report(self):
+        """장마감 후 최종 리포트 (15:35)"""
+        if self.final_report_sent:
+            return
+        
+        self._update_assets()
+        
+        # 당일 손익
+        day_pnl = self.current_total_asset - self.start_day_asset
+        day_pnl_pct = (day_pnl / self.start_day_asset * 100) if self.start_day_asset > 0 else 0
+        
+        # 누적 손익
+        cumulative_pnl = self.current_total_asset - self.total_deposit
+        cumulative_pnl_pct = (cumulative_pnl / self.total_deposit * 100) if self.total_deposit > 0 else 0
+        
+        # 오늘 거래 내역
+        today_trades = self.db.get_trades_by_date(self.today_date)
+        
+        msg = f"""🏁 **[장마감 최종 보고 - 15:35]**
+━━━━━━━━━━━━━━━━━━━━
+📅 **당일 손익**
+- 시작: {self.start_day_asset:,.0f}원
+- 종료: {self.current_total_asset:,.0f}원
+- 손익: {day_pnl:+,.0f}원 ({day_pnl_pct:+.2f}%)
+
+💰 **누적 손익 (총 입금액 대비)**
+- 총 입금: {self.total_deposit:,.0f}원
+- 현재 자산: {self.current_total_asset:,.0f}원
+- 누적 손익: {cumulative_pnl:+,.0f}원 ({cumulative_pnl_pct:+.2f}%)
+
+📊 **거래 현황**
+- 오늘 매매: {len(today_trades)}건
+- 보유 종목: {len(self.holdings)}개
+- 예수금: {self.current_cash:,.0f}원
+━━━━━━━━━━━━━━━━━━━━"""
+        
+        self.send_mm(msg)
+        self.final_report_sent = True
+        logger.info("🏁 장마감 최종 리포트 전송 완료")
+    
+    def send_ai_report(self):
+        """AI 분석 리포트 (13:00)"""
+        if self.ai_report_sent or not gemini_model:
+            return
+        
+        try:
+            # 최근 거래 내역 조회
+            recent_trades = []
+            try:
+                conn = self.db.conn
+                cursor = conn.execute("""
+                    SELECT code, name, buy_price, sell_price, qty, profit_rate, 
+                           realized_pnl, strategy, sell_reason, buy_date, sell_date, hold_minutes
+                    FROM trade_history
+                    WHERE strategy LIKE 'LONG%'
+                    ORDER BY id DESC
+                    LIMIT 10
+                """)
+                for row in cursor.fetchall():
+                    recent_trades.append({
+                        'code': row[0],
+                        'name': row[1],
+                        'buy_price': row[2],
+                        'sell_price': row[3],
+                        'qty': row[4],
+                        'profit_rate': row[5],
+                        'realized_pnl': row[6],
+                        'strategy': row[7],
+                        'sell_reason': row[8],
+                        'buy_date': row[9],
+                        'sell_date': row[10],
+                        'hold_minutes': row[11] or 0
+                    })
+            except Exception as e:
+                logger.error(f"거래 내역 조회 실패: {e}")
+                return
+            
+            if not recent_trades:
+                return
+            
+            # 통계 계산
+            total = len(recent_trades)
+            wins = sum(1 for t in recent_trades if t['profit_rate'] > 0)
+            losses = total - wins
+            win_rate = wins / total * 100 if total > 0 else 0
+            avg_profit = sum(t['profit_rate'] for t in recent_trades) / total
+            total_pnl = sum(t['realized_pnl'] for t in recent_trades)
+            avg_hold_days = sum(t['hold_minutes'] for t in recent_trades) / total / 1440  # 분을 일로 변환
+            
+            # AI 분석
+            trades_text = ""
+            for i, t in enumerate(recent_trades, 1):
+                trades_text += f"""
+[거래 {i}] {t['name']} ({t['strategy']})
+- 매수: {t['buy_price']:,.0f}원 × {t['qty']}주
+- 매도: {t['sell_price']:,.0f}원
+- 손익: {t['profit_rate']:+.2f}% ({t['realized_pnl']:,.0f}원)
+- 보유: {avg_hold_days:.1f}일
+- 사유: {t['sell_reason']}
+"""
+            
+            prompt = f"""당신은 퀀트 트레이딩 전문가입니다.
+
+다음은 최근 {total}건의 장기/늘림목 거래 내역입니다:
+
+{trades_text}
+
+📊 통계:
+- 승률: {win_rate:.1f}% ({wins}승 {losses}패)
+- 평균 수익률: {avg_profit:.2f}%
+- 총 손익: {total_pnl:,.0f}원
+- 평균 보유: {avg_hold_days:.1f}일
+
+**당신의 임무:**
+1. 문제점 3가지 진단 (구체적으로)
+2. DB 설정 수정 권장사항 (변수명=값 형식)
+3. 예상 효과
+
+**출력 형식:**
+## 🔍 문제점
+1. [구체적 문제 1]
+2. [구체적 문제 2]
+3. [구체적 문제 3]
+
+## 💡 권장 수정사항
+```
+MAX_PER=XX
+MAX_PEG=X.XX
+DCA_INTERVALS=X,-X.XX,-X.XX
+...
+```
+
+## 📈 예상 효과
+- [효과 1]
+- [효과 2]
+
+**간결하고 명확하게 답변하세요.**
+"""
+            
+            response = gemini_model.generate_content(prompt)
+            analysis = response.text
+            
+            summary = f"""📊 최근 {total}건 거래 통계
+- 승률: {win_rate:.1f}% ({wins}승 {losses}패)
+- 평균 수익률: {avg_profit:.2f}%
+- 총 손익: {total_pnl:,.0f}원
+- 평균 보유: {avg_hold_days:.1f}일"""
+            
+            message = f"""🤖 **[13시 AI 자동 분석]**
+
+{summary}
+
+{analysis}
+
+---
+💬 늘림목 전략 최적화를 위한 AI 분석입니다.
+"""
+            
+            self.send_mm(message)
+            self.ai_report_sent = True
+            logger.info("🤖 AI 리포트 전송 완료")
+            
+        except Exception as e:
+            logger.error(f"AI 리포트 생성 실패: {e}")
+
+    def analyze_stock_value(self, code, name):
+        """종목 밸류에이션 분석 - 고도화된 분석"""
+        try:
+            # 현재가 조회
+            price_data = self.client.inquire_price(code)
+            if not price_data:
+                return None
+            
+            current_price = abs(float(price_data.get("stck_prpr", 0)))
+            if current_price == 0:
+                return None
+            
+            # PER/PEG 조회
+            fund_data = get_kis_per_eps_peg(self.client, code, current_price)
+            per = fund_data.get("per")
+            peg = fund_data.get("peg")
+            growth_pct = fund_data.get("growth_pct")
+            
+            # 차트 분석
+            df = get_kis_daily_chart(self.client, code, max_days=65)
+            if df.empty:
+                return None
+            
+            # RSI 계산
+            delta = df["close"].diff(1)
+            gain = delta.where(delta > 0, 0).rolling(window=14).mean()
+            loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
+            rs = gain / loss.replace(0, float("nan"))
+            rsi = 100 - (100 / (1 + rs))
+            current_rsi = float(rsi.iloc[-1]) if len(rsi) > 0 else None
+            
+            # [필터 1] RSI 과열 체크
+            rsi_threshold = get_env_float("RSI_OVERHEAT_THRESHOLD", 78.0)
+            if current_rsi and current_rsi >= rsi_threshold:
+                logger.info(f"🔍 [Pass-RSI] {name} {code}: RSI 과열 ({current_rsi:.1f} >= {rsi_threshold})")
+                return None
+            
+            # 변동성
+            volatility = calculate_volatility(df)
+            
+            # 이동평균
+            ma20 = float(df["MA20"].iloc[-1]) if "MA20" in df.columns and len(df) >= 20 else None
+            ma60 = float(df["MA60"].iloc[-1]) if "MA60" in df.columns and len(df) >= 60 else None
+            
+            # [필터 2] MA20 체크
+            if ma20 and current_price < ma20:
+                logger.info(f"🔍 [Pass-MA20] {name} {code}: 현재가({current_price:.0f}) < MA20({ma20:.2f})")
+                return None
+            
+            # 외국인/기관 동향 분석
+            investor_trend = self.client.get_investor_trend(code, days=5)
+            investor_score = 0
+            investor_signal = "중립"
+            if investor_trend:
+                total_net = investor_trend.get("total_net_buy", 0)
+                if total_net > 20000:
+                    investor_score = 25
+                    investor_signal = "강한 매수세"
+                elif total_net > 5000:
+                    investor_score = 15
+                    investor_signal = "매수세"
+                elif total_net < -20000:
+                    investor_score = -25
+                    investor_signal = "강한 매도세"
+                elif total_net < -5000:
+                    investor_score = -15
+                    investor_signal = "매도세"
+            
+            # 종합 점수 계산
+            score = 50  # 기본 점수
+            
+            # PER 점수
+            if per is not None:
+                if per < 10:
+                    score += 30
+                elif per < 15:
+                    score += 20
+                elif per < 20:
+                    score += 10
+                elif per > 30:
+                    score -= 20
+            
+            # PEG 점수
+            if peg is not None:
+                if peg < 1.0:
+                    score += 30
+                elif peg < 1.5:
+                    score += 15
+                elif peg > 2.0:
+                    score -= 20
+            
+            # RSI 점수
+            if current_rsi is not None:
+                if current_rsi < 30:
+                    score += 20  # 과매도 구간
+                elif current_rsi < 40:
+                    score += 10
+                elif current_rsi > 70:
+                    score -= 20  # 과매수 구간
+            
+            # 이동평균 점수
+            if ma20 is not None and ma60 is not None:
+                if ma20 > ma60:
+                    score += 10  # 정배열
+                    ma_gap_pct = ((ma20 - ma60) / ma60) * 100
+                    if ma_gap_pct > 5:
+                        score += 5  # 강한 상승세
+            
+            # 외국인/기관 점수 추가
+            score += investor_score
+            
+            return {
+                "code": code,
+                "name": name,
+                "current_price": current_price,
+                "per": per,
+                "peg": peg,
+                "growth_pct": growth_pct,
+                "rsi": current_rsi,
+                "volatility": volatility,
+                "ma20": ma20,
+                "ma60": ma60,
+                "investor_trend": investor_trend,
+                "investor_signal": investor_signal,
+                "score": score,
+                "is_buyable": (
+                    (per is None or per <= self.max_per) and
+                    (peg is None or peg <= self.max_peg) and
+                    (growth_pct is None or growth_pct >= self.min_growth_pct) and
+                    score >= 60 and
+                    investor_score >= -10  # 강한 매도세는 제외
+                ),
+            }
+            
+            # 필터링 로그 출력
+            if not analysis["is_buyable"]:
+                reasons = []
+                if per and per > self.max_per:
+                    reasons.append(f"PER {per:.1f} > {self.max_per}")
+                if peg and peg > self.max_peg:
+                    reasons.append(f"PEG {peg:.2f} > {self.max_peg}")
+                if growth_pct and growth_pct < self.min_growth_pct:
+                    reasons.append(f"성장률 {growth_pct:.1f}% < {self.min_growth_pct}%")
+                if score < 60:
+                    reasons.append(f"점수 {score:.1f} < 60")
+                if investor_score < -10:
+                    reasons.append(f"수급 점수 {investor_score} < -10")
+                
+                if reasons:
+                    logger.info(f"🔍 [Pass-밸류] {name} {code}: {', '.join(reasons)}")
+            
+            return {
+            }
+        except Exception as e:
+            logger.error(f"종목 분석 실패({code}): {e}")
+            return None
+
+    def check_dca_opportunity(self, code, holding):
+        """늘림목(분할 매수) 기회 체크"""
+        if code not in self.holdings:
+            return None
+        
+        try:
+            price_data = self.client.inquire_price(code)
+            if not price_data:
+                return None
+            
+            current_price = abs(float(price_data.get("stck_prpr", 0)))
+            avg_price = holding["avg_price"]
+            
+            # 평단가 대비 하락률 계산
+            drop_pct = (current_price - avg_price) / avg_price
+            
+            # 분할 매수 구간 확인
+            for i, interval in enumerate(self.dca_intervals):
+                if drop_pct <= interval:
+                    # 이미 이 구간에서 매수했는지 확인
+                    buy_prices = holding.get("buy_prices", [])
+                    if buy_prices and min(buy_prices) <= current_price * 1.02:  # 2% 오차 범위 내
+                        continue  # 이미 매수한 구간
+                    
+                    # 분할 매수 실행
+                    amount = self.dca_amounts[i] if i < len(self.dca_amounts) else self.dca_amounts[-1]
+                    qty = int(amount / current_price)
+                    if qty > 0:
+                        return {
+                            "code": code,
+                            "name": holding.get("name", code),
+                            "price": current_price,
+                            "qty": qty,
+                            "drop_pct": drop_pct,
+                            "interval": interval,
+                        }
+            
+            return None
+        except Exception as e:
+            logger.error(f"늘림목 체크 실패({code}): {e}")
+            return None
+
+    def check_sell_signals(self):
+        """매도 신호 체크 (손절/익절)"""
+        if not self.holdings:
+            return []
+        
+        sell_signals = []
+        for code, holding in list(self.holdings.items()):
+            try:
+                price_data = self.client.inquire_price(code)
+                if not price_data:
+                    continue
+                
+                current_price = abs(float(price_data.get("stck_prpr", 0)))
+                avg_price = holding["avg_price"]
+                profit_pct = (current_price - avg_price) / avg_price
+                
+                # 손절 또는 익절 체크
+                if profit_pct <= self.stop_loss_pct:
+                    sell_signals.append({
+                        "code": code,
+                        "name": holding.get("name", code),
+                        "reason": "손절",
+                        "profit_pct": profit_pct,
+                        "qty": holding["total_qty"],
+                    })
+                elif profit_pct >= self.take_profit_pct:
+                    sell_signals.append({
+                        "code": code,
+                        "name": holding.get("name", code),
+                        "reason": "익절",
+                        "profit_pct": profit_pct,
+                        "qty": holding["total_qty"],
+                    })
+                
+                time.sleep(random.uniform(0.3, 0.7))
+            except Exception as e:
+                logger.error(f"매도 신호 체크 실패({code}): {e}")
+                continue
+        
+        return sell_signals
+
+    def execute_buy(self, signal, is_dca=False):
+        """매수 실행"""
+        code = signal["code"]
+        name = signal["name"]
+        price = signal["price"]
+        qty = signal["qty"]
+        
+        # 🔥 매수 직전 예수금 실시간 확인 (30분마다 업데이트된 값이 부정확할 수 있음)
+        if not self._update_account_light(profit_val=0):
+            logger.warning(f"⚠️ [{name}] 예수금 조회 실패 -> 매수 스킵")
+            return False
+        
+        # 예수금 부족 체크 (수수료 포함 여유분 5% 고려)
+        required_amount = price * qty * 1.05  # 수수료 포함
+        if self.current_cash < required_amount:
+            logger.warning(
+                f"⚠️ [{name}] 예수금 부족: 필요 {required_amount:,.0f}원 / "
+                f"보유 {self.current_cash:,.0f}원 -> 매수 스킵"
+            )
+            return False
+        
+        # 매수 주문
+        success = self.client.buy_market_order(code, qty)
+        if success:
+            # 매수 후 예수금 + 총자산 즉시 업데이트 (다음 매수 시 정확한 예수금 확인)
+            self._update_account_light(profit_val=0)
+            buy_time = dt.now().strftime("%Y-%m-%d %H:%M:%S")
+            
+            if code not in self.holdings:
+                self.holdings[code] = {
+                    "buy_prices": [],
+                    "qtys": [],
+                    "total_qty": 0,
+                    "avg_price": 0,
+                    "first_buy_date": buy_time,
+                    "name": name,
+                }
+            
+            holding = self.holdings[code]
+            holding["buy_prices"].append(price)
+            holding["qtys"].append(qty)
+            holding["total_qty"] += qty
+            
+            # 평단가 재계산
+            total_cost = sum(p * q for p, q in zip(holding["buy_prices"], holding["qtys"]))
+            holding["avg_price"] = total_cost / holding["total_qty"]
+            
+            # DB에 저장/업데이트
+            self.db.upsert_trade({
+                "code": code,
+                "name": name,
+                "strategy": "LONG_DCA" if is_dca else "LONG_INITIAL",
+                "avg_buy_price": holding["avg_price"],
+                "current_price": price,
+                "target_qty": holding["total_qty"],
+                "current_qty": holding["total_qty"],
+                "status": "HOLDING",
+                "buy_date": holding["first_buy_date"],
+            })
+            
+            action = "늘림목 매수" if is_dca else "초기 매수"
+            logger.info(f"💰 [{action}] {name} ({code}): {price:,.0f}원 × {qty}주 (평단: {holding['avg_price']:,.0f}원)")
+            return True
+        
+        return False
+
+    def execute_sell(self, signal):
+        """매도 실행"""
+        code = signal["code"]
+        name = signal["name"]
+        qty = signal["qty"]
+        
+        if code not in self.holdings:
+            logger.warning(f"⚠️ [{name}] 보유 종목 아님")
+            return False
+        
+        # 매도 주문
+        success = self.client.sell_market_order(code, qty)
+        if success:
+            # 현재가 조회
+            price_data = self.client.inquire_price(code)
+            sell_price = abs(float(price_data.get("stck_prpr", 0))) if price_data else signal.get("price", 0)
+            
+            holding = self.holdings[code]
+            profit_pct = signal["profit_pct"]
+            
+            # DB에서 매도 처리
+            self.db.close_trade(
+                code=code,
+                sell_price=sell_price,
+                sell_reason=signal['reason'],
+            )
+            
+            # 손익 계산 (매도 후 총자산 반영용)
+            profit_val = (sell_price - holding["avg_price"]) * qty  # 손익 금액
+            
+            del self.holdings[code]
+            
+            # 🔥 매도 후 예수금 + 총자산 즉시 업데이트 (손익 반영)
+            self._update_account_light(profit_val=profit_val)
+            
+            logger.info(
+                f"💸 [매도 체결] {name} ({code}): {qty}주 "
+                f"({signal['reason']}, {profit_pct*100:+.2f}%, 평단: {holding['avg_price']:,.0f}원)"
+            )
+            return True
+        
+        return False
+
+    def run(self):
+        """메인 루프 (진입점). 내부적으로 asyncio.run(_run_async()) 호출."""
+        asyncio.run(self._run_async())
+    
+    async def _run_async(self):
+        """비동기 메인 루프 - 백그라운드 태스크 시작 후 동기 매매 루프 실행"""
+        logger.info("🚀 늘림목 트레이딩 봇 시작 (비동기 백그라운드 작업 활성화)")
+        
+        # 백그라운드 태스크 시작
+        self._report_task = asyncio.create_task(self._report_scheduler())
+        self._asset_task = asyncio.create_task(self._asset_update_scheduler())
+        logger.info("✅ 백그라운드 태스크 시작 완료 (리포트, 자산 업데이트)")
+        
+        # 동기 매매 루프는 별도 스레드에서 실행 (메인 이벤트 루프 블로킹 방지)
+        loop = asyncio.get_event_loop()
+        await loop.run_in_executor(None, self._sync_trading_loop)
+    
+    def _sync_trading_loop(self):
+        """동기 매매 루프 (메인 로직) - 백그라운드 작업과 분리"""
+        logger.info("📈 매매 루프 시작 (동기 모드)")
+        
+        while True:
+            try:
+                now = dt.now()
+                current_date = now.strftime("%Y-%m-%d")
+                
+                # 날짜 변경 시 리포트 플래그 리셋
+                if current_date != self.today_date:
+                    self.today_date = current_date
+                    self.morning_report_sent = False
+                    self.closing_report_sent = False
+                    self.final_report_sent = False
+                    self.ai_report_sent = False
+                    self.start_day_asset = 0
+                    logger.info(f"📅 날짜 변경: {current_date}")
+                
+                # 리포트 전송은 백그라운드 태스크에서 처리하므로 여기서는 제거
+                # (기존 코드와의 호환성을 위해 주석 처리)
+                # if now.hour == 13 and now.minute == 0:
+                #     self.send_morning_report()
+                #     self.send_ai_report()
+                # elif now.hour == 15 and now.minute == 15:
+                #     self.send_closing_report()
+                # elif now.hour == 15 and now.minute == 35:
+                #     self.send_final_report()
+                
+                # 장 상태 체크
+                if not self.check_market_status():
+                    logger.info("⏸ 장 시간 아님 - 대기 중...")
+                    time.sleep(60)
+                    continue
+                
+                # 자산 정보 업데이트는 백그라운드 태스크에서 처리하므로 여기서는 제거
+                # (기존 코드와의 호환성을 위해 주석 처리)
+                # if now.minute % 30 == 0:  # 30분마다
+                #     self._update_assets()
+                
+                # 매도 신호 체크 (우선) - 메인 루프에서 처리
+                sell_signals = self.check_sell_signals()
+                for signal in sell_signals:
+                    self.execute_sell(signal)
+                    time.sleep(random.uniform(1, 2))
+                
+                # 늘림목 기회 체크
+                for code, holding in list(self.holdings.items()):
+                    dca_signal = self.check_dca_opportunity(code, holding)
+                    if dca_signal:
+                        self.execute_buy(dca_signal, is_dca=True)
+                        time.sleep(random.uniform(1, 2))
+                
+                # 신규 매수 기회 스캔 (관심 종목 리스트 기준)
+                active_count = len(self.holdings)
+                if len(self.watchlist) > 0:
+                    logger.info(f"🔍 [매수 기회 탐색] 타겟:{len(self.watchlist)}개 | 보유:{active_count}/{self.max_stocks}")
+                
+                for item in self.watchlist:
+                    code = item.get("code", "").strip()
+                    name = item.get("name", code)
+                    
+                    if not code or code in self.holdings:
+                        continue
+                    
+                    # 밸류에이션 분석
+                    analysis = self.analyze_stock_value(code, name)
+                    if not analysis or not analysis["is_buyable"]:
+                        continue
+                    
+                    # 초기 매수 실행
+                    signal = {
+                        "code": code,
+                        "name": name,
+                        "price": analysis["current_price"],
+                        "qty": int(100000 / analysis["current_price"]),  # 10만원 분할
+                    }
+                    self.execute_buy(signal, is_dca=False)
+                    time.sleep(random.uniform(2, 4))
+                    break  # 한 번에 하나씩만
+                
+                # 대기
+                time.sleep(random.uniform(10, 15))
+                
+            except KeyboardInterrupt:
+                logger.info("⏹ 봇 종료")
+                # 백그라운드 태스크 취소
+                if self._report_task:
+                    self._report_task.cancel()
+                if self._asset_task:
+                    self._asset_task.cancel()
+                break
+            except Exception as e:
+                logger.error(f"❌ 루프 에러: {e}")
+                import traceback
+                logger.error(traceback.format_exc())
+                time.sleep(10)
+
+
+if __name__ == "__main__":
+    bot = LongTradingBot()
+    bot.run()
diff --git a/kis_short_ver1.py b/kis_short_ver1.py
new file mode 100644
index 0000000..e0bab0a
--- /dev/null
+++ b/kis_short_ver1.py
@@ -0,0 +1,3296 @@
+"""
+KIS Short Trading Bot Ver1 - 단타용 한투 API 트레이딩 시스템
+- 한국투자증권(KIS) Open API 사용
+- 개미털기(눌림목) 전략 기반 단타 매매
+- 빠른 손절/익절 로직
+- kiwoom_trader_ver2.py의 단타 전략을 한투 API로 변환
+"""
+
+import os
+import re
+import json
+import time
+import random
+import logging
+import datetime
+import hashlib
+import hmac
+import base64
+import warnings
+import asyncio
+from datetime import datetime as dt
+from pathlib import Path
+from typing import List, Dict, Optional
+
+import pandas as pd
+import requests
+
+from database import TradeDB
+
+# 로깅 설정
+logging.basicConfig(
+    format='[%(asctime)s] %(message)s',
+    datefmt='%H:%M:%S',
+    level=logging.INFO,
+)
+logger = logging.getLogger("KISShortBot")
+
+# 로그 색상 (ANSI) - 탈락/통과 구분
+LOG_RED = "\033[91m"     # 탈락
+LOG_YELLOW = "\033[93m"  # 탈락 (Pass-조건)
+LOG_GREEN = "\033[92m"   # 통과
+LOG_CYAN = "\033[96m"    # 강조
+LOG_RESET = "\033[0m"
+
+# DB 초기화
+SCRIPT_DIR = Path(__file__).resolve().parent
+db = TradeDB(db_path=str(SCRIPT_DIR / "quant_bot.db"))
+
+# DB에서 환경변수 로드
+def get_env_from_db(key, default=""):
+    """DB에서 환경변수 읽기"""
+    env_data = db.get_latest_env()
+    if env_data and env_data.get("snapshot"):
+        return env_data["snapshot"].get(key, default)
+    return default
+
+def get_env_float(key, default):
+    """환경변수를 float로 변환 (DB 우선)"""
+    value = get_env_from_db(key, str(default))
+    if isinstance(value, str) and "#" in value:
+        value = value.split("#")[0].strip()
+    try:
+        return float(value) if value else default
+    except (ValueError, TypeError):
+        return default
+
+def get_env_int(key, default):
+    """환경변수를 int로 변환 (DB 우선)"""
+    value = get_env_from_db(key, str(default))
+    if isinstance(value, str) and "#" in value:
+        value = value.split("#")[0].strip()
+    try:
+        return int(value) if value else default
+    except (ValueError, TypeError):
+        return default
+
+def get_env_bool(key, default=False):
+    """환경변수를 bool로 변환 (DB 우선)"""
+    value = get_env_from_db(key, str(default)).lower()
+    return value in ("true", "1", "yes")
+
+# Mattermost 설정
+MM_SERVER_URL = get_env_from_db("MM_SERVER_URL", "https://mattermost.hoonfam.org")
+MM_BOT_TOKEN = get_env_from_db("MM_BOT_TOKEN_", "").strip()
+MM_CONFIG_FILE = SCRIPT_DIR / "mm_config.json"
+# 기본 채널(alias) + 단타 봇 전용 채널(alias)
+MM_CHANNEL_DEFAULT = get_env_from_db("MATTERMOST_CHANNEL", "stock")
+MM_CHANNEL_SHORT = get_env_from_db("KIS_SHORT_MM_CHANNEL", MM_CHANNEL_DEFAULT)
+
+# Gemini API (AI 리포트용) - google.genai 신규 SDK (Client 사용, configure 없음)
+try:
+    import google.genai as genai
+    GEMINI_AVAILABLE = True
+except ImportError:
+    GEMINI_AVAILABLE = False
+    logger.warning("⚠️ google-genai 미설치 - AI 리포트 기능 사용 불가")
+
+GEMINI_API_KEY = get_env_from_db("GEMINI_API_KEY", "").strip()
+GEMINI_MODEL_ID = "gemini-2.5-flash"  # 또는 gemini-2.5-flash (모델명 확인)
+gemini_client = None
+if GEMINI_API_KEY and GEMINI_AVAILABLE:
+    try:
+        gemini_client = genai.Client(api_key=GEMINI_API_KEY)
+    except Exception as e:
+        logger.warning(f"⚠️ Gemini 초기화 실패: {e}")
+        gemini_client = None
+else:
+    gemini_client = None
+
+# ML 예측 (선택적)
+try:
+    from ml_predictor import MLPredictor
+    ML_AVAILABLE = True
+except ImportError:
+    ML_AVAILABLE = False
+    logger.warning("⚠️ ml_predictor 미설치 - ML 예측 기능 사용 불가")
+
+# RiskManager (변동성 기반 리스크 관리)
+try:
+    from risk_manager import RiskManager
+    RISK_MANAGER_AVAILABLE = True
+except ImportError:
+    RISK_MANAGER_AVAILABLE = False
+    logger.warning("⚠️ risk_manager 미설치 - 변동성 역가중 매수 금액 계산 불가")
+
+# ============================================================
+# 한투(KIS) API 클라이언트 (kis_long_term_checker.py 참고)
+# ============================================================
+# 모의계좌용 토큰 캐시 경로
+KIS_TOKEN_CACHE_PATH_MOCK = SCRIPT_DIR / ".kis_token_cache_mock.json"
+# 실계좌용 토큰 캐시 경로
+KIS_TOKEN_CACHE_PATH_REAL = SCRIPT_DIR / ".kis_token_cache_real.json"
+
+
+
+# 한투 접근 토큰 유효기간 24시간. 자주 발급하면 영구 제명될 수 있으므로 캐시 철저 재사용.
+# 만료 1분 전에만 재발급 (불필요한 발급 최소화)
+KIS_TOKEN_EXPIRE_MARGIN_SEC = 60
+
+
+def _parse_kis_token_expired(expired_str):
+    """한투 API 만료시간 문자열 파싱. 'YYYY-MM-DD HH:MM:SS' 또는 'YYYY-MM-DDTHH:MM:SS' 등 지원."""
+    if not expired_str or not isinstance(expired_str, str):
+        return None
+    s = expired_str.strip().replace("T", " ")[:19]
+    if len(s) < 19:
+        return None
+    try:
+        return dt.strptime(s, "%Y-%m-%d %H:%M:%S")
+    except ValueError:
+        return None
+
+
+def _load_kis_token_cache(mock):
+    """캐시 파일에서 토큰 로드. 만료 1분 전까지 유효하면 재사용 (24h 토큰 자주 발급 시 영구 제명 주의)."""
+    if mock:
+        path = KIS_TOKEN_CACHE_PATH_MOCK
+    else:
+        path = KIS_TOKEN_CACHE_PATH_REAL
+    if not path.exists():
+        logger.info("한투 토큰 캐시 없음 → API 발급 예정 (캐시 경로: %s)", path)
+        return None
+    try:
+        logger.info("패스 %s", path)
+        with open(path, "r", encoding="utf-8") as f:
+            cache = json.load(f)
+        if cache.get("mock") != mock:
+            logger.info("한투 토큰 캐시 모의/실전 불일치 → API 발급 예정")
+            return None
+        token = cache.get("access_token")
+        expired_str = cache.get("access_token_token_expired") or cache.get("expires_at")
+        if not token or not expired_str:
+            logger.info("한투 토큰 캐시 내용 불완전 → API 발급 예정")
+            return None
+        expired_dt = _parse_kis_token_expired(expired_str)
+        if expired_dt is None:
+            logger.info("한투 토큰 캐시 만료시간 파싱 실패(%s) → API 발급 예정", expired_str[:30])
+            return None
+        if dt.now() >= expired_dt - datetime.timedelta(seconds=KIS_TOKEN_EXPIRE_MARGIN_SEC):
+            logger.info("한투 토큰 캐시 만료 임박(%s) → API 발급 예정", expired_str[:19])
+            return None
+        return token
+    except Exception as e:
+        logger.warning("한투 토큰 캐시 로드 실패(%s): %s", path, e)
+        return None
+
+
+def _save_kis_token_cache(access_token, access_token_token_expired, mock):
+    """발급받은 토큰을 캐시 파일에 저장."""
+    try:
+        if mock:
+            path = KIS_TOKEN_CACHE_PATH_MOCK
+        else:
+            path = KIS_TOKEN_CACHE_PATH_REAL
+        with open(path, "w", encoding="utf-8") as f:
+            json.dump({
+                "access_token": access_token,
+                "access_token_token_expired": access_token_token_expired,
+                "mock": mock,
+            }, f, ensure_ascii=False, indent=2)
+        logger.info("한투 토큰 캐시 저장 완료: %s", path)
+    except Exception as e:
+        logger.warning("한투 토큰 캐시 저장 실패: %s", e)
+
+
+class KISClient:
+    """한국투자증권 Open API 클라이언트"""
+    def __init__(self, mock=None):
+
+        # 모의 여부 결정
+        if mock is not None:
+            use_mock = mock
+        else:
+            use_mock = get_env_bool("KIS_MOCK", True)
+
+        # 모의투자는 MOCK 전용 키만 사용(실전 키로 폴백 안 함 → 토큰/캐시가 실전이랑 섞이지 않도록)
+        if use_mock:
+            self.app_key = get_env_from_db("KIS_APP_KEY_MOCK", "").strip()
+            self.app_secret = get_env_from_db("KIS_APP_SECRET_MOCK", "").strip()
+            if not self.app_key or not self.app_secret:
+                logger.error("❌ 모의투자용 APP KEY/SECRET이 DB에 없습니다. KIS_APP_KEY_MOCK, KIS_APP_SECRET_MOCK 설정 필요.")
+                raise ValueError("모의투자 KIS_APP_KEY_MOCK / KIS_APP_SECRET_MOCK 미설정")
+        else:
+            self.app_key = (get_env_from_db("KIS_APP_KEY_REAL", "") or get_env_from_db("KIS_APP_KEY", "")).strip()
+            self.app_secret = (get_env_from_db("KIS_APP_SECRET_REAL", "") or get_env_from_db("KIS_APP_SECRET", "")).strip()
+
+        # 계좌번호: 모의/실전 분리
+        if use_mock:
+            raw_no   = get_env_from_db("KIS_ACCOUNT_NO_MOCK",   "").strip()
+            raw_code = get_env_from_db("KIS_ACCOUNT_CODE_MOCK", "").strip()
+            if not raw_code:
+                raw_code = "01"
+        else:
+            raw_no   = (get_env_from_db("KIS_ACCOUNT_NO_REAL",   "") or get_env_from_db("KIS_ACCOUNT_NO",   "")).strip()
+            raw_code = (get_env_from_db("KIS_ACCOUNT_CODE_REAL", "") or get_env_from_db("KIS_ACCOUNT_CODE", "01")).strip()
+            if not raw_code:
+                raw_code = "01"
+
+        # 10자리면 앞 8 / 뒤 2 분리
+        if len(raw_no) >= 10:
+            self.acc_no   = raw_no[:8]
+            self.acc_code = raw_no[8:10]
+        else:
+            self.acc_no   = raw_no
+            self.acc_code = raw_code[:2] if len(raw_code) >= 2 else "01"
+            if len(self.acc_no) != 8:
+                logger.warning("⚠️ 계좌번호 CANO 8자리 아님: '%s'(%s자리). DB 확인.", self.acc_no, len(self.acc_no))
+
+        if len(self.acc_no) != 8 or len(self.acc_code) != 2:
+            logger.error(
+                "❌ 계좌번호 형식 오류: CANO=%s(%s자리), ACNT_PRDT_CD=%s(%s자리) → OPSQ2000 발생. "
+                "모의면 KIS_ACCOUNT_NO_MOCK/KIS_ACCOUNT_CODE_MOCK, 실전이면 KIS_ACCOUNT_NO/KIS_ACCOUNT_CODE 확인.",
+                self.acc_no, len(self.acc_no), self.acc_code, len(self.acc_code)
+            )
+        else:
+            logger.info("✅ 한투 계좌 CANO=%s, ACNT_PRDT_CD=%s (모의=%s)", self.acc_no, self.acc_code, use_mock)
+
+        self.mock = use_mock
+
+        if self.mock is True:
+            self.base_url = "https://openapivts.koreainvestment.com:29443"
+        else:
+            self.base_url = "https://openapi.koreainvestment.com:9443"
+
+        self.access_token = None
+        logger.info("한투 API 연결: 모의=%s → %s", self.mock, self.base_url)
+        self._auth()
+
+
+    def _auth(self):
+        """접근 토큰 발급"""
+        if not self.app_key or not self.app_secret:
+            if self.mock:
+                key_hint = "KIS_APP_KEY_MOCK, KIS_APP_SECRET_MOCK"
+            else:
+                key_hint = "KIS_APP_KEY_REAL, KIS_APP_SECRET_REAL (또는 KIS_APP_KEY, KIS_APP_SECRET)"
+            logger.error("한투 API 키가 없습니다. DB env_config에 설정 필요: %s", key_hint)
+            raise ValueError("KIS 앱키/시크릿 설정 필요 (모의=%s)" % self.mock)
+
+        # ✅ path를 먼저 정의 (발급 성공/실패 양쪽에서 사용)
+        path = KIS_TOKEN_CACHE_PATH_MOCK if self.mock else KIS_TOKEN_CACHE_PATH_REAL
+        mode_str = "모의" if self.mock else "실전"
+
+        cached = _load_kis_token_cache(self.mock)
+        if cached:
+            self.access_token = cached
+            token_head = (cached[:8] + "…") if cached and len(cached) > 8 else "(없음)"
+            logger.info("한투 토큰 캐시 사용 (%s) | 파일=%s | 토큰앞8=%s", mode_str, path, token_head)
+            return
+
+        # 캐시 없음/만료 → API로 새 토큰 발급 (캐시 파일 없어도 자동 발급)
+        appkey_tail = (self.app_key[-4:] if len(self.app_key) >= 4 else self.app_key) or "????"
+        logger.info(
+            "한투 토큰 발급 요청 (%s) | 앱키 끝4자리=%s | 저장할 캐시=%s",
+            mode_str, appkey_tail, path,
+        )
+        url  = f"{self.base_url}/oauth2/tokenP"
+        body = {"grant_type": "client_credentials", "appkey": self.app_key, "appsecret": self.app_secret}
+        try:
+            r    = requests.post(url, json=body, timeout=10)
+            data = r.json()
+            if "access_token" in data:
+                self.access_token = data["access_token"]
+                expired = data.get("access_token_token_expired") or ""
+                _save_kis_token_cache(self.access_token, expired, self.mock)
+                token_head = (self.access_token[:8] + "…") if self.access_token and len(self.access_token) > 8 else "(없음)"
+                logger.info(
+                    "한투 토큰 발급 완료 (%s) | 캐시=%s | 앱키끝4=%s | 토큰앞8=%s",
+                    mode_str, path, appkey_tail, token_head,
+                )
+            else:
+                logger.error("한투 토큰 발급 실패: %s", data)
+                if isinstance(data, dict) and data.get("error_code") == "EGW00133":
+                    logger.warning("한투 1분당 1회 제한. 1분 후 재시도하거나 캐시 사용: %s", path)
+                raise RuntimeError("한투 토큰 발급 실패")
+        except Exception as e:
+            logger.error("한투 인증 예외: %s", e)
+            raise
+
+    def _get_hashkey(self, body):
+        """해시키(Hashkey) 발급 - POST 요청 시 body 무결성 검증용"""
+        try:
+            url = f"{self.base_url}/uapi/hashkey"
+            headers = {
+                "content-type": "application/json",
+                "appkey": self.app_key,
+                "appsecret": self.app_secret,
+            }
+            r = requests.post(url, headers=headers, json=body, timeout=5)
+            if r.status_code == 200:
+                data = r.json()
+                if data.get("rt_cd") == "0":
+                    return data.get("HASH")
+            return None
+        except Exception as e:
+            logger.debug(f"해시키 발급 실패: {e}")
+            return None
+
+    def _headers(self, tr_id, hashkey=None):
+        """API 호출용 헤더 생성"""
+        headers = {
+            "content-type": "application/json; charset=utf-8",
+            "authorization": f"Bearer {self.access_token}",
+            "appkey": self.app_key,
+            "appsecret": self.app_secret,
+            "tr_id": tr_id,
+        }
+        if hashkey:
+            headers["hashkey"] = hashkey
+        return headers
+
+    def _get(self, path, tr_id, params, max_retries=3, tr_cont=None):
+        """
+        GET 요청. EGW00201(초당 거래건수 초과) 시 점진적 대기 시간 증가 재시도
+        - 한투 API 제한: 초당 20개 (실제로는 더 엄격, 모의투자는 초당 2~3회 권장)
+        - EGW00201 감지 시: 5초 + (attempt * 1초) 대기 후 재시도
+        - 기본 호출 간격: 0.5초 이상 권장
+        """
+        url = f"{self.base_url}{path}"
+        headers = self._headers(tr_id)
+        if tr_cont:
+            headers["tr_cont"] = tr_cont  # 연속 조회 시 다음 페이지 요청 (한투: Response Header tr_cont=M 이면 Request Header tr_cont=N)
+        logger.debug(f"[API호출] GET {path} TR_ID={tr_id} params={params} tr_cont={tr_cont}")
+        
+        time.sleep(0.5)
+        
+        for attempt in range(max_retries):
+            try:
+                r = requests.get(url, headers=headers, params=params, timeout=15)
+                
+                # HTTP 429 (Too Many Requests)
+                if r.status_code == 429:
+                    wait_time = 1 + (attempt * 1)  # 5초, 6초, 7초...
+                    logger.warning(
+                        f"⏳ API 호출 제한 (429) -> {wait_time}초 대기 후 재시도 "
+                        f"({attempt+1}/{max_retries}) path={path}"
+                    )
+                    time.sleep(wait_time)
+                    continue
+                
+                if r.status_code == 200:
+                    j = r.json()
+                    if j.get("rt_cd") == "0":
+                        logger.debug(f"[API성공] GET {path} TR_ID={tr_id} status=200 rt_cd=0")
+                        return r
+                    # EGW00201: 초당 거래건수 초과
+                    elif j.get("msg_cd") == "EGW00201" or "초과" in str(j.get("msg1", "")) or "과부하" in str(j.get("msg1", "")):
+                        wait_time = 1 + (attempt * 1)  # 5초, 6초, 7초... (키움 봇 방식)
+                        logger.warning(
+                            f"⏳ API 과부하 (EGW00201) GET {path} TR_ID={tr_id} -> {wait_time}초 대기 후 재시도 "
+                            f"({attempt+1}/{max_retries}) rt_cd={j.get('rt_cd')} msg_cd={j.get('msg_cd')} msg1={j.get('msg1')}"
+                        )
+                        time.sleep(wait_time)
+                        continue
+                # HTTP 200이 아니거나 rt_cd != "0"인 경우
+                try:
+                    body_preview = (r.text or "")[:500]
+                except Exception:
+                    body_preview = ""
+                logger.warning(
+                    f"[API실패] GET {path} TR_ID={tr_id} status={r.status_code} "
+                    f"params={params} body={body_preview}"
+                )
+                return r
+            except requests.exceptions.RequestException as e:
+                if attempt < max_retries - 1:
+                    wait_time = (2 ** attempt) + random.uniform(0.5, 1.5)
+                    logger.warning(f"⚠️ 네트워크 에러 -> {wait_time:.1f}초 대기 후 재시도: {e}")
+                    time.sleep(wait_time)
+                else:
+                    logger.error(f"❌ GET 요청 실패 ({path}): {e}")
+        return r
+
+    def _post(self, path, tr_id, body, use_hashkey=True, max_retries=3):
+        """
+        POST 요청. EGW00201(초당 거래건수 초과) 시 점진적 대기 시간 증가 재시도
+        - 한투 API 제한: 초당 20개 (실제로는 더 엄격)
+        - EGW00201 감지 시: 5초 + (attempt * 1초) 대기 후 재시도
+        """
+        url = f"{self.base_url}{path}"
+        hashkey = None
+        
+        # API 호출 정보 디버그 로그 (민감 정보는 일부만)
+        body_preview = str(body)[:200] if body else "{}"
+        logger.debug(f"[API호출] POST {path} TR_ID={tr_id} body={body_preview}...")
+        
+        # 기본 안전 대기 (서버 부하 완화)
+        time.sleep(0.5)
+        
+        # 해시키 발급 (선택적이지만 보안 강화)
+        if use_hashkey:
+            hashkey = self._get_hashkey(body)
+            if not hashkey:
+                logger.debug("해시키 발급 실패, 해시키 없이 진행")
+        
+        for attempt in range(max_retries):
+            try:
+                r = requests.post(url, headers=self._headers(tr_id, hashkey), json=body, timeout=15)
+                
+                # HTTP 429 (Too Many Requests)
+                if r.status_code == 429:
+                    wait_time = 5 + (attempt * 1)  # 5초, 6초, 7초...
+                    logger.warning(
+                        f"⏳ API 호출 제한 (429) -> {wait_time}초 대기 후 재시도 "
+                        f"({attempt+1}/{max_retries}) path={path}"
+                    )
+                    time.sleep(wait_time)
+                    # 해시키 재발급
+                    if use_hashkey:
+                        hashkey = self._get_hashkey(body)
+                    continue
+                
+                if r.status_code == 200:
+                    j = r.json()
+                    if j.get("rt_cd") == "0":
+                        logger.debug(f"[API성공] POST {path} TR_ID={tr_id} status=200 rt_cd=0")
+                        return r
+                    # EGW00201: 초당 거래건수 초과
+                    elif j.get("msg_cd") == "EGW00201" or "초과" in str(j.get("msg1", "")) or "과부하" in str(j.get("msg1", "")):
+                        wait_time = 5 + (attempt * 1)  # 5초, 6초, 7초... (키움 봇 방식)
+                        logger.warning(
+                            f"⏳ API 과부하 (EGW00201) POST {path} TR_ID={tr_id} -> {wait_time}초 대기 후 재시도 "
+                            f"({attempt+1}/{max_retries}) rt_cd={j.get('rt_cd')} msg_cd={j.get('msg_cd')} msg1={j.get('msg1')}"
+                        )
+                        time.sleep(wait_time)
+                        if use_hashkey:
+                            hashkey = self._get_hashkey(body)
+                        continue
+                # HTTP 200이 아니거나 rt_cd != "0"인 경우
+                try:
+                    body_preview = (r.text or "")[:500]
+                except Exception:
+                    body_preview = ""
+                logger.warning(
+                    f"[API실패] POST {path} TR_ID={tr_id} status={r.status_code} "
+                    f"body={body_preview}"
+                )
+                return r
+            except requests.exceptions.RequestException as e:
+                if attempt < max_retries - 1:
+                    wait_time = (2 ** attempt) + random.uniform(0.5, 1.5)
+                    logger.warning(f"⚠️ 네트워크 에러 -> {wait_time:.1f}초 대기 후 재시도: {e}")
+                    time.sleep(wait_time)
+                else:
+                    logger.error(f"❌ POST 요청 실패 ({path}): {e}")
+        return r
+
+    def inquire_price(self, stock_code):
+        """
+        주식 현재가 시세 조회 [v1_국내주식-008] (단건).
+        output: stck_prpr(현재가) ✅, stck_oprc(시가), stck_hgpr(고가), stck_lwpr(저가) 등 당일 OHLC 포함.
+        실패 시 오류코드(rt_cd, msg_cd, msg1) 로깅.
+        """
+        path = "/uapi/domestic-stock/v1/quotations/inquire-price"
+        tr_id = "FHKST01010100"
+        params = {"FID_COND_MRKT_DIV_CODE": "J", "FID_INPUT_ISCD": stock_code}
+        logger.debug(f"[현재가API] 호출 code={stock_code} path={path} TR_ID={tr_id}")
+        r = self._get(path, tr_id, params)
+        if r.status_code != 200:
+            try:
+                body_preview = (r.text or "")[:300]
+            except Exception:
+                body_preview = ""
+            logger.warning(
+                f"[현재가API] HTTP 실패 code={stock_code} path={path} TR_ID={tr_id} "
+                f"status={r.status_code} body={body_preview}"
+            )
+            return None
+        try:
+            j = r.json()
+        except Exception as e:
+            logger.warning(
+                f"[현재가API] JSON 파싱 실패 code={stock_code} path={path} TR_ID={tr_id} exception={e}"
+            )
+            return None
+        if j.get("rt_cd") != "0":
+            logger.warning(
+                f"[현재가API] 오류 code={stock_code} path={path} TR_ID={tr_id} "
+                f"rt_cd={j.get('rt_cd')} msg_cd={j.get('msg_cd')} msg1={j.get('msg1')}"
+            )
+            return None
+        return j.get("output")
+
+    def inquire_multprice(self, stock_codes: List[str], max_per_call: int = 20):
+        """
+        다중 종목 현재가 조회 [intstock-multprice]
+        - 한투 API: /uapi/domestic-stock/v1/quotations/intstock-multprice
+        - 성공 시 {종목코드: output딕셔너리} 반환, 실패 시 None (오류 시 rt_cd/msg_cd/msg1 로깅)
+        - TR_ID: FHKST01010600
+        - ⚠️ 배치 응답에는 stck_oprc(시가)/stck_hgpr(고가)/stck_lwpr(저가)가 없을 수 있음(API 스펙).
+          시가·고가·저가 필요 시 단건 inquire_price() 사용.
+        """
+        if not stock_codes:
+            return None
+        codes = list(stock_codes)[: max_per_call * 10]
+        result = {}
+        for i in range(0, len(codes), max_per_call):
+            chunk = codes[i : i + max_per_call]
+            iscd = ",".join(chunk)
+            path = "/uapi/domestic-stock/v1/quotations/intstock-multprice"
+            tr_id = "FHKST01010600"
+            params = {"FID_COND_MRKT_DIV_CODE": "J", "FID_INPUT_ISCD": iscd}
+            r = self._get(path, tr_id, params)
+            if r.status_code != 200:
+                try:
+                    body_preview = (r.text or "")[:300]
+                except Exception:
+                    body_preview = ""
+                logger.warning(
+                    f"[다중시세API] HTTP 실패 status={r.status_code} body={body_preview}"
+                )
+                continue
+            try:
+                j = r.json()
+            except Exception as e:
+                logger.warning(f"[다중시세API] JSON 파싱 실패 exception={e}")
+                continue
+            if j.get("rt_cd") != "0":
+                logger.warning(
+                    f"[다중시세API] 오류 rt_cd={j.get('rt_cd')} "
+                    f"msg_cd={j.get('msg_cd')} msg1={j.get('msg1')}"
+                )
+                continue
+            out = j.get("output")
+            if out is None:
+                continue
+            if isinstance(out, list):
+                for item in out:
+                    if isinstance(item, dict):
+                        code = (
+                            item.get("stck_shrn_iscd")
+                            or item.get("rsym")
+                            or item.get("FID_INPUT_ISCD")
+                            or item.get("mksc_shrn_iscd")
+                        )
+                        if code:
+                            result[code] = item
+            elif isinstance(out, dict):
+                code = (
+                    out.get("stck_shrn_iscd")
+                    or out.get("rsym")
+                    or out.get("FID_INPUT_ISCD")
+                )
+                if code:
+                    result[code] = out
+            time.sleep(random.uniform(0.2, 0.5))
+        return result if result else None
+
+    def inquire_prices_batch(self, stock_codes: List[str]):
+        """
+        다중 종목 현재가 일괄 조회
+        - intstock-multprice API 우선 시도 후, 실패 시 순차 조회(inquire_price)로 fallback
+        - 순차 조회 시 종목당 0.3~0.6초 딜레이
+        - 배치 응답에는 stck_prpr(현재가)는 있으나, stck_oprc/stck_hgpr/stck_lwpr 는 없을 수 있음.
+          시가·고가·저가 필요 시 배치 대신 종목별 inquire_price() 사용(개미털기 스캔은 이미 단건 사용).
+        """
+        if not stock_codes:
+            return {}
+        multi = self.inquire_multprice(stock_codes)
+        if multi:
+            return multi
+        result = {}
+        for code in stock_codes:
+            try:
+                price_data = self.inquire_price(code)
+                if price_data:
+                    result[code] = price_data
+                time.sleep(random.uniform(0.3, 0.6))
+            except Exception as e:
+                logger.warning(f"종목 조회 실패({code}) exception={e!r}")
+                continue
+        return result
+
+    def get_account_balance(self):
+        """계좌 잔고 조회 [v1_국내주식-010]. 모의/실전에 따라 TR ID 분기 (EGW2004 방지)."""
+        if self.mock:
+            tr_id = "VTTC8434R"
+        else:
+            tr_id = "TTTC8434R"
+        params = {
+            "CANO": self.acc_no,
+            "ACNT_PRDT_CD": self.acc_code,
+            "AFHR_FLPR_YN": "N",
+            "OFL_YN": "",
+            "INQR_DVSN": "01",   # 01: 예수금/잔고 요약 (output2에 예수금) - 블로그·한투 문서 기준
+            "UNPR_DVSN": "01",
+            "FUND_STTL_ICLD_YN": "N",
+            "FNCG_AMT_AUTO_RDPT_YN": "N",
+            "PRCS_DVSN": "00",   # 00: 조회 (블로그 기준)
+            "CTX_AREA_FK100": "",
+            "CTX_AREA_NK100": "",
+        }
+        try:
+            logger.info(f"💵 [예수금] 잔고 조회 요청: TR={tr_id}, CANO={self.acc_no}, ACNT_PRDT_CD={self.acc_code}, 모의={self.mock}")
+            r = self._get(
+                "/uapi/domestic-stock/v1/trading/inquire-balance",
+                tr_id,
+                params,
+            )
+            if r.status_code != 200:
+                logger.warning(
+                    f"💵 [예수금] 잔고 API HTTP 오류: status={r.status_code}, body={getattr(r, 'text', '')[:200]} | "
+                    f"TR={tr_id} (모의={self.mock}), CANO={self.acc_no}, ACNT_PRDT_CD={self.acc_code}. "
+                    f"EGW2004 시 모의면 VTTC8434R/실전이면 TTTC8434R 확인"
+                )
+                return None
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                msg1 = (j.get("msg1") or "")[:150]
+                msg_cd = j.get("msg_cd", "")
+                logger.error(
+                    f"💵 [예수금] 잔고 API 응답 오류: rt_cd={j.get('rt_cd')}, msg_cd={msg_cd}, msg1={msg1} | "
+                    f"요청 파라미터: TR={tr_id}, CANO={self.acc_no}({len(self.acc_no)}자리), "
+                    f"ACNT_PRDT_CD={self.acc_code}({len(self.acc_code)}자리), 모의={self.mock} | "
+                    f"전체 응답: {j}"
+                )
+                if "OPSQ2000" in str(msg_cd) or "INVALID_CHECK_ACNO" in msg1:
+                    logger.error(
+                        "💵 [예수금] OPSQ2000 = 계좌번호 검증 실패. "
+                        f"모의투자 서버({self.base_url})에 계좌번호 CANO={self.acc_no}, ACNT_PRDT_CD={self.acc_code}가 등록되어 있는지 확인. "
+                        f"한투 모의투자 앱/웹에서 계좌번호 확인 필요. DB의 KIS_ACCOUNT_NO_MOCK/KIS_ACCOUNT_CODE_MOCK 값 확인."
+                    )
+                return None
+            logger.debug(f"💵 [예수금] 잔고 조회 성공: output2 keys={list(j.get('output2', [{}])[0].keys()) if isinstance(j.get('output2'), list) and j.get('output2') else []}")
+            return j
+        except Exception as e:
+            logger.error(f"💵 [예수금] 잔고 조회 예외: {e} | CANO={self.acc_no}, ACNT_PRDT_CD={self.acc_code}, 모의={self.mock}")
+            return None
+    
+    def get_account_evaluation(self):
+        """계좌 평가 잔고 조회 [v1_국내주식-011]. 모의=VTTC8494R, 실전=TTTC8494R."""
+        if self.mock:
+            tr_id = "VTTC8494R"
+        else:
+            tr_id = "TTTC8494R"
+        try:
+            logger.info(tr_id)
+            r = self._get(
+                "/uapi/domestic-stock/v1/trading/inquire-balance-rlz-pl",
+                tr_id,
+                {
+                    "CANO": self.acc_no,
+                    "ACNT_PRDT_CD": self.acc_code,
+                    "AFHR_FLPR_YN": "N",
+                    "OFL_YN": "",
+                    "INQR_DVSN": "01",
+                    "UNPR_DVSN": "01",
+                    "FUND_STTL_ICLD_YN": "N",
+                    "FNCG_AMT_AUTO_RDPT_YN": "N",
+                    "PRCS_DVSN": "01",
+                    "CTX_AREA_FK100": "",
+                    "CTX_AREA_NK100": "",
+                },
+            )
+            if r.status_code != 200:
+                return None
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                return None
+            return j
+        except Exception as e:
+            logger.error(f"계좌 평가 조회 실패: {e}")
+            return None
+    
+    def get_order_history(self, start_date=None, end_date=None):
+        """주문 체결 내역 조회 [v1_국내주식-012] (모의=VTTC8001R, 실전=TTTC8001R)"""
+        try:
+            if self.mock:
+                tr_id = "VTTC8001R"
+            else:
+                tr_id = "TTTC8001R"
+            if not start_date:
+                start_date = dt.now().strftime("%Y%m%d")
+            if not end_date:
+                end_date = dt.now().strftime("%Y%m%d")
+            
+            r = self._get(
+                "/uapi/domestic-stock/v1/trading/inquire-daily-ccld",
+                tr_id,
+                {
+                    "CANO": self.acc_no,
+                    "ACNT_PRDT_CD": self.acc_code,
+                    "INQR_STRT_DT": start_date,
+                    "INQR_END_DT": end_date,
+                    "SLL_BUY_DVSN_CD": "00",  # 00:전체
+                    "INQR_DVSN": "00",  # 00:역순
+                    "PDNO": "",
+                    "CCLD_DVSN": "00",  # 00:전체
+                    "ORD_GNO_BRNO": "",
+                    "ODNO": "",
+                    "INQR_DVSN_3": "00",
+                    "INQR_DVSN_1": "",
+                    "CTX_AREA_FK100": "",
+                    "CTX_AREA_NK100": "",
+                },
+            )
+            if r.status_code != 200:
+                return None
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                return None
+            return j
+        except Exception as e:
+            logger.error(f"주문 내역 조회 실패: {e}")
+            return None
+    
+    def get_volume_surge_stocks(self, market="J", min_volume_rate="50", limit=50):
+        """거래량 급증 종목 조회 [v1_국내주식-023]"""
+        try:
+            r = self._get(
+                "/uapi/domestic-stock/v1/quotations/inquire-time-itemchartprice",
+                "FHKST03010200",
+                {
+                    "FID_COND_MRKT_DIV_CODE": market,
+                    "FID_INPUT_ISCD": "",
+                    "FID_INPUT_HOUR_1": dt.now().strftime("%Y%m%d"),
+                    "FID_INPUT_HOUR_2": dt.now().strftime("%Y%m%d"),
+                    "FID_PW_DATA_INCU_YN": "Y",
+                },
+            )
+            # 실제로는 거래량 급증 API를 사용해야 하지만, 여기서는 예시로 현재가 조회 활용
+            # 실제 구현 시: /uapi/domestic-stock/v1/quotations/inquire-time-itemchartprice 사용
+            return []
+        except Exception as e:
+            logger.error(f"거래량 급증 종목 조회 실패: {e}")
+            return []
+    
+    def get_top_price_movers(self, market="J", sort_type="1", limit=50):
+        """등락률 상위 종목 조회 [v1_국내주식-027]"""
+        try:
+            r = self._get(
+                "/uapi/domestic-stock/v1/quotations/inquire-time-itemchartprice",
+                "FHKST03010200",
+                {
+                    "FID_COND_MRKT_DIV_CODE": market,
+                    "FID_INPUT_ISCD": "",
+                    "FID_INPUT_HOUR_1": dt.now().strftime("%Y%m%d"),
+                    "FID_INPUT_HOUR_2": dt.now().strftime("%Y%m%d"),
+                    "FID_PW_DATA_INCU_YN": "Y",
+                },
+            )
+            # 실제 구현 필요
+            return []
+        except Exception as e:
+            logger.error(f"등락률 상위 조회 실패: {e}")
+            return []
+    
+    def get_investor_trend(self, stock_code, days=5):
+        """외국인/기관 매매 동향 조회"""
+        path = "/uapi/domestic-stock/v1/quotations/inquire-daily-itemchartprice"
+        tr_id = "FHKST03010100"
+        try:
+            # 일봉 데이터에서 외국인/기관 정보 추출
+            end_dt = dt.now()
+            start_dt = end_dt - datetime.timedelta(days=days + 10)
+            start_ymd = start_dt.strftime("%Y%m%d")
+            end_ymd = end_dt.strftime("%Y%m%d")
+            
+            params = {
+                "FID_COND_MRKT_DIV_CODE": "J",
+                "FID_INPUT_ISCD": stock_code,
+                "FID_INPUT_DATE_1": start_ymd,
+                "FID_INPUT_DATE_2": end_ymd,
+                "FID_PERIOD_DIV_CODE": "D",
+                "FID_ORG_ADJ_PRC": "1",
+            }
+            logger.debug(f"[투자자동향] 호출 code={stock_code} path={path} TR_ID={tr_id}")
+            r = self._get(path, tr_id, params)
+            if r.status_code != 200:
+                logger.warning(f"[투자자동향] HTTP 실패 code={stock_code} path={path} TR_ID={tr_id} status={r.status_code}")
+                return None
+            
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                logger.warning(
+                    f"[투자자동향] 오류 code={stock_code} path={path} TR_ID={tr_id} "
+                    f"rt_cd={j.get('rt_cd')} msg_cd={j.get('msg_cd')} msg1={j.get('msg1')}"
+                )
+                return None
+            
+            out2 = j.get("output2", [])
+            if not out2:
+                return None
+            
+            # 최근 N일 외국인/기관 순매수 합계
+            foreign_sum = 0
+            org_sum = 0
+            
+            for item in out2[:days]:
+                try:
+                    foreign_raw = item.get("frgn_ntby_qty") or item.get("frgn_ntby_shnu") or "0"
+                    foreign_net = int(float(str(foreign_raw).replace(",", "").replace("+", "").replace("-", "")))
+                    if str(foreign_raw).startswith("-"):
+                        foreign_net = -foreign_net
+                    
+                    org_raw = item.get("orgn_ntby_qty") or "0"
+                    org_net = int(float(str(org_raw).replace(",", "").replace("+", "").replace("-", "")))
+                    if str(org_raw).startswith("-"):
+                        org_net = -org_net
+                    
+                    foreign_sum += foreign_net
+                    org_sum += org_net
+                except:
+                    continue
+            
+            return {
+                "foreign_net_buy": foreign_sum,
+                "org_net_buy": org_sum,
+                "total_net_buy": foreign_sum + org_sum,
+            }
+        except Exception as e:
+            logger.error(f"외국인/기관 동향 조회 실패({stock_code}): {e}")
+            return None
+
+    def get_daily_chart(self, code, limit=10):
+        """일봉 차트 조회 [v1_국내주식-017] - 거래대금(대/중/소형) 계산용"""
+        path = "/uapi/domestic-stock/v1/quotations/inquire-daily-itemchartprice"
+        tr_id = "FHKST03010100"
+        try:
+            end_dt = dt.now()
+            start_dt = end_dt - datetime.timedelta(days=limit + 30)
+            start_ymd = start_dt.strftime("%Y%m%d")
+            end_ymd = end_dt.strftime("%Y%m%d")
+            params = {
+                "FID_COND_MRKT_DIV_CODE": "J",
+                "FID_INPUT_ISCD": code,
+                "FID_INPUT_DATE_1": start_ymd,
+                "FID_INPUT_DATE_2": end_ymd,
+                "FID_PERIOD_DIV_CODE": "D",
+                "FID_ORG_ADJ_PRC": "1",
+            }
+            logger.debug(f"[일봉차트] 호출 code={code} path={path} TR_ID={tr_id}")
+            r = self._get(path, tr_id, params)
+            if r.status_code != 200:
+                logger.warning(f"[일봉차트] HTTP 실패 code={code} path={path} TR_ID={tr_id} status={r.status_code}")
+                return pd.DataFrame()
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                logger.warning(
+                    f"[일봉차트] 오류 code={code} path={path} TR_ID={tr_id} "
+                    f"rt_cd={j.get('rt_cd')} msg_cd={j.get('msg_cd')} msg1={j.get('msg1')}"
+                )
+                return pd.DataFrame()
+            data = j.get("output2", [])
+            if not data:
+                return pd.DataFrame()
+            rows = []
+            for item in data:
+                try:
+                    rows.append({
+                        "date": item.get("stck_bsop_date", ""),
+                        "open": abs(float(item.get("stck_oprc", 0))),
+                        "high": abs(float(item.get("stck_hgpr", 0))),
+                        "low": abs(float(item.get("stck_lwpr", 0))),
+                        "close": abs(float(item.get("stck_clpr", 0))),
+                        "volume": int(item.get("acml_vol", 0)),
+                    })
+                except Exception:
+                    continue
+            if not rows:
+                return pd.DataFrame()
+            df = pd.DataFrame(rows)
+            df = df.sort_values("date").reset_index(drop=True)
+            return df.tail(limit)
+        except Exception as e:
+            logger.error(f"일봉 조회 실패({code}): {e}")
+            return pd.DataFrame()
+
+    def buy_order(self, code, qty, price=0, order_type="01"):
+        """
+        매수 주문 (모의=VTTC0802U, 실전=TTTC0802U)
+        
+        Args:
+            code: 종목코드
+            qty: 수량
+            price: 가격 (0이면 시장가)
+            order_type: 주문구분
+                - "01": 시장가
+                - "00": 지정가
+                - "05": 조건부지정가
+                - "06": 최유리지정가
+                - "07": 최우선지정가
+                - "10": 보통(IOC)
+                - "13": 시장가(IOC)
+                - "16": 최유리(IOC)
+                - "20": 보통(FOK)
+                - "23": 시장가(FOK)
+                - "26": 최유리(FOK)
+        """
+        try:
+            if self.mock:
+                tr_id = "VTTC0802U"
+            else:
+                tr_id = "TTTC0802U"
+            if price > 0:
+                ord_unpr = str(price)
+            else:
+                ord_unpr = "0"
+            path = "/uapi/domestic-stock/v1/trading/order-cash"
+            body = {
+                "CANO": self.acc_no,
+                "ACNT_PRDT_CD": self.acc_code,
+                "PDNO": code,
+                "ORD_DVSN": order_type,
+                "ORD_QTY": str(qty),
+                "ORD_UNPR": ord_unpr,
+            }
+            logger.debug(f"[매수주문] 호출 code={code} qty={qty} price={price} path={path} TR_ID={tr_id}")
+            r = self._post(path, tr_id, body, use_hashkey=True)
+            if r.status_code != 200:
+                logger.error(f"[매수주문] HTTP 에러 code={code} path={path} TR_ID={tr_id} status={r.status_code}")
+                return False
+            j = r.json()
+            if j.get("rt_cd") == "0":
+                ord_no = j.get("output", {}).get("ODNO", "")
+                logger.info(f"✅ 매수 주문 성공: {code} {qty}주 (주문번호: {ord_no})")
+                return True
+            else:
+                logger.error(
+                    f"[매수주문] 실패 code={code} path={path} TR_ID={tr_id} "
+                    f"rt_cd={j.get('rt_cd')} msg_cd={j.get('msg_cd')} msg1={j.get('msg1')}"
+                )
+                return False
+        except Exception as e:
+            logger.error(f"매수 주문 예외({code}): {e}")
+            return False
+
+    def buy_market_order(self, code, qty):
+        """시장가 매수 주문 (간편 메서드)"""
+        return self.buy_order(code, qty, price=0, order_type="01")
+
+    def sell_order(self, code, qty, price=0, order_type="01"):
+        """
+        매도 주문 (모의=VTTC0801U, 실전=TTTC0801U)
+        
+        Args:
+            code: 종목코드
+            qty: 수량
+            price: 가격 (0이면 시장가)
+            order_type: 주문구분 (buy_order와 동일)
+        """
+        try:
+            if self.mock:
+                tr_id = "VTTC0801U"
+            else:
+                tr_id = "TTTC0801U"
+            if price > 0:
+                ord_unpr = str(price)
+            else:
+                ord_unpr = "0"
+            path = "/uapi/domestic-stock/v1/trading/order-cash"
+            body = {
+                "CANO": self.acc_no,
+                "ACNT_PRDT_CD": self.acc_code,
+                "PDNO": code,
+                "ORD_DVSN": order_type,
+                "ORD_QTY": str(qty),
+                "ORD_UNPR": ord_unpr,
+            }
+            logger.debug(f"[매도주문] 호출 code={code} qty={qty} price={price} path={path} TR_ID={tr_id}")
+            r = self._post(path, tr_id, body, use_hashkey=True)
+            if r.status_code != 200:
+                logger.error(f"[매도주문] HTTP 에러 code={code} path={path} TR_ID={tr_id} status={r.status_code}")
+                return False
+            j = r.json()
+            if j.get("rt_cd") == "0":
+                ord_no = j.get("output", {}).get("ODNO", "")
+                logger.info(f"✅ 매도 주문 성공: {code} {qty}주 (주문번호: {ord_no})")
+                return True
+            else:
+                logger.error(
+                    f"[매도주문] 실패 code={code} path={path} TR_ID={tr_id} "
+                    f"rt_cd={j.get('rt_cd')} msg_cd={j.get('msg_cd')} msg1={j.get('msg1')}"
+                )
+                return False
+        except Exception as e:
+            logger.error(f"매도 주문 예외({code}): {e}")
+            return False
+
+    def sell_market_order(self, code, qty):
+        """시장가 매도 주문 (간편 메서드)"""
+        return self.sell_order(code, qty, price=0, order_type="01")
+
+    def get_minute_chart(self, code, period="3", limit=100):
+        """분봉 차트 조회 [v1_국내주식-017]"""
+        path = "/uapi/domestic-stock/v1/quotations/inquire-time-itemchartprice"
+        tr_id = "FHKST03010200"
+        try:
+            end_dt = dt.now()
+            start_dt = end_dt - datetime.timedelta(days=1)
+            start_ymd = start_dt.strftime("%Y%m%d")
+            end_ymd = end_dt.strftime("%Y%m%d")
+            
+            # 분봉 코드: 1분=1, 3분=3, 5분=5, 10분=10, 30분=30, 60분=60
+            period_map = {"1": "1", "3": "3", "5": "5", "10": "10", "30": "30", "60": "60"}
+            period_code = period_map.get(str(period), "3")
+            
+            params = {
+                "FID_COND_MRKT_DIV_CODE": "J",
+                "FID_INPUT_ISCD": code,
+                "FID_INPUT_HOUR_1": start_ymd,
+                "FID_INPUT_HOUR_2": end_ymd,
+                "FID_PW_DATA_INCU_YN": "Y",
+                "FID_ETC_CLS_CODE": "",  # 기타분류코드 (필수 파라미터, 빈 값 가능)
+            }
+            logger.debug(f"[분봉차트] 호출 code={code} period={period} path={path} TR_ID={tr_id}")
+            r = self._get(path, tr_id, params)
+            if r.status_code != 200:
+                logger.warning(f"[분봉차트] HTTP 실패 code={code} path={path} TR_ID={tr_id} status={r.status_code}")
+                return pd.DataFrame()
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                logger.warning(
+                    f"[분봉차트] 오류 code={code} path={path} TR_ID={tr_id} "
+                    f"rt_cd={j.get('rt_cd')} msg_cd={j.get('msg_cd')} msg1={j.get('msg1')}"
+                )
+                return pd.DataFrame()
+            
+            data = j.get("output2", [])
+            if not data:
+                return pd.DataFrame()
+            
+            rows = []
+            for item in data:
+                try:
+                    rows.append({
+                        "time": item.get("stck_bsop_date", ""),
+                        "open": abs(float(item.get("stck_oprc", 0))),
+                        "high": abs(float(item.get("stck_hgpr", 0))),
+                        "low": abs(float(item.get("stck_lwpr", 0))),
+                        "close": abs(float(item.get("stck_clpr", 0))),
+                        "volume": int(item.get("acml_vol", 0)),
+                    })
+                except:
+                    continue
+            
+            if not rows:
+                return pd.DataFrame()
+            
+            df = pd.DataFrame(rows)
+            df = df.sort_values("time").reset_index(drop=True)
+            
+            # 기술적 지표 추가
+            if len(df) >= 14:
+                delta = df["close"].diff(1)
+                gain = delta.where(delta > 0, 0).rolling(window=14).mean()
+                loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
+                rs = gain / loss.replace(0, float("nan"))
+                df["RSI"] = 100 - (100 / (1 + rs))
+            
+            if len(df) >= 20:
+                df["MA20"] = df["close"].rolling(window=20).mean()
+            
+            return df.tail(limit)
+        except Exception as e:
+            logger.error(f"분봉 조회 실패({code}): {e}")
+            return pd.DataFrame()
+    
+    def get_orderbook(self, stock_code):
+        """호가 조회 [v1_국내주식-009]"""
+        try:
+            r = self._get(
+                "/uapi/domestic-stock/v1/quotations/inquire-asking-price-exp-ccn",
+                "FHKST01010200",
+                {
+                    "FID_COND_MRKT_DIV_CODE": "J",
+                    "FID_INPUT_ISCD": stock_code,
+                },
+            )
+            if r.status_code != 200:
+                return None
+            j = r.json()
+            if j.get("rt_cd") != "0":
+                return None
+            return j.get("output")
+        except Exception as e:
+            logger.error(f"호가 조회 실패({stock_code}): {e}")
+            return None
+    
+    # ============================================================
+    # 순위분석 API (키움 봇과 동일한 로직 + 레버리지/스팩/ETN 제외 옵션)
+    # ============================================================
+    
+    @staticmethod
+    def _is_valid_stock(name: str, code: str) -> bool:
+        """
+        종목 필터링 (키움 kiwoom_trader_ver2와 동일, ETF는 포함)
+        - 스팩, ETN, 우선주, 레버리지, 인버스 등만 제외 (ETF는 위험도 낮아 포함)
+        """
+        if not code or len(code) != 6 or not code.isdigit():
+            return False
+        name = (name or "").strip()
+        exclude = [
+            "스팩", "SPAC", "ETN", "W", "ELW", "채권",
+            "레버리지", "인버스", "곱버스", "선물", "콜", "풋",
+            "2X", "3X", "합성", "H", "B",
+        ]
+        # ETF는 exclude 목록에 없음 → 일반 주식·ETF 모두 통과
+        if any(k in name for k in exclude):
+            return False
+        if name.endswith("우") or name.endswith("우B"):
+            return False
+        return True
+
+    def _filter_rank_by_valid_stock(self, rank_list: list) -> list:
+        """랭크 API 응답 리스트에서 스팩/ETN/레버리지 등 제외 (키움 옵션과 동일)"""
+        if not rank_list:
+            return []
+        filtered = []
+        for item in rank_list:
+            code = (item.get("stk_cd") or item.get("mksc_shrn_iscd") or item.get("code") or "").strip()
+            name = (item.get("stk_nm") or item.get("prst_name") or item.get("hts_kor_isnm") or "").strip()
+            if self._is_valid_stock(name, code):
+                filtered.append(item)
+        return filtered
+
+    def _fetch_volume_rank_paged(
+        self,
+        market: str,
+        blng_cls_code: str,
+        limit: int,
+        exclude_spec_etn_leverage: bool,
+    ) -> list:
+        """
+        거래량순위 API 연속 조회 (tr_cont)로 limit건까지 수집.
+        API가 한 번에 20~30건만 주므로, tr_cont='M'이면 다음 페이지 요청 반복.
+        """
+        path = "/uapi/domestic-stock/v1/quotations/volume-rank"
+        tr_id = "FHPST01710000"
+        base = {
+            "FID_COND_MRKT_DIV_CODE": market,
+            "FID_COND_SCR_DIV_CODE": "20171",
+            "FID_INPUT_ISCD": "0000",
+            "FID_DIV_CLS_CODE": "0",
+            "FID_BLNG_CLS_CODE": blng_cls_code,
+            "FID_TRGT_CLS_CODE": "111111111",
+            "FID_TRGT_EXLS_CLS_CODE": "0000000000",
+            "FID_INPUT_PRICE_1": "0",
+            "FID_INPUT_PRICE_2": "0",
+            "FID_VOL_CNT": "0",
+            "FID_INPUT_DATE_1": "",
+        }
+        accumulated = []
+        tr_cont = ""
+        max_pages = 20  # 20페이지 이상이면 중단 (과부하 방지)
+        page = 0
+        try:
+            while len(accumulated) < limit and page < max_pages:
+                params = {**base}
+                time.sleep(0.5)
+                # 연속 조회 시 tr_cont는 요청 헤더로 전달 (한투 문서: Request Header tr_cont=N)
+                r = self._get(path, tr_id, params, tr_cont=tr_cont if tr_cont else None)
+                if r.status_code != 200:
+                    break
+                j = r.json()
+                if j.get("rt_cd") != "0":
+                    break
+                output = j.get("output", [])
+                if exclude_spec_etn_leverage:
+                    output = self._filter_rank_by_valid_stock(output)
+                # 2차 이상 수신 시: 이번 output이 이미 누적된 종목과 완전 동일하면 서버가 같은 페이지를 반복 준 것 → 중복 누적·추가 요청 중단
+                def _codes_from_list(lst):
+                    s = set()
+                    for item in lst:
+                        c = (item.get("stk_cd") or item.get("mksc_shrn_iscd") or item.get("code") or "").strip()
+                        if c:
+                            s.add(c)
+                    return s
+                if page >= 1 and output:
+                    already = _codes_from_list(accumulated)
+                    this_codes = _codes_from_list(output)
+                    if this_codes and this_codes <= already:
+                        logger.info(f"   📡 [순위API] 2차 수신 {len(output)}건은 1차와 동일(중복) → 연속조회 중단 (API가 다음 페이지 미지원 또는 동일 데이터 반환)")
+                        break
+                accumulated.extend(output)
+                # 연속 조회: tr_cont는 HTTP 응답 헤더에 있음 (한투 문서). 소문자/대문자 모두 확인
+                tr_cont_resp = ""
+                for k, v in (r.headers or {}).items():
+                    if k.strip().lower() == "tr_cont" and v:
+                        tr_cont_resp = v.strip() if isinstance(v, str) else str(v)
+                        break
+                if not tr_cont_resp:
+                    tr_cont_resp = (r.headers.get("tr_cont") or r.headers.get("TR_CONT") or "").strip()
+                if isinstance(tr_cont_resp, str):
+                    tr_cont_resp = tr_cont_resp.strip()
+                # 페이지네이션 동작 확인용 INFO 로그 (기본 로그 레벨에서 보이도록)
+                header_keys = list((r.headers or {}).keys())
+                logger.info(f"   📡 [순위API] 1차 수신 {len(output)}건, 누적 {len(accumulated)}건 | 응답 tr_cont='{tr_cont_resp}' | 헤더키: {header_keys}")
+                # tr_cont=M이면 다음 페이지 있음. 또는 첫 페이지에서 누적이 limit 미만이면 한 번 더 시도 (서버가 tr_cont 없이도 다음 페이지 지원하는 경우 대비)
+                if tr_cont_resp == "M":
+                    tr_cont = "N"
+                    page += 1
+                    logger.info(f"   📡 [연속조회] tr_cont=M → tr_cont=N으로 다음 페이지 요청 (페이지 {page})")
+                elif page == 0 and len(output) > 0 and len(accumulated) < limit:
+                    tr_cont = "N"
+                    page += 1
+                    logger.info(f"   📡 [연속조회] 누적 {len(accumulated)}건 < {limit}건 → tr_cont=N으로 다음 페이지 1회 시도")
+                else:
+                    break
+                time.sleep(random.uniform(0.8, 1.5))
+            return accumulated[:limit]
+        except Exception as e:
+            logger.debug(f"거래량순위 연속 조회 실패: {e}")
+            return accumulated[:limit]
+
+    def get_volume_rank(
+        self,
+        market: str = "J",
+        limit: int = 50,
+        exclude_spec_etn_leverage: bool = True,
+    ):
+        """
+        거래량순위 조회 [v1_국내주식-047] (연속 조회로 limit건까지 수집)
+        """
+        try:
+            output = self._fetch_volume_rank_paged(
+                market=market,
+                blng_cls_code="0",
+                limit=limit,
+                exclude_spec_etn_leverage=exclude_spec_etn_leverage,
+            )
+            return output
+        except Exception as e:
+            logger.debug(f"거래량순위 조회 실패: {e}")
+            return []
+    
+    def get_price_change_rank(
+        self,
+        market: str = "J",
+        sort_type: str = "1",
+        limit: int = 50,
+        exclude_spec_etn_leverage: bool = True,
+    ):
+        """
+        등락률순위 조회 (동일 volume-rank API, FID_BLNG_CLS_CODE로 등락 구분)
+        sort_type: "1"=상승률 상위, "2"=하락률 상위(낙폭 큰 종목, N자 망치봉 스캔에 유리)
+        """
+        # 한투 volume-rank API: 4=등락률(상승), 5=등락률(하락). 미지원 시 빈값/에러 가능.
+        blng = "5" if sort_type == "2" else "4"
+        try:
+            out = self._fetch_volume_rank_paged(
+                market=market,
+                blng_cls_code=blng,
+                limit=limit,
+                exclude_spec_etn_leverage=exclude_spec_etn_leverage,
+            )
+            if out:
+                return out
+        except Exception as e:
+            logger.debug(f"등락률순위(blng={blng}) 조회 실패: {e}")
+        # API가 4/5 미지원이면 기존처럼 거래량순위로 fallback (상승 위주 후보 확보)
+        if sort_type != "2":
+            return self.get_volume_rank(market=market, limit=limit, exclude_spec_etn_leverage=exclude_spec_etn_leverage)
+        return []
+
+    def get_price_decline_rank(
+        self,
+        market: str = "J",
+        limit: int = 100,
+        exclude_spec_etn_leverage: bool = True,
+    ):
+        """하락률 순위(낙폭 큰 종목) 조회. N자 망치봉/개미털기 스캔 유니버스 확대용."""
+        return self.get_price_change_rank(
+            market=market,
+            sort_type="2",
+            limit=limit,
+            exclude_spec_etn_leverage=exclude_spec_etn_leverage,
+        )
+
+    def get_trading_value_rank(
+        self,
+        market: str = "J",
+        limit: int = 50,
+        exclude_spec_etn_leverage: bool = True,
+    ):
+        """거래대금순위 조회 (연속 조회로 limit건까지). FID_BLNG_CLS_CODE=3"""
+        try:
+            return self._fetch_volume_rank_paged(
+                market=market,
+                blng_cls_code="3",
+                limit=limit,
+                exclude_spec_etn_leverage=exclude_spec_etn_leverage,
+            )
+        except Exception as e:
+            logger.debug(f"거래대금순위 조회 실패: {e}")
+            return []
+
+    def get_turnover_rank(
+        self,
+        market: str = "J",
+        limit: int = 50,
+        exclude_spec_etn_leverage: bool = True,
+    ):
+        """회전율순위 조회 (연속 조회로 limit건까지). FID_BLNG_CLS_CODE=2"""
+        try:
+            return self._fetch_volume_rank_paged(
+                market=market,
+                blng_cls_code="2",
+                limit=limit,
+                exclude_spec_etn_leverage=exclude_spec_etn_leverage,
+            )
+        except Exception as e:
+            logger.debug(f"회전율순위 조회 실패: {e}")
+            return []
+
+    def get_volume_growth_rank(
+        self,
+        market: str = "J",
+        limit: int = 50,
+        exclude_spec_etn_leverage: bool = True,
+    ):
+        """거래증가율순위 조회 (연속 조회로 limit건까지). FID_BLNG_CLS_CODE=1"""
+        try:
+            return self._fetch_volume_rank_paged(
+                market=market,
+                blng_cls_code="1",
+                limit=limit,
+                exclude_spec_etn_leverage=exclude_spec_etn_leverage,
+            )
+        except Exception as e:
+            logger.debug(f"거래증가율순위 조회 실패: {e}")
+            return []
+
+    def get_execution_strength_rank(
+        self,
+        market: str = "J",
+        limit: int = 200,
+        exclude_spec_etn_leverage: bool = True,
+    ):
+        """체결강도 상위 순위 조회 (FHPST01710000, FID_BLNG_CLS_CODE=6). 매수세 강한 종목 필터용."""
+        try:
+            return self._fetch_volume_rank_paged(
+                market=market,
+                blng_cls_code="6",
+                limit=limit,
+                exclude_spec_etn_leverage=exclude_spec_etn_leverage,
+            )
+        except Exception as e:
+            logger.debug(f"체결강도순위 조회 실패: {e}")
+            return []
+
+    def get_execution_strength_map(self, market: str = "J", limit: int = 200):
+        """
+        체결강도 상위 API 조회 후 종목코드 -> 체결강도 값 매핑 반환.
+        output 필드: cntr_str(체결강도) 등 한투 문서 기준으로 파싱. 미제공 시 0.
+        """
+        strength_map = {}
+        try:
+            rows = self.get_execution_strength_rank(market=market, limit=limit, exclude_spec_etn_leverage=True)
+            for item in (rows or []):
+                code = (item.get("stk_cd") or item.get("mksc_shrn_iscd") or item.get("code") or "").strip()
+                if not code or len(code) != 6:
+                    continue
+                # 한투 volume-rank 체결강도: cntr_str 또는 유사 필드 (문서 확인 후 조정)
+                raw = item.get("cntr_str") or item.get("exec_str") or item.get("strg_rt") or item.get("prdy_ctrt") or ""
+                try:
+                    strength = float(str(raw).replace(",", "").strip()) if raw else 0
+                except (ValueError, TypeError):
+                    strength = 0
+                strength_map[code] = strength
+        except Exception as e:
+            logger.debug(f"체결강도 맵 조회 실패: {e}")
+        return strength_map
+
+
+# ============================================================
+# Mattermost 봇 클래스
+# ============================================================
+class MattermostBot:
+    """Mattermost 알림 봇"""
+    def __init__(self):
+        self.api_url = f"{MM_SERVER_URL.rstrip('/')}/api/v4/posts"
+        self.headers = {
+            "Authorization": f"Bearer {MM_BOT_TOKEN}",
+            "Content-Type": "application/json"
+        }
+        self.channels = self._load_channels()
+
+    def _load_channels(self):
+        """채널 설정 로드"""
+        try:
+            if MM_CONFIG_FILE.exists():
+                with open(MM_CONFIG_FILE, 'r', encoding='utf-8') as f:
+                    return json.load(f).get("channels", {})
+            return {}
+        except Exception as e:
+            logger.error(f"⚠️ MM 설정 로드 실패: {e}")
+            return {}
+
+    def send(self, channel_alias, message):
+        """메시지 전송"""
+        channel_id = self.channels.get(channel_alias)
+        if not channel_id:
+            logger.warning(f"❌ '{channel_alias}' 채널 ID 없음")
+            return False
+
+        payload = {"channel_id": channel_id, "message": message}
+        try:
+            res = requests.post(self.api_url, headers=self.headers, json=payload, timeout=3)
+            res.raise_for_status()
+            return True
+        except Exception as e:
+            logger.error(f"❌ MM 전송 에러: {e}")
+            return False
+
+
+# ============================================================
+# 단타 트레이딩 봇
+# ============================================================
+class ShortTradingBot:
+    """단타용 트레이딩 봇 - 개미털기(눌림목) 전략"""
+    def __init__(self):
+        self.db = db
+        self.client = KISClient()
+        
+        # Mattermost 초기화
+        self.mm = MattermostBot()
+        # 단타 봇 전용 채널(alias) 우선 사용, 없으면 기본 채널 사용
+        self.mm_channel = MM_CHANNEL_SHORT
+        
+        # ML 예측 초기화 (선택적)
+        self.ml_predictor = None
+        if ML_AVAILABLE:
+            try:
+                self.ml_predictor = MLPredictor(db_path=str(SCRIPT_DIR / "quant_bot.db"))
+                if self.ml_predictor.should_retrain():
+                    self.ml_predictor.train_model(retrain=True)
+            except Exception as e:
+                logger.warning(f"⚠️ ML 예측 초기화 실패: {e}")
+        
+        # 전략 파라미터 (DB·env 연동)
+        # ============================================================
+        # [손절/익절 설정] - 대형주 기준 현실적인 값
+        # ============================================================
+        # 손절 라인: -4% (주가 기준, 대형주는 노이즈 감안해 넉넉히)
+        self.stop_loss_pct = get_env_float("STOP_LOSS_PCT", -0.04)  # -4% 손절 (대형주 기준)
+        self.take_profit_pct = get_env_float("TAKE_PROFIT_PCT", 0.05)
+        self.max_stocks = get_env_int("MAX_STOCKS", 3)
+        # 개미털기 필터: 낙폭 3% 이상 + 회복률 50% 이상 통과 (후보가 너무 적으면 MIN_DROP_RATE=0.02, MIN_RECOVERY_RATIO_SHORT=0.32 등 완화)
+        self.min_drop_rate = get_env_float("MIN_DROP_RATE", 0.03)
+        self.min_recovery_ratio = get_env_float("MIN_RECOVERY_RATIO_SHORT", 0.5)
+        
+        # ATR 기반 손절/익절 배수 (변동성 기반 동적 손절가/목표가)
+        self.stop_atr_multiplier = get_env_float("STOP_ATR_MULTIPLIER_TAIL", 2.5)
+        self.target_atr_multiplier = get_env_float("TARGET_ATR_MULTIPLIER_TAIL", 8.0)
+        
+        # 24시간 보유 전략 (N자 패턴 등 다음날 상승 가능성 있는 종목)
+        self.min_hold_hours = get_env_float("MIN_HOLD_HOURS", 24.0)  # 최소 보유 시간 (기본 24시간)
+        
+        # ============================================================
+        # [리스크 관리 설정] - 변동성 역가중 (Volatility Inverse Weighting)
+        # ============================================================
+        self.risk_pct_per_trade = get_env_float("RISK_PCT_PER_TRADE", 0.01)  # 1% (계좌 기준)
+        self.kelly_multiplier = get_env_float("KELLY_MULTIPLIER", 0.25)  # 쿼터 켈리 (0.25)
+        self.max_position_pct = get_env_float("MAX_POSITION_PCT", 0.15)  # 종목당 최대 15%
+        self.min_position_amount = get_env_int("MIN_POSITION_AMOUNT", 50000)  # 최소 5만원
+        
+        # RiskManager 초기화 (변동성 역가중 + 쿼터 켈리 매수 금액 계산)
+        self.risk_mgr = None
+        if RISK_MANAGER_AVAILABLE:
+            # 켈리 공식 사용 여부 (기본 ON - 쿼터 켈리 0.25 적용)
+            use_kelly = get_env_bool("USE_KELLY_FORMULA", True)
+            self.risk_mgr = RiskManager(
+                risk_pct_per_trade=self.risk_pct_per_trade,
+                max_position_pct=self.max_position_pct,
+                min_position_amount=self.min_position_amount,
+                use_kelly=use_kelly,
+                kelly_multiplier=self.kelly_multiplier,  # 쿼터 켈리 0.25
+            )
+            kelly_status = f"켈리{'ON' if use_kelly else 'OFF'}(배율={self.kelly_multiplier})"
+            logger.info(f"✅ RiskManager 활성화: 변동성 역가중 + {kelly_status}")
+        else:
+            logger.warning("⚠️ RiskManager 미사용: 고정 슬롯 금액 방식으로 폴백")
+        
+        # ML 신호 필터링 설정
+        self.use_ml_signal = get_env_bool("USE_ML_SIGNAL", False)
+        self.ml_min_probability = get_env_float("ML_MIN_PROBABILITY", 0.57)
+        
+        # 리포트 플래그
+        self.morning_report_sent = False
+        self.closing_report_sent = False
+        self.final_report_sent = False
+        self.ai_report_sent = False
+        
+        # 자산 추적
+        self.today_date = dt.now().strftime("%Y-%m-%d")
+        self.start_day_asset = 0
+        self.current_total_asset = 0
+        self.current_cash = 0
+        self.d2_excc_amt = 0   # D+2 예수금 (output2 prvs_rcdl_excc_amt)
+        self.total_deposit = get_env_float("TOTAL_DEPOSIT", 0)
+        
+        # DB에서 활성 트레이드 로드
+        self.holdings = {}
+        active_trades = self.db.get_active_trades()
+        for code, trade in active_trades.items():
+            self.holdings[code] = {
+                "buy_price": trade.get("avg_buy_price", 0),
+                "qty": trade.get("current_qty", 0),
+                "buy_time": trade.get("buy_date", dt.now().strftime("%Y-%m-%d %H:%M:%S")),
+                "name": trade.get("name", code),
+            }
+        
+        # 초기 자산 조회
+        self._update_assets()
+        
+        # 비동기 태스크 관리
+        self._universe_task = None
+        self._report_task = None
+        self._asset_task = None
+        self.is_first_run = True
+        
+    def _seconds_until_next_5min(self):
+        """다음 5분 정각까지 남은 초 계산"""
+        now = dt.now()
+        next_min = ((now.minute // 5) + 1) * 5
+        if next_min >= 60:
+            next_time = now.replace(hour=now.hour + 1, minute=0, second=0, microsecond=0)
+        else:
+            next_time = now.replace(minute=next_min, second=0, microsecond=0)
+        return (next_time - now).total_seconds()
+    
+    def update_universe(self):
+        """
+        유니버스 업데이트 (5분마다 호출) - 키움 봇과 동일한 복합 스캔 로직
+        - 개미털기 우선 (원본 점수 유지)
+        - 외국인/거래량/상승률/기관 추가 (보너스 점수)
+        - 강도 순으로 정렬 → Top 30
+        """
+        logger.info(f"🔄 [유니버스 업데이트] 시작 | 예수금: {self.current_cash:,.0f}원")
+        logger.info("📡 [복합 스캔] 개미털기 우선 + 4가지 보너스 소스")
+        
+        try:
+            # 매수 가능 금액 계산
+            if self.max_stocks > 0:
+                slot_money = int(self.current_cash * 0.9 / self.max_stocks)
+            else:
+                slot_money = 100000
+            
+            all_candidates = {}  # {code: {name, price, base_score, bonus_score, total_score}}
+            
+            # 이번 스캔 주기용으로 후보 테이블 비움 (통과 시마다 add_target_candidate로 채워짐)
+            self.db.update_target_candidates([])
+            
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            # 1. 개미털기 (눌림목) - 원본 점수 100% 유지! (통과 시마다 즉시 add_target_candidate)
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            try:
+                ant_shaking = self.scan_ant_shaking_candidates(max_candidates=50)
+                logger.info(f"   ✅ [개미털기] {len(ant_shaking)}개 수집 (강도 원본 유지)")
+                for item in ant_shaking:
+                    code = item['code']
+                    all_candidates[code] = {
+                        'code': code,
+                        'name': item['name'],
+                        'price': item['price'],
+                        'base_score': item['score'],  # 개미털기 원본 점수 (100%)
+                        'bonus_score': 0.0,           # 보너스 점수 (추가)
+                        'from_ant': True,
+                        'drop_rate': item.get('drop_rate', 0),
+                        'recovery': item.get('recovery', 0),
+                    }
+            except Exception as e:
+                logger.warning(f"   ⚠️ [개미털기] 수집 실패: {e}")
+            
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            # 2. 거래량순위 - 보너스 +0.3 (순위별 가산점)
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            try:
+                volume_rank = self.client.get_volume_rank(market="J", limit=50)
+                logger.info(f"   ✅ [거래량순위] {len(volume_rank)}개 수집")
+                for idx, item in enumerate(volume_rank):
+                    code = item.get('stk_cd', '').strip() or item.get('code', '').strip()
+                    if not code or len(code) != 6:
+                        continue
+                    bonus = (50 - idx) / 50.0 * 0.3  # 순위별 보너스 (최대 +0.3)
+                    
+                    if code in all_candidates:
+                        all_candidates[code]['bonus_score'] += bonus
+                    else:
+                        # 신규 추가 (가격 확인 필요)
+                        price_data = self.client.inquire_price(code)
+                        if price_data:
+                            current_price = abs(float(price_data.get("stck_prpr", 0)))
+                            if current_price > 0 and current_price <= slot_money:
+                                all_candidates[code] = {
+                                    'code': code,
+                                    'name': item.get('stk_nm', code),
+                                    'price': current_price,
+                                    'base_score': 0.0,
+                                    'bonus_score': bonus,
+                                    'from_ant': False,
+                                }
+            except Exception as e:
+                logger.warning(f"   ⚠️ [거래량순위] 수집 실패: {e}")
+            
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            # 3. 등락률순위 (상승률) - 보너스 +0.2
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            try:
+                price_movers = self.client.get_price_change_rank(market="J", sort_type="1", limit=30)
+                logger.info(f"   ✅ [등락률순위] {len(price_movers)}개 수집")
+                for idx, item in enumerate(price_movers):
+                    code = item.get('stk_cd', '').strip() or item.get('code', '').strip()
+                    if not code or len(code) != 6:
+                        continue
+                    bonus = (30 - idx) / 30.0 * 0.2  # 순위별 보너스 (최대 +0.2)
+                    
+                    if code in all_candidates:
+                        all_candidates[code]['bonus_score'] += bonus
+                    else:
+                        price_data = self.client.inquire_price(code)
+                        if price_data:
+                            current_price = abs(float(price_data.get("stck_prpr", 0)))
+                            if current_price > 0 and current_price <= slot_money:
+                                all_candidates[code] = {
+                                    'code': code,
+                                    'name': item.get('stk_nm', code),
+                                    'price': current_price,
+                                    'base_score': 0.0,
+                                    'bonus_score': bonus,
+                                    'from_ant': False,
+                                }
+            except Exception as e:
+                logger.warning(f"   ⚠️ [등락률순위] 수집 실패: {e}")
+            
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            # 4. 거래대금순위 - 보너스 +0.2
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            try:
+                value_rank = self.client.get_trading_value_rank(market="J", limit=30)
+                logger.info(f"   ✅ [거래대금순위] {len(value_rank)}개 수집")
+                for idx, item in enumerate(value_rank):
+                    code = item.get('stk_cd', '').strip() or item.get('code', '').strip()
+                    if not code or len(code) != 6:
+                        continue
+                    bonus = (30 - idx) / 30.0 * 0.2  # 순위별 보너스 (최대 +0.2)
+                    
+                    if code in all_candidates:
+                        all_candidates[code]['bonus_score'] += bonus
+            except Exception as e:
+                logger.warning(f"   ⚠️ [거래대금순위] 수집 실패: {e}")
+            
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            # 5. 외국인/기관 순매수 - 보너스 +0.3 (투자자 동향 기반)
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            # 개미털기 후보에 대해서만 투자자 동향 확인 (API 호출 최소화)
+            investor_check_count = 0
+            for code, candidate in list(all_candidates.items()):
+                if candidate.get('from_ant') and investor_check_count < 10:  # 최대 10개만 체크
+                    try:
+                        investor_trend = self.client.get_investor_trend(code, days=2)
+                        investor_check_count += 1
+                        if investor_trend:
+                            total_net = investor_trend.get("total_net_buy", 0)
+                            if total_net > 20000:
+                                candidate['bonus_score'] += 0.3  # 강한 매수세
+                            elif total_net > 5000:
+                                candidate['bonus_score'] += 0.15  # 매수세
+                    except Exception as e:
+                        logger.debug(f"투자자 동향 조회 실패({code}): {e}")
+            
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            # 최종 점수 계산 및 정렬
+            # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+            final_candidates = []
+            for code, item in all_candidates.items():
+                total_score = item['base_score'] + item['bonus_score']
+                final_candidates.append({
+                    'code': code,
+                    'name': item['name'],
+                    'price': item['price'],
+                    'score': total_score,
+                    'base_score': item['base_score'],
+                    'bonus_score': item['bonus_score'],
+                    'from_ant': item.get('from_ant', False),
+                    'drop_rate': item.get('drop_rate', 0),
+                    'recovery': item.get('recovery', 0),
+                })
+            
+            # 강도 순 정렬 (total_score 기준)
+            final_candidates.sort(key=lambda x: x['score'], reverse=True)
+            
+            # 강도 4.0 이상만 필터링 (키움 봇과 동일)
+            filtered = [c for c in final_candidates if c['score'] >= 4.0]
+            
+            if not filtered:
+                logger.warning(f"   ⚠️ 강도 4.0 이상 후보 없음 (전체: {len(final_candidates)}개)")
+                # 강도 낮춰서라도 상위 30개 저장
+                filtered = final_candidates[:30]
+            
+            # DB 저장: 스캔 중 통과 시마다 이미 add_target_candidate()로 실시간 저장됨 → 여기서는 전체 교체 안 함
+            # 스캔 완료 후에는 정렬만 해서 로그만 찍음 (매매 루프는 DB에서 실시간으로 후보 읽음)
+            logger.info(f"   💾 매수 후보군: 스캔 중 통과 즉시 저장 완료, 최종 후보 {len(filtered)}개 (DB 반영됨, 정렬 순 로그만 출력)")
+            
+            # Top 5 상세 로그 (강도 순, 종목명 표시)
+            logger.info(f"   🔝 [유니버스 Top 5] (강도 순)")
+            
+            # Top 5 종목의 전일 대비 정보 조회 (API 문서: stck_prdy_clpr = 전일 종가)
+            def _safe_float(val):
+                if not val:
+                    return 0.0
+                try:
+                    return abs(float(str(val).replace(",", "").strip() or 0))
+                except:
+                    return 0.0
+            
+            prev_day_map = {}
+            for x in filtered[:5]:
+                code = x["code"]
+                name = x.get("name", code)
+                try:
+                    price_data = self.client.inquire_price(code)
+                    if not price_data:
+                        logger.info(f"   ⚠️ 전일대비: {name} {code} API응답없음")
+                        continue
+                    current_price = _safe_float(price_data.get("stck_prpr")) or _safe_float(x.get("price", 0))
+                    prev_close = _safe_float(price_data.get("stck_prdy_clpr"))  # API 문서 필드명 그대로 사용
+                    if prev_close <= 0:  # 없으면 일봉에서 전일 close
+                        df_daily = self.client.get_daily_chart(code, limit=3)
+                        if not df_daily.empty and len(df_daily) >= 2:
+                            prev_close = _safe_float(df_daily["close"].iloc[-2])
+                            logger.info(f"   📊 전일대비: {name} {code} 일봉에서 전일종가 조회 성공 ({prev_close:,.0f}원)")
+                        else:
+                            logger.info(f"   ⚠️ 전일대비: {name} {code} 일봉데이터없음 (len={len(df_daily) if not df_daily.empty else 0})")
+                    if prev_close > 0 and current_price > 0:
+                        change = current_price - prev_close
+                        change_pct = (change / prev_close) * 100
+                        prev_day_map[code] = (change, change_pct)
+                    else:
+                        logger.info(f"   ⚠️ 전일대비: {name} {code} prev_close={prev_close}, current={current_price}")
+                    time.sleep(random.uniform(0.2, 0.3))
+                except Exception as e:
+                    logger.warning(f"   ⚠️ 전일대비 조회 실패({name} {code}): {e}")
+            
+            for i, x in enumerate(filtered[:5], 1):
+                base = x.get('base_score', 0)
+                bonus = x.get('bonus_score', 0)
+                total = x['score']
+                drop_pct = x.get('drop_rate', 0) * 100
+                recovery_pct = x.get('recovery', 0) * 100
+                if x.get('from_ant'):
+                    source = "개미털기"
+                else:
+                    source = "랭킹"
+                if x.get('ml_probability'):
+                    ml_info = f" | ML {x.get('ml_probability', 0):.1%}"
+                else:
+                    ml_info = ""
+                
+                # 전일 대비 등락률 표시
+                prev_day_info = ""
+                code = x['code']
+                if code in prev_day_map:
+                    change, change_pct = prev_day_map[code]
+                    sign = "+" if change >= 0 else ""
+                    prev_day_info = f" | 어제보다 {sign}{change:,.0f}원 ({sign}{change_pct:.2f}%)"
+                
+                logger.info(
+                    f"      {i}. {x['name']} {x['code']}: "
+                    f"강도 {total:.1f} (기본 {base:.1f} + 보너스 {bonus:.1f}) | "
+                    f"낙폭 {drop_pct:.1f}% | 회복 {recovery_pct:.0f}% | {source}{ml_info}{prev_day_info}"
+                )
+            
+            logger.info(f"   ✅ 최종 후보: {len(filtered)}개 (강도 4.0 이상: {len([c for c in final_candidates if c['score'] >= 4.0])}개)")
+            
+        except Exception as e:
+            logger.error(f"❌ 유니버스 업데이트 실패: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+    
+    async def _universe_scan_scheduler(self):
+        """5분마다 정각에 유니버스 스캔 실행 (비동기 백그라운드)"""
+        loop = asyncio.get_event_loop()
+        while True:
+            try:
+                if self.is_first_run:
+                    wait_sec = 0  # 첫 실행은 즉시
+                else:
+                    wait_sec = max(0, self._seconds_until_next_5min())
+                if wait_sec > 0:
+                    await asyncio.sleep(wait_sec)
+                now = dt.now()
+                logger.info(f"🔄 [스캔 주기] 정각 스캔 시작 | 시각:{now.hour:02d}:{now.minute:02d}:{now.second:02d}")
+                # 동기 함수를 executor에서 실행 (메인 루프 블로킹 방지)
+                await loop.run_in_executor(None, self.update_universe)
+                self.is_first_run = False
+                await asyncio.sleep(5)  # 스캔 직후 5초 대기 (과부하 방지)
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.error(f"❌ [스캔 스케줄러] 에러: {e}")
+                await asyncio.sleep(60)
+    
+    async def _report_scheduler(self):
+        """리포트 전송 스케줄러 (비동기 백그라운드)"""
+        while True:
+            try:
+                await asyncio.sleep(60)  # 1분마다 체크
+                now = dt.now()
+                
+                # 13:00 - 오전 리포트 + AI 리포트
+                if now.hour == 13 and now.minute == 0 and not self.morning_report_sent:
+                    loop = asyncio.get_event_loop()
+                    await loop.run_in_executor(None, self.send_morning_report)
+                    await loop.run_in_executor(None, self.send_ai_report)
+                
+                # 15:15 - 장마감 전 리포트
+                elif now.hour == 15 and now.minute == 15 and not self.closing_report_sent:
+                    loop = asyncio.get_event_loop()
+                    await loop.run_in_executor(None, self.send_closing_report)
+                
+                # 15:35 - 최종 리포트
+                elif now.hour == 15 and now.minute == 35 and not self.final_report_sent:
+                    loop = asyncio.get_event_loop()
+                    await loop.run_in_executor(None, self.send_final_report)
+                
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.error(f"❌ [리포트 스케줄러] 에러: {e}")
+                await asyncio.sleep(60)
+    
+    async def _asset_update_scheduler(self):
+        """자산 정보 업데이트 스케줄러 (30분마다, 비동기 백그라운드)"""
+        while True:
+            try:
+                await asyncio.sleep(60)  # 1분마다 체크
+                now = dt.now()
+                
+                # 30분마다 자산 업데이트
+                if now.minute % 30 == 0:
+                    loop = asyncio.get_event_loop()
+                    await loop.run_in_executor(None, self._update_assets)
+                    await asyncio.sleep(60)  # 업데이트 후 1분 대기 (중복 방지)
+                
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.error(f"❌ [자산 업데이트 스케줄러] 에러: {e}")
+                await asyncio.sleep(60)
+        
+    def _update_assets(self):
+        """자산 정보 업데이트"""
+        try:
+            balance = self.client.get_account_balance()
+            if balance is None:
+                logger.warning(
+                    "💵 [예수금] get_account_balance가 None 반환 → 예수금 갱신 스킵 "
+                    "(토큰·계좌·TR ID 확인. 모의=VTTC8434R, 실전=TTTC8434R)"
+                )
+                return
+            # 한투 API: output1=주식 잔고(종목별), output2=예수금 관련(dnca_tot_amt 등) - 블로그·문서 기준
+            def _parse_amt(v):
+                if v is None or str(v).strip() == "":
+                    return None
+                return float(str(v).replace(",", "").strip())
+            def _cash_block(obj):
+                if not obj:
+                    return {}
+                if isinstance(obj, list) and obj:
+                    return obj[0]
+                if isinstance(obj, dict):
+                    return obj
+                return {}
+            out2 = _cash_block(balance.get("output2"))
+            if isinstance(balance.get("output1"), dict):
+                out1 = balance.get("output1", {})
+            else:
+                out1 = {}
+            ord_psbl_val = _parse_amt(out2.get("ord_psbl_cash") or out1.get("ord_psbl_cash"))
+            dnca_tot_val = _parse_amt(out2.get("dnca_tot_amt") or out1.get("dnca_tot_amt")) or 0
+            # D+2 예수금 (전일 정산 수령 예정 금액) - 한투 output2 prvs_rcdl_excc_amt
+            prvs_rcdl = _parse_amt(out2.get("prvs_rcdl_excc_amt"))
+            if prvs_rcdl is not None:
+                self.d2_excc_amt = prvs_rcdl
+            else:
+                self.d2_excc_amt = 0
+            if ord_psbl_val is not None:
+                self.current_cash = ord_psbl_val
+                logger.info(
+                    f"💵 [예수금] 주문가능(ord_psbl_cash)={self.current_cash:,.0f}원 | "
+                    f"dnca_tot_amt={dnca_tot_val:,.0f} | D+2예수금(prvs_rcdl_excc_amt)={self.d2_excc_amt:,.0f}원"
+                )
+            else:
+                self.current_cash = dnca_tot_val
+                logger.info(
+                    f"💵 [예수금] dnca_tot_amt={self.current_cash:,.0f}원 | "
+                    f"D+2예수금(prvs_rcdl_excc_amt)={self.d2_excc_amt:,.0f}원 (output2 keys={list(out2.keys()) if out2 else []})"
+                )
+            # 보유 종목 평가액 계산
+            holdings_value = 0
+            for code, holding in self.holdings.items():
+                price_data = self.client.inquire_price(code)
+                if price_data:
+                    current_price = abs(float(price_data.get("stck_prpr", 0)))
+                    holdings_value += current_price * holding["qty"]
+            self.current_total_asset = self.current_cash + holdings_value
+            if self.start_day_asset == 0:
+                self.start_day_asset = self.current_total_asset
+        except Exception as e:
+            logger.error(f"자산 정보 업데이트 실패: {e}")
+    
+    def _update_account_light(self, profit_val=0):
+        """
+        경량 계좌 갱신 (매수/매도 직후 즉시 호출!)
+        - API 부하를 줄이기 위해 예수금 + 보유 종목 평가액만 빠르게 계산
+        - 총자산 = 예수금 + 보유 종목 평가액 (+ 손익 반영)
+        """
+        try:
+            balance = self.client.get_account_balance()
+            if balance is None:
+                logger.warning("💵 [예수금-경량] get_account_balance None → 예수금 갱신 스킵")
+                return False
+            def _parse_amt_light(v):
+                if v is None or str(v).strip() == "":
+                    return None
+                return float(str(v).replace(",", "").strip())
+            def _cash_block_light(obj):
+                if not obj:
+                    return {}
+                if isinstance(obj, list) and obj:
+                    return obj[0]
+                if isinstance(obj, dict):
+                    return obj
+                return {}
+            out2 = _cash_block_light(balance.get("output2"))
+            if isinstance(balance.get("output1"), dict):
+                out1 = balance.get("output1", {})
+            else:
+                out1 = {}
+            ord_psbl_val = _parse_amt_light(out2.get("ord_psbl_cash") or out1.get("ord_psbl_cash"))
+            dnca_tot_val = _parse_amt_light(out2.get("dnca_tot_amt") or out1.get("dnca_tot_amt")) or 0
+            prvs_rcdl = _parse_amt_light(out2.get("prvs_rcdl_excc_amt"))
+            if prvs_rcdl is not None:
+                self.d2_excc_amt = prvs_rcdl
+            if ord_psbl_val is not None:
+                new_cash = ord_psbl_val
+            else:
+                new_cash = dnca_tot_val
+            logger.info(
+                f"💵 [예수금-경량] 주문가능={new_cash:,.0f}원 (이전={self.current_cash:,.0f}) | D+2예수금={self.d2_excc_amt:,.0f}원"
+            )
+            if new_cash > 0 or self.current_cash == 0:
+                self.current_cash = new_cash
+            # 보유 종목 평가액: output1=주식 잔고(종목별), output2=예수금 요약 (블로그 기준)
+            output1_list = balance.get("output1", [])
+            if isinstance(output1_list, dict):
+                output1_list = [output1_list]
+            holdings_value = 0
+            for code, holding in self.holdings.items():
+                for item in output1_list:
+                    if (item.get("pdno") or "").strip() == code:
+                        evlu_amt = float(item.get("evlu_amt", 0))
+                        holdings_value += evlu_amt
+                        break
+                else:
+                    price_data = self.client.inquire_price(code)
+                    if price_data:
+                        current_price = abs(float(price_data.get("stck_prpr", 0)))
+                        holdings_value += current_price * holding["qty"]
+            self.current_total_asset = self.current_cash + holdings_value
+            if profit_val != 0:
+                self.current_total_asset += profit_val
+            logger.debug(f"💵 [경량갱신] 예수금: {self.current_cash:,.0f}원 | 총자산: {self.current_total_asset:,.0f}원")
+            return True
+        except Exception as e:
+            logger.error(f"❌ 경량 갱신 실패: {e}")
+        return False
+    
+    def _update_cash_only(self):
+        """예수금만 빠르게 업데이트 (하위 호환성용, _update_account_light 사용 권장)"""
+        return self._update_account_light(profit_val=0)
+    
+    def send_mm(self, msg):
+        """Mattermost 알림 전송"""
+        try:
+            self.mm.send(self.mm_channel, msg)
+        except Exception as e:
+            logger.error(f"❌ MM 전송 에러: {e}")
+    
+    def check_market_status(self):
+        """장 운영 시간 체크"""
+        # FORCE_MARKET_OPEN 플래그 확인 (테스트용)
+        force_open = get_env_bool("FORCE_MARKET_OPEN", False)
+        if force_open:
+            logger.debug("🔓 FORCE_MARKET_OPEN=true - 장 상태 무시하고 계속 진행")
+            return True
+        
+        # 정상 장 운영 시간 체크
+        now = dt.now()
+        if not (datetime.time(8, 30) <= now.time() <= datetime.time(16, 0)):
+            return False
+        if now.weekday() >= 5:  # 주말
+            return False
+        return True
+    
+    def send_morning_report(self):
+        """오전 장 뜸할 때 리포트 (13:00)"""
+        if self.morning_report_sent:
+            return
+        
+        self._update_assets()
+        day_pnl = self.current_total_asset - self.start_day_asset
+        if self.start_day_asset > 0:
+            day_pnl_pct = day_pnl / self.start_day_asset * 100
+        else:
+            day_pnl_pct = 0
+        
+        msg = f"""📊 **[오전 장 현황 - 13:00]**
+- 당일 시작: {self.start_day_asset:,.0f}원
+- 현재 자산: {self.current_total_asset:,.0f}원
+- 당일 손익: {day_pnl:+,.0f}원 ({day_pnl_pct:+.2f}%)
+- 보유 종목: {len(self.holdings)}개"""
+        
+        self.send_mm(msg)
+        self.morning_report_sent = True
+        logger.info("📊 오전 리포트 전송 완료")
+    
+    def send_closing_report(self):
+        """장마감 전 리포트 (15:15)"""
+        if self.closing_report_sent:
+            return
+        
+        self._update_assets()
+        day_pnl = self.current_total_asset - self.start_day_asset
+        if self.start_day_asset > 0:
+            day_pnl_pct = day_pnl / self.start_day_asset * 100
+        else:
+            day_pnl_pct = 0
+        
+        msg = f"""📈 **[장마감 전 현황 - 15:15]**
+- 당일 손익: {day_pnl:+,.0f}원 ({day_pnl_pct:+.2f}%)
+- 현재 자산: {self.current_total_asset:,.0f}원
+- 보유 종목: {len(self.holdings)}개
+- 예수금(주문가능): {self.current_cash:,.0f}원 | D+2예수금: {self.d2_excc_amt:,.0f}원"""
+        
+        self.send_mm(msg)
+        self.closing_report_sent = True
+        logger.info("📈 장마감 전 리포트 전송 완료")
+    
+    def send_final_report(self):
+        """장마감 후 최종 리포트 (15:35)"""
+        if self.final_report_sent:
+            return
+        
+        self._update_assets()
+        
+        # 당일 손익
+        day_pnl = self.current_total_asset - self.start_day_asset
+        if self.start_day_asset > 0:
+            day_pnl_pct = day_pnl / self.start_day_asset * 100
+        else:
+            day_pnl_pct = 0
+        
+        # 누적 손익
+        cumulative_pnl = self.current_total_asset - self.total_deposit
+        if self.total_deposit > 0:
+            cumulative_pnl_pct = cumulative_pnl / self.total_deposit * 100
+        else:
+            cumulative_pnl_pct = 0
+        
+        # 오늘 거래 내역
+        today_trades = self.db.get_trades_by_date(self.today_date)
+        
+        msg = f"""🏁 **[장마감 최종 보고 - 15:35]**
+━━━━━━━━━━━━━━━━━━━━
+📅 **당일 손익**
+- 시작: {self.start_day_asset:,.0f}원
+- 종료: {self.current_total_asset:,.0f}원
+- 손익: {day_pnl:+,.0f}원 ({day_pnl_pct:+.2f}%)
+
+💰 **누적 손익 (총 입금액 대비)**
+- 총 입금: {self.total_deposit:,.0f}원
+- 현재 자산: {self.current_total_asset:,.0f}원
+- 누적 손익: {cumulative_pnl:+,.0f}원 ({cumulative_pnl_pct:+.2f}%)
+
+📊 **거래 현황**
+- 오늘 매매: {len(today_trades)}건
+- 보유 종목: {len(self.holdings)}개
+- 예수금(주문가능): {self.current_cash:,.0f}원 | D+2예수금: {self.d2_excc_amt:,.0f}원
+━━━━━━━━━━━━━━━━━━━━"""
+        
+        self.send_mm(msg)
+        self.final_report_sent = True
+        logger.info("🏁 장마감 최종 리포트 전송 완료")
+    
+    def send_ai_report(self):
+        """AI 분석 리포트 (13:00)"""
+        if self.ai_report_sent or not gemini_client:
+            return
+        
+        try:
+            # 최근 거래 내역 조회
+            recent_trades = []
+            try:
+                conn = self.db.conn
+                cursor = conn.execute("""
+                    SELECT code, name, buy_price, sell_price, qty, profit_rate, 
+                           realized_pnl, strategy, sell_reason, buy_date, sell_date, hold_minutes
+                    FROM trade_history
+                    ORDER BY id DESC
+                    LIMIT 10
+                """)
+                for row in cursor.fetchall():
+                    recent_trades.append({
+                        'code': row[0],
+                        'name': row[1],
+                        'buy_price': row[2],
+                        'sell_price': row[3],
+                        'qty': row[4],
+                        'profit_rate': row[5],
+                        'realized_pnl': row[6],
+                        'strategy': row[7],
+                        'sell_reason': row[8],
+                        'buy_date': row[9],
+                        'sell_date': row[10],
+                        'hold_minutes': row[11] or 0
+                    })
+            except Exception as e:
+                logger.error(f"거래 내역 조회 실패: {e}")
+                return
+            
+            # 현재 유니버스 상태
+            db_candidates = self.db.get_target_candidates()
+            candidate_count = len(db_candidates)
+            
+            # 거래 내역이 없어도 유니버스 상태는 리포트에 포함
+            if not recent_trades:
+                # 거래 내역 없을 때도 유니버스 상태 리포트
+                summary = f"""📊 **현재 상태**
+- 유니버스 후보: {candidate_count}개
+- 최근 거래: 없음"""
+                
+                prompt = f"""당신은 퀀트 트레이딩 전문가입니다.
+
+**현재 상태:**
+- 유니버스 후보: {candidate_count}개
+- 최근 거래: 없음
+
+**현재 설정값:**
+- 최대 보유: {self.max_stocks}개
+- 최소 낙폭: {self.min_drop_rate*100:.1f}%
+- 최소 회복률: {self.min_recovery_ratio*100:.0f}%
+- ML 사용: {self.use_ml_signal}
+- ML 최소 승률: {self.ml_min_probability:.1%}
+
+**당신의 임무:**
+1. 후보가 {candidate_count}개인 이유 분석 (필터 조건이 너무 까다로운지 등)
+2. **수치 추천** (변수명=값 형식, 정확한 숫자 제시)
+   - 예: MIN_DROP_RATE=0.025 (2.5%)
+   - 예: MIN_RECOVERY_RATIO=0.40 (40%)
+3. 예상 효과
+
+**출력 형식:**
+## 🔍 문제점
+1. [구체적 문제 1]
+2. [구체적 문제 2]
+
+## 💡 수치 추천 (DB 설정 변경)
+- 변수명1=값1 (이유: ...)
+- 변수명2=값2 (이유: ...)
+
+## 📈 예상 효과
+- [효과 1]
+- [효과 2]
+"""
+                
+                response = gemini_client.models.generate_content(model=GEMINI_MODEL_ID, contents=prompt)
+                analysis = getattr(response, "text", None) or (response.candidates[0].content.parts[0].text if response.candidates else "")
+                
+                message = f"""🤖 **[13시 AI 자동 분석 + 수치 추천]**
+
+{summary}
+
+{analysis}
+
+---
+💬 단타 전략 최적화를 위한 AI 분석입니다. (수치 추천 포함)
+"""
+                
+                self.send_mm(message)
+                self.ai_report_sent = True
+                logger.info("🤖 AI 리포트 전송 완료 (거래 내역 없음, 유니버스 상태 포함)")
+                return
+            
+            # 통계 계산
+            total = len(recent_trades)
+            wins = sum(1 for t in recent_trades if t['profit_rate'] > 0)
+            losses = total - wins
+            if total > 0:
+                win_rate = wins / total * 100
+            else:
+                win_rate = 0
+            avg_profit = sum(t['profit_rate'] for t in recent_trades) / total
+            total_pnl = sum(t['realized_pnl'] for t in recent_trades)
+            avg_hold = sum(t['hold_minutes'] for t in recent_trades) / total
+            
+            # AI 분석
+            trades_text = ""
+            for i, t in enumerate(recent_trades, 1):
+                trades_text += f"""
+[거래 {i}] {t['name']} ({t['strategy']})
+- 매수: {t['buy_price']:,.0f}원 × {t['qty']}주
+- 매도: {t['sell_price']:,.0f}원
+- 손익: {t['profit_rate']:+.2f}% ({t['realized_pnl']:,.0f}원)
+- 보유: {t['hold_minutes']}분
+- 사유: {t['sell_reason']}
+"""
+            
+            # 현재 유니버스 상태
+            db_candidates = self.db.get_target_candidates()
+            candidate_count = len(db_candidates)
+            
+            prompt = f"""당신은 퀀트 트레이딩 전문가입니다.
+
+**현재 상태:**
+- 유니버스 후보: {candidate_count}개
+- 최근 거래: {total}건
+- 승률: {win_rate:.1f}% ({wins}승 {losses}패)
+- 평균 수익률: {avg_profit:.2f}%
+- 총 손익: {total_pnl:,.0f}원
+- 평균 보유: {avg_hold:.0f}분
+
+**최근 거래 내역:**
+{trades_text}
+
+**현재 설정값:**
+- 최대 보유: {self.max_stocks}개
+- 최소 낙폭: {self.min_drop_rate*100:.1f}%
+- 최소 회복률: {self.min_recovery_ratio*100:.0f}%
+- ML 사용: {self.use_ml_signal}
+- ML 최소 승률: {self.ml_min_probability:.1%}
+
+**당신의 임무:**
+1. 문제점 3가지 진단 (구체적으로)
+   - 특히 후보가 {candidate_count}개인 이유 분석
+2. **수치 추천** (변수명=값 형식, 정확한 숫자 제시)
+   - 예: MIN_DROP_RATE=0.025 (2.5%)
+   - 예: MIN_RECOVERY_RATIO=0.40 (40%)
+   - 예: MAX_STOCKS=5
+3. 예상 효과
+
+**출력 형식:**
+## 🔍 문제점
+1. [구체적 문제 1]
+2. [구체적 문제 2]
+3. [구체적 문제 3]
+
+## 💡 수치 추천 (DB 설정 변경)
+- 변수명1=값1 (이유: ...)
+- 변수명2=값2 (이유: ...)
+
+## 📈 예상 효과
+- [효과 1]
+- [효과 2]
+
+**간결하고 명확하게 답변하세요.**
+"""
+            
+            response = gemini_client.models.generate_content(model=GEMINI_MODEL_ID, contents=prompt)
+            analysis = getattr(response, "text", None) or (response.candidates[0].content.parts[0].text if response.candidates else "")
+            
+            summary = f"""📊 **현재 상태**
+- 유니버스 후보: {candidate_count}개
+- 최근 거래: {total}건
+- 승률: {win_rate:.1f}% ({wins}승 {losses}패)
+- 평균 수익률: {avg_profit:.2f}%
+- 총 손익: {total_pnl:+,.0f}원
+- 평균 보유: {avg_hold:.0f}분"""
+            
+            message = f"""🤖 **[13시 AI 자동 분석 + 수치 추천]**
+
+{summary}
+
+{analysis}
+
+---
+💬 단타 전략 최적화를 위한 AI 분석입니다. (수치 추천 포함)
+"""
+            
+            self.send_mm(message)
+            self.ai_report_sent = True
+            logger.info("🤖 AI 리포트 전송 완료")
+            
+        except Exception as e:
+            logger.error(f"AI 리포트 생성 실패: {e}")
+
+    def _fetch_scan_universe_from_api(self, max_codes=500):
+        """
+        KIS API로 스캔 대상 종목 리스트 조회 (6소스 각 100건 → 최대 500개).
+        - 거래량·거래대금·회전율·등락률(상승)·등락률(하락)·거래증가율 각 100건 합산 후 중복 제거.
+        - 리스트는 DB에 저장하지 않음. 스캔 끝난 뒤 후보만 DB에 한 번에 인서트.
+        Returns:
+            list[dict]: [{"code": "006자리", "name": "종목명"}, ...] (중복 제거, 최대 max_codes개)
+        """
+        def _code_from_item(item):
+            code = (item.get("stk_cd") or item.get("mksc_shrn_iscd") or item.get("code") or "").strip()
+            return code if code and len(code) == 6 else None
+
+        def _name_from_item(item):
+            return (
+                (item.get("stk_nm") or item.get("prst_name") or item.get("hts_kor_isnm") or "").strip()
+                or ""
+            )
+
+        scan_list = []
+        seen = set()
+
+        # 1) 거래량순위 100개 (키움은 거래대금+회전율만 사용, KIS는 거래량+거래대금+회전율 3가지로 풀 확대)
+        try:
+            time.sleep(random.uniform(0.5, 1.0))
+            vol_list = self.client.get_volume_rank(market="J", limit=100)
+            for item in (vol_list or []):
+                c = _code_from_item(item)
+                if c and c not in seen:
+                    seen.add(c)
+                    scan_list.append({"code": c, "name": _name_from_item(item) or ""})
+            logger.info(f"   📡 [스캔유니버스] 거래량순위 API → {len(vol_list)}건 수신, 누적 {len(scan_list)}종목")
+        except Exception as e:
+            logger.warning(f"   ⚠️ [스캔유니버스] 거래량순위 조회 실패: {e}")
+
+        # 2) 거래대금순위 100개 (키움과 동일 소스)
+        try:
+            time.sleep(random.uniform(0.5, 1.0))
+            val_list = self.client.get_trading_value_rank(market="J", limit=100)
+            for item in (val_list or []):
+                c = _code_from_item(item)
+                if c and c not in seen:
+                    seen.add(c)
+                    scan_list.append({"code": c, "name": _name_from_item(item) or ""})
+            logger.info(f"   📡 [스캔유니버스] 거래대금순위 API → {len(val_list)}건 수신, 누적 {len(scan_list)}종목")
+        except Exception as e:
+            logger.warning(f"   ⚠️ [스캔유니버스] 거래대금순위 조회 실패: {e}")
+
+        # 3) 회전율순위 100개 (키움 개미털기 2번째 소스와 동일)
+        try:
+            time.sleep(random.uniform(0.5, 1.0))
+            turn_list = self.client.get_turnover_rank(market="J", limit=100)
+            for item in (turn_list or []):
+                c = _code_from_item(item)
+                if c and c not in seen:
+                    seen.add(c)
+                    scan_list.append({"code": c, "name": _name_from_item(item) or ""})
+            logger.info(f"   📡 [스캔유니버스] 회전율순위 API → {len(turn_list)}건 수신, 누적 {len(scan_list)}종목")
+        except Exception as e:
+            logger.warning(f"   ⚠️ [스캔유니버스] 회전율순위 조회 실패: {e}")
+
+        # 4) 등락률순위(상승) 100개 (기존 후보군 풀 확대)
+        try:
+            time.sleep(random.uniform(0.5, 1.0))
+            chg_list = self.client.get_price_change_rank(market="J", sort_type="1", limit=100)
+            for item in (chg_list or []):
+                c = _code_from_item(item)
+                if c and c not in seen:
+                    seen.add(c)
+                    scan_list.append({"code": c, "name": _name_from_item(item) or ""})
+            logger.info(f"   📡 [스캔유니버스] 등락률순위(상승) API → {len(chg_list)}건 수신, 누적 {len(scan_list)}종목")
+        except Exception as e:
+            logger.warning(f"   ⚠️ [스캔유니버스] 등락률순위(상승) 조회 실패: {e}")
+
+        # 4-2) 등락률순위(하락) 100개 — 낙폭 큰 종목 직접 조회 → N자 망치봉 스캔 효율·Pass-낙폭 포착
+        try:
+            time.sleep(random.uniform(0.5, 1.0))
+            decline_list = self.client.get_price_decline_rank(market="J", limit=100)
+            for item in (decline_list or []):
+                c = _code_from_item(item)
+                if c and c not in seen:
+                    seen.add(c)
+                    scan_list.append({"code": c, "name": _name_from_item(item) or ""})
+            logger.info(f"   📡 [스캔유니버스] 등락률순위(하락) API → {len(decline_list)}건 수신, 누적 {len(scan_list)}종목")
+        except Exception as e:
+            logger.warning(f"   ⚠️ [스캔유니버스] 등락률순위(하락) 조회 실패: {e}")
+
+        # 5) 거래증가율순위 100개 (거래량/대금/회전율과 다른 풀 → 후보 다양화)
+        try:
+            time.sleep(random.uniform(0.5, 1.0))
+            growth_list = self.client.get_volume_growth_rank(market="J", limit=100)
+            for item in (growth_list or []):
+                c = _code_from_item(item)
+                if c and c not in seen:
+                    seen.add(c)
+                    scan_list.append({"code": c, "name": _name_from_item(item) or ""})
+            logger.info(f"   📡 [스캔유니버스] 거래증가율순위 API → {len(growth_list)}건 수신, 누적 {len(scan_list)}종목 (6소스 합산 → 개미털기 필터)")
+        except Exception as e:
+            logger.warning(f"   ⚠️ [스캔유니버스] 거래증가율순위 조회 실패: {e}")
+
+        if not scan_list:
+            logger.warning("   ⚠️ [스캔유니버스] API에서 0건 수신 → 스캔 불가 (권한/계정/시간 확인)")
+            return []
+
+        scan_list = scan_list[:max_codes]
+        # 종목명 비어 있으면 시세 배치로 채우기 (KIS volume-rank는 종목명 미제공 시 많음)
+        need_name_codes = [x["code"] for x in scan_list[:20] if not (x.get("name") or "").strip()]
+        if need_name_codes:
+            try:
+                time.sleep(random.uniform(0.2, 0.4))
+                batch = self.client.inquire_prices_batch(need_name_codes[:20])
+                name_map = {}
+                _market_names = {"KOSPI", "KOSDAQ", "ETF", "KOSPI200", "KSQ150"}
+                for code, out in (batch or {}).items():
+                    n = (out.get("stck_kor_isnm") or out.get("rprs_mrkt_kor_name") or "").strip()
+                    if n and n not in _market_names:
+                        name_map[code] = n
+                for x in scan_list:
+                    if not (x.get("name") or "").strip() and x["code"] in name_map:
+                        x["name"] = name_map[x["code"]]
+            except Exception as e:
+                logger.debug(f"   스캔 종목명 배치 조회 스킵: {e}")
+        for x in scan_list:
+            if not (x.get("name") or "").strip():
+                x["name"] = x["code"]
+
+        logger.info(
+            f"   📋 스캔 대상: {len(scan_list)}개 종목 (거래량·거래대금·회전율·등락률상승·등락률하락·거래증가율 각 100건 합산 → 개미털기 필터)"
+        )
+        if scan_list:
+            part = ", ".join(f"{x['code']} {x.get('name') or x['code']}" for x in scan_list[:15])
+            logger.info(f"   📋 스캔 대상(일부): {part}{' ...' if len(scan_list) > 15 else ''}")
+        return scan_list
+
+    def scan_ant_shaking_candidates(self, max_candidates=20):
+        """개미털기(눌림목) 후보 종목 스캔 - KIS API로 스캔 대상 조회 후 필터링"""
+        logger.info("🐜 [개미털기] 고급 스캔 시작 (KIS API 스캔유니버스 사용)")
+        logger.info(
+            "   📌 스캔 대상 리스트는 DB에 저장되지 않음. "
+            "수치 체크(낙폭/회복률 등)는 이 리스트를 순회하며 개미털기 전략 필터를 적용한 결과입니다."
+        )
+        candidates = []
+        seen_codes = set()
+        # 필터별 탈락 건수 (0개 나오는 이유 확인용) - 세분화
+        filter_counts = {
+            "낙폭부족": 0,
+            "회복률부족": 0,
+            "피뢰침(고점근접)": 0,
+            "피뢰침(급등주)": 0,
+            "RSI과열": 0,
+            "MA20": 0,
+            "API응답없음": 0,
+            "API예외": 0,
+            "시가0": 0,
+            "동전주": 0,
+            "가격파싱오류": 0,
+        }
+
+        scan_list = self._fetch_scan_universe_from_api(max_codes=500)
+        scan_codes = [x["code"] for x in scan_list]
+        # scan_list를 딕셔너리로 변환하여 코드로 종목명을 빠르게 찾을 수 있게 함
+        scan_name_map = {x["code"]: x.get("name", "") for x in scan_list}
+        if not scan_codes:
+            logger.warning("   ⚠️ [개미털기] 스캔 대상 0개 → 스캔 생략 (API에서 종목 리스트를 받지 못함)")
+            return []
+
+        # 스캔 대상 리스트를 거래량/낙폭 체크 전에 한 번 출력 (종목명 · 코드)
+        # 참고: 위 [스캔유니버스] 6소스(거래량·거래대금·회전율·등락률상승·등락률하락·거래증가율) 합산 → 동일 개미털기 필터 적용
+        logger.info(f"   📋 [개미털기 스캔 대상] {len(scan_list)}개 (6소스 합산, 종목명 · 코드)")
+        for i, x in enumerate(scan_list):
+            logger.info(f"      {i+1}. {x.get('name') or x['code']}  {x['code']}")
+
+        # 체결강도 상위 API(FHPST01710000) 1회 조회 → 통과 종목 보너스(100 이상 +10, 120 이상 +20) 적용용
+        execution_strength_map = {}
+        try:
+            time.sleep(random.uniform(0.3, 0.6))
+            execution_strength_map = self.client.get_execution_strength_map(market="J", limit=200)
+            if execution_strength_map:
+                logger.info(f"   📡 [체결강도] 상위 {len(execution_strength_map)}종목 로드 (통과 시 100+ → +10점, 120+ → +20점)")
+        except Exception as e:
+            logger.debug(f"체결강도 맵 로드 스킵: {e}")
+
+        # 순차 조회 (한투 API는 다중 종목 조회 미지원 - 순차 조회 필수)
+        # 규칙: 일반 루프에는 random.sleep(1~3) 기본 적용 (서버 부하 방지)
+        total_scanned = 0
+        passed_filters = 0
+        
+        for code in scan_codes:
+            total_scanned += 1
+            if code in seen_codes:
+                continue
+            seen_codes.add(code)
+            
+            try:
+                # 순차 조회 (종목당 1회 API 호출)
+                price_data = self.client.inquire_price(code)
+                if not price_data:
+                    filter_counts["API응답없음"] += 1
+                    if code == "001510":  # SK증권 추적
+                        logger.warning(f"   ⚠️ SK증권(001510) API응답없음 (상세는 위 [현재가API] 로그 참고)")
+                    time.sleep(random.uniform(1.0, 2.0))
+                    continue
+                time.sleep(random.uniform(1.0, 2.0))
+                
+                # 가격 데이터 파싱
+                try:
+                    current_price = abs(float(str(price_data.get("stck_prpr", 0)).replace(",", "")))
+                    open_price = abs(float(str(price_data.get("stck_oprc", current_price)).replace(",", "")))
+                    high_price = abs(float(str(price_data.get("stck_hgpr", current_price)).replace(",", "")))
+                    low_price = abs(float(str(price_data.get("stck_lwpr", current_price)).replace(",", "")))
+                    volume = int(float(str(price_data.get("acml_vol", 0)).replace(",", "")))
+                except (ValueError, TypeError) as e:
+                    filter_counts["가격파싱오류"] += 1
+                    logger.debug(f"가격 파싱 실패({code}): {e}")
+                    continue
+                
+                if open_price == 0:
+                    filter_counts["시가0"] += 1
+                    continue
+                if current_price < 1000:  # 동전주 제외
+                    filter_counts["동전주"] += 1
+                    continue
+                
+                # 종목명 가져오기: 시장명(KOSPI/KOSDAQ 등)이 아닌 진짜 종목명만 사용
+                # KIS API는 rprs_mrkt_kor_name에 시장구분을 넣는 경우가 있어, stck_kor_isnm(종목한글명) 우선 사용
+                _MARKET_NAMES = {"KOSPI", "KOSDAQ", "ETF", "KOSPI200", "KSQ150"}
+                name = scan_name_map.get(code, "").strip()
+                if not name or name in _MARKET_NAMES:
+                    name = (price_data.get("stck_kor_isnm") or price_data.get("rprs_mrkt_kor_name") or "").strip()
+                if not name or name in _MARKET_NAMES:
+                    name = code
+                
+                # 낙폭 계산
+                if open_price > 0:
+                    drop_rate = (open_price - low_price) / open_price
+                else:
+                    drop_rate = 0
+                total_range = high_price - low_price
+                if total_range > 0:
+                    recovery_pos = (current_price - low_price) / total_range
+                else:
+                    recovery_pos = 0
+                
+                # 필터 조건 수치 로그 (디버깅용)
+                logger.debug(
+                    f"   📊 [{name} {code}] 수치: "
+                    f"낙폭 {drop_rate*100:.2f}% (기준: {self.min_drop_rate*100:.1f}%) | "
+                    f"회복 {recovery_pos*100:.1f}% (기준: {self.min_recovery_ratio*100:.0f}%) | "
+                    f"고점 {high_price:,.0f}원 | 저점 {low_price:,.0f}원 | 현재 {current_price:,.0f}원"
+                )
+                
+                # [필터 1] 낙폭 체크
+                if drop_rate < self.min_drop_rate:
+                    filter_counts["낙폭부족"] += 1
+                    logger.info(
+                        f"{LOG_YELLOW}🔍 [탈락-낙폭] {name} {code}: 낙폭 {drop_rate*100:.2f}% < {self.min_drop_rate*100:.1f}% "
+                        f"(시가 {open_price:,.0f}원 → 저점 {low_price:,.0f}원){LOG_RESET}"
+                    )
+                    if code == "001510":  # SK증권 추적
+                        logger.warning(f"   ⚠️ SK증권(001510) 낙폭부족으로 탈락: 낙폭={drop_rate*100:.2f}%, 기준={self.min_drop_rate*100:.1f}%")
+                    continue
+                
+                # [필터 2] 회복률 체크
+                if recovery_pos < self.min_recovery_ratio:
+                    filter_counts["회복률부족"] += 1
+                    logger.info(
+                        f"{LOG_YELLOW}🔍 [탈락-회복률] {name} {code}: 회복률 {recovery_pos*100:.1f}% < {self.min_recovery_ratio*100:.0f}% "
+                        f"(저점 {low_price:,.0f}원 → 현재 {current_price:,.0f}원 / 범위 {total_range:,.0f}원){LOG_RESET}"
+                    )
+                    if code == "001510":  # SK증권 추적
+                        logger.warning(f"   ⚠️ SK증권(001510) 회복률부족으로 탈락: 회복률={recovery_pos*100:.1f}%, 기준={self.min_recovery_ratio*100:.0f}%")
+                    continue
+                
+                # [필터 3] 피뢰침 방지 - 고점 추격 매수 방지
+                high_chase_threshold = get_env_float("HIGH_PRICE_CHASE_THRESHOLD", 0.96)
+                if current_price >= high_price * high_chase_threshold:
+                    filter_counts["피뢰침(고점근접)"] += 1
+                    drop_from_high = (high_price - current_price) / high_price * 100
+                    logger.info(f"{LOG_YELLOW}🔍 [탈락-피뢰침] {name} {code}: 고점 대비 {drop_from_high:.1f}% 조정 부족 (최소 4% 필요){LOG_RESET}")
+                    continue
+                
+                # [필터 4] 피뢰침 방지 - 급등주 제외
+                if low_price > 0:
+                    daily_change_pct = (high_price - low_price) / low_price * 100
+                else:
+                    daily_change_pct = 0
+                max_daily_change = get_env_float("MAX_DAILY_CHANGE_PCT", 20.0)
+                if daily_change_pct > max_daily_change:
+                    filter_counts["피뢰침(급등주)"] += 1
+                    logger.info(f"{LOG_YELLOW}🔍 [탈락-피뢰침] {name} {code}: 당일 변동폭 {daily_change_pct:.1f}% 과도 (최대 {max_daily_change}%){LOG_RESET}")
+                    continue
+                
+                # [필터 5] RSI 과열 체크 (분봉 데이터 필요)
+                try:
+                    df = self.client.get_minute_chart(code, period="3", limit=20)
+                    if not df.empty and len(df) >= 14 and "RSI" in df.columns:
+                        rsi = float(df["RSI"].iloc[-1])
+                        rsi_threshold = get_env_float("RSI_OVERHEAT_THRESHOLD", 78.0)
+                        if rsi >= rsi_threshold:
+                            filter_counts["RSI과열"] += 1
+                            logger.info(f"{LOG_YELLOW}🔍 [탈락-RSI] {name} {code}: RSI 과열 ({rsi:.1f} >= {rsi_threshold}){LOG_RESET}")
+                            continue
+                        
+                        # [필터 6] MA20 체크
+                        if "MA20" in df.columns and len(df) >= 20:
+                            ma20 = float(df["MA20"].iloc[-1])
+                            if current_price < ma20:
+                                filter_counts["MA20"] += 1
+                                logger.info(f"{LOG_YELLOW}🔍 [탈락-MA20] {name} {code}: 현재가({current_price:.0f}) < MA20({ma20:.2f}){LOG_RESET}")
+                                continue
+                            
+                            ma20_cap_pct = get_env_float("MA20_MAX_ABOVE_PCT", 3.0)
+                            if ma20 > 0 and current_price > ma20 * (1 + ma20_cap_pct / 100):
+                                filter_counts["MA20"] += 1
+                                gap_pct = (current_price - ma20) / ma20 * 100
+                                logger.info(f"{LOG_YELLOW}🔍 [탈락-MA20과열] {name} {code}: 20선 대비 {gap_pct:.1f}% 위 (최대 {ma20_cap_pct}%){LOG_RESET}")
+                                continue
+                except Exception as e:
+                    logger.debug(f"RSI/MA20 체크 실패({code}): {e}")
+                
+                # 외국인/기관 동향 확인
+                investor_trend = self.client.get_investor_trend(code, days=3)
+                investor_score = 0
+                if investor_trend:
+                    total_net = investor_trend.get("total_net_buy", 0)
+                    if total_net > 10000:
+                        investor_score = 20  # 강한 매수세
+                    elif total_net > 0:
+                        investor_score = 10  # 매수세
+                
+                # 조건 통과: 낙폭 3% 이상 & 회복 50% 이상
+                if drop_rate >= self.min_drop_rate and recovery_pos >= self.min_recovery_ratio:
+                    # ML 승률 예측 (USE_ML_SIGNAL=true일 때만)
+                    ml_prob = None
+                    if self.use_ml_signal and self.ml_predictor:
+                        try:
+                            # ML 피처 추출 (간단 버전 - 실제로는 더 많은 피처 필요)
+                            # TODO: 실제 피처 데이터로 교체 필요 (RSI, 거래량비, 이동평균 등)
+                            ml_features = {
+                                "rsi": 50.0,  # 임시값
+                                "volume_ratio": 1.0,
+                                "tail_length_pct": drop_rate * 100,
+                                "ma5_gap_pct": 0.0,
+                                "ma20_gap_pct": 0.0,
+                                "foreign_net_buy": investor_trend.get("foreign_net_buy", 0) if investor_trend else 0,
+                                "institution_net_buy": investor_trend.get("org_net_buy", 0) if investor_trend else 0,
+                                "market_hour": dt.now().hour,
+                            }
+                            ml_prob = self.ml_predictor.predict_win_probability(ml_features)
+                            
+                            # ML 임계값 미달 시 스킵
+                            if ml_prob < self.ml_min_probability:
+                                logger.info(
+                                    f"{LOG_YELLOW}🔍 [탈락-ML] {name} {code}: ML 승률 {ml_prob:.1%} < {self.ml_min_probability:.1%}{LOG_RESET}"
+                                )
+                                continue
+                        except Exception as e:
+                            logger.debug(f"ML 예측 실패({code}): {e}")
+                    
+                    # 점수 계산: 낙폭 + 회복률 + 거래량 + 수급 + ML 승률
+                    score = (drop_rate * 100) + (recovery_pos * 50) + investor_score
+                    if volume > 1000000:  # 거래량 100만주 이상 가산점
+                        score += 10
+                    if ml_prob is not None:
+                        score += (ml_prob - 0.5) * 100  # ML 승률 가산점
+                    # 체결강도 상위 API(FHPST01710000) 보너스: 100 이상 +10점, 120 이상 +20점
+                    execution_strength = execution_strength_map.get(code, 0)
+                    if execution_strength >= 120:
+                        score += 20
+                    elif execution_strength >= 100:
+                        score += 10
+                    candidate = {
+                        "code": code,
+                        "name": name,
+                        "price": current_price,
+                        "score": score,
+                        "drop_rate": drop_rate,
+                        "recovery": recovery_pos,
+                        "volume": volume,
+                        "investor_trend": investor_trend,
+                        "execution_strength": execution_strength,
+                    }
+                    if ml_prob is not None:
+                        candidate["ml_probability"] = ml_prob
+                    
+                    candidates.append(candidate)
+                    passed_filters += 1
+                    
+                    # 통과 즉시 DB 저장 (매매 루프가 스캔 완료를 기다리지 않고 실시간으로 후보 읽기 위함)
+                    # 같은 종목 중복 시 ON CONFLICT(code) DO UPDATE 로 최신 점수/가격으로 갱신됨
+                    try:
+                        self.db.add_target_candidate({
+                            "code": code,
+                            "name": name,
+                            "score": score,
+                            "price": current_price,
+                        })
+                    except Exception as e:
+                        logger.debug(f"후보 즉시 저장 실패({code}): {e}")
+                    
+                    ml_info = f" | ML {ml_prob:.1%}" if ml_prob is not None else ""
+                    strength_info = f" | 체결강도 {execution_strength:.0f}(+{'20' if execution_strength >= 120 else '10'}점)" if execution_strength >= 100 else ""
+                    logger.info(
+                        f"{LOG_GREEN}✅ [통과] {name} {code}: 낙폭 {drop_rate*100:.1f}% | 회복 {recovery_pos*100:.0f}% | 강도 {score:.1f}{strength_info}{ml_info}{LOG_RESET}"
+                    )
+                    
+            except Exception as e:
+                filter_counts["API예외"] = filter_counts.get("API예외", 0) + 1
+                logger.warning(
+                    f"종목 스캔 예외 code={code} exception={e!r} type={type(e).__name__}"
+                )
+                time.sleep(random.uniform(1.0, 2.0))
+                continue
+        
+        candidates.sort(key=lambda x: x["score"], reverse=True)
+        
+        # 필터별 탈락/통과 요약 (색상: 탈락=노랑, 통과=초록)
+        summary = ", ".join(f"{k}={v}" for k, v in filter_counts.items() if v > 0)
+        logger.info(f"   📊 [필터 요약] 스캔 {total_scanned}개 중 {LOG_YELLOW}탈락: {summary or '없음'}{LOG_RESET} | {LOG_GREEN}통과: {len(candidates)}개{LOG_RESET}")
+        count_ge4 = sum(1 for c in candidates if c.get("score", 0) >= 4.0)
+        logger.info(
+            f"   ✅ 스캔 완료: 개미털기 {len(candidates)}개 통과 (강도 4.0 이상: {count_ge4}개) "
+            f"[스캔 {total_scanned}개 → 필터 통과 {passed_filters}개]"
+        )
+        # 통과 종목 전부 출력: 종목명 · 코드 · 강도 (몇 개 안 되므로 전부 표시)
+        if candidates:
+            logger.info("   📌 [개미털기 통과 목록] 종목명 · 코드 · 강도")
+            for i, c in enumerate(candidates):
+                logger.info(f"      {i+1}. {c['name']}  {c['code']}  강도 {c['score']:.1f}")
+            # 강도순 상위 10개 → Mattermost 전송
+            top10 = candidates[:10]
+            lines = [f"🐜 **개미털기 강도순 TOP{len(top10)}** (스캔 {total_scanned}개 중 통과 {len(candidates)}개)"]
+            for i, c in enumerate(top10, 1):
+                name = (c.get("name") or c.get("code") or "").strip()
+                score = c.get("score", 0)
+                lines.append(f"{i}. 강도 **{score:.1f}**  {name}")
+            try:
+                self.send_mm("\n".join(lines))
+            except Exception as e:
+                logger.debug(f"Mattermost 개미털기 TOP10 전송 스킵: {e}")
+        return candidates[:max_candidates]
+
+    def calculate_atr(self, df, period=14):
+        """
+        ATR (Average True Range) 계산 - 변동성 지표
+        - TR(True Range) = max(고가-저가, |고가-전일종가|, |저가-전일종가|)
+        - ATR = TR의 14일 이동평균
+        """
+        try:
+            if df is None or len(df) < period:
+                return 0
+            
+            df = df.copy()
+            # True Range 계산
+            high_low = df['high'] - df['low']
+            high_close = (df['high'] - df['close'].shift()).abs()
+            low_close = (df['low'] - df['close'].shift()).abs()
+            df['tr'] = pd.concat([high_low, high_close, low_close], axis=1).max(axis=1)
+            
+            # ATR = TR의 14일 이동평균
+            atr = df['tr'].rolling(window=period).mean().iloc[-1]
+            return float(atr) if not pd.isna(atr) and atr > 0 else 0
+        except Exception as e:
+            logger.debug(f"ATR 계산 실패: {e}")
+            return 0
+
+    def check_sell_signals(self):
+        """
+        매도 신호 체크 (ATR 기반 변동성 매도 로직)
+        - 어깨 매도 (고점 대비 3% 하락)
+        - ATR 기반 스캘핑 (본절사수/익절보존)
+        - 순수익 보존
+        - 목표가/손절가
+        """
+        if not self.holdings:
+            return []
+        
+        sell_signals = []
+        for code, holding in list(self.holdings.items()):
+            try:
+                name = holding.get("name", code)
+                buy_price = holding["buy_price"]
+                buy_time_str = holding.get("buy_time", "")
+                qty = holding["qty"]
+                
+                # 현재가 조회
+                price_data = self.client.inquire_price(code)
+                if not price_data:
+                    continue
+                
+                current_price = abs(float(price_data.get("stck_prpr", 0)))
+                if current_price == 0:
+                    continue
+                
+                # 고점 갱신 (holdings에 저장)
+                max_price = holding.get("max_price", buy_price)
+                if current_price > max_price:
+                    max_price = current_price
+                    self.holdings[code]["max_price"] = max_price
+                
+                # 손익률 계산
+                profit_pct = (current_price - buy_price) / buy_price if buy_price > 0 else 0
+                profit_val = (current_price - buy_price) * qty
+                
+                # ATR 조회 (DB 또는 재계산)
+                atr = holding.get("atr_entry", 0)
+                if atr == 0:
+                    # ATR 재계산 (3분봉)
+                    try:
+                        df = self.client.get_minute_chart(code, period="3", limit=20)
+                        if not df.empty:
+                            atr = self.calculate_atr(df)
+                            if atr > 0:
+                                self.holdings[code]["atr_entry"] = atr
+                    except Exception as e:
+                        logger.debug(f"ATR 조회 실패({code}): {e}")
+                        atr = buy_price * 0.01  # 기본값 1%
+                
+                # 손절가/목표가 (ATR 기반 또는 기본값)
+                stop_price = holding.get("stop_price", buy_price * (1 + self.stop_loss_pct))
+                target_price_atr = holding.get("target_price", buy_price * (1 + self.take_profit_pct))
+                target_price_pct = buy_price * (1 + self.take_profit_pct)  # 퍼센트 기반 목표가
+                
+                # ATR 기반 손절가/목표가 계산
+                if atr > 0:
+                    stop_price = buy_price - (atr * self.stop_atr_multiplier)
+                    target_price_atr = buy_price + (atr * self.target_atr_multiplier)
+                
+                # 목표가: ATR 기반과 퍼센트 기반 중 더 작은 값 사용 (둘 다 체크)
+                target_price = min(target_price_atr, target_price_pct)
+                
+                # 매도 사유 판단
+                sell_reason = None
+                
+                # ==========================================================
+                # [1] 어깨 매도 (Shoulder Cut) - 최우선!
+                # 고점 대비 3% 이상 빠지면 수익/손실 불문하고 즉시 탈출
+                # ==========================================================
+                shoulder_cut_pct = get_env_float("SHOULDER_CUT_PCT", 0.03)
+                drop_from_high = (max_price - current_price) / max_price if max_price > 0 else 0
+                if drop_from_high >= shoulder_cut_pct:
+                    sell_reason = "어깨매도"
+                
+                # ==========================================================
+                # [2] 금액 기준 손절 (원 단위)
+                # ==========================================================
+                max_loss_per_trade_krw = get_env_int("MAX_LOSS_PER_TRADE_KRW", 200000)
+                if not sell_reason and profit_val <= -max_loss_per_trade_krw:
+                    sell_reason = "금액손실컷"
+                
+                # ==========================================================
+                # [3] ATR 기반 스캘핑 로직
+                # ==========================================================
+                if not sell_reason and atr > 0:
+                    # [스캘핑 1] 본절사수: 고점이 ATR 1배 이상 올랐는데 현재가가 ATR 0.2배 이하로 떨어짐
+                    if (max_price >= buy_price + atr * 1.0) and (current_price <= buy_price + atr * 0.2):
+                        sell_reason = "스캘핑_본절사수"
+                    
+                    # [스캘핑 2] 익절보존: 수익 중인데 고점 대비 ATR 1배 이상 하락
+                    if not sell_reason and current_price < (max_price - atr * 1.0) and profit_pct > 0:
+                        sell_reason = "스캘핑_익절보존"
+                
+                # 보유 시간 계산 (N자 패턴 등 다음날 상승 가능성 있는 종목 24시간 보유)
+                hours_passed = 0
+                if buy_time_str:
+                    try:
+                        buy_time = dt.strptime(buy_time_str, "%Y-%m-%d %H:%M:%S")
+                        hours_passed = (dt.now() - buy_time).total_seconds() / 3600
+                    except:
+                        pass
+                
+                # ==========================================================
+                # [4] 빠른 익절 보호 (매수 후 30분 이내)
+                # ==========================================================
+                if not sell_reason and hours_passed > 0:
+                    use_quick_profit = get_env_bool("USE_QUICK_PROFIT_PROTECTION", True)
+                    if use_quick_profit and hours_passed < 0.5:
+                        if max_price >= buy_price * 1.005 and current_price <= buy_price * 1.0015:
+                            sell_reason = "💨 작은수익보호"
+                
+                # ==========================================================
+                # [5] 24시간 보유 전략 (N자 패턴 등 다음날 상승 가능성)
+                # ==========================================================
+                # 세력이 N자 만들어서 털어먹으려는 종목은 하루에 안 끝나고 다음날 오르는 경우가 있음
+                # 24시간 이내: 특정 조건에서만 매도 (보수적)
+                # 24시간 이후: 일반 매도 조건 적용
+                min_hold_hours = get_env_float("MIN_HOLD_HOURS", 24.0)  # 최소 보유 시간 (기본 24시간)
+                
+                if not sell_reason and hours_passed > 0:
+                    if hours_passed < min_hold_hours:
+                        # 24시간 이내: 큰 수익(5% 이상) 또는 고점 대비 큰 하락만 매도
+                        if profit_pct > 0.05:  # 5% 이상 수익
+                            sell_reason = f"💰 {hours_passed:.1f}시간내 5%+ 익절"
+                        elif max_price >= buy_price * 1.07 and current_price <= max_price * 0.97:
+                            # 고점 7% 이상 찍고 고점 대비 3% 이상 하락
+                            sell_reason = f"📈 {hours_passed:.1f}시간내 고점7%→3%하락"
+                        # 그 외에는 24시간 보유 유지 (손절은 제외)
+                    else:
+                        # 24시간 이후: 일반 매도 조건 적용
+                        if profit_pct > 0.02:  # 2% 이상 수익
+                            sell_reason = f"⏰ {hours_passed:.1f}시간 경과 2%+ 익절"
+                        elif profit_pct > 0 and current_price < max_price * 0.97:
+                            # 수익 중인데 고점 대비 3% 이상 하락
+                            sell_reason = f"⏰ {hours_passed:.1f}시간 경과 익절보호"
+                
+                # ==========================================================
+                # [6] 목표가 달성 및 손절 (24시간 보유 전략과 별개로 항상 체크)
+                # ==========================================================
+                if not sell_reason:
+                    # 목표가 달성 체크 (ATR 기반 또는 퍼센트 기반 중 먼저 도달한 것)
+                    if current_price >= target_price:
+                        if current_price >= target_price_atr and current_price >= target_price_pct:
+                            sell_reason = "목표달성(ATR+퍼센트)"
+                        elif current_price >= target_price_atr:
+                            sell_reason = "목표달성(ATR)"
+                        else:
+                            sell_reason = "목표달성(퍼센트)"
+                    elif current_price <= stop_price:
+                        sell_reason = "전략손절"
+                    elif profit_pct <= self.stop_loss_pct:
+                        sell_reason = f"칼손절({profit_pct * 100:.1f}%)"
+                    elif profit_pct >= self.take_profit_pct:
+                        sell_reason = "익절(퍼센트)"
+                
+                # 매도 신호 추가
+                if sell_reason:
+                    sell_signals.append({
+                        "code": code,
+                        "name": name,
+                        "reason": sell_reason,
+                        "profit_pct": profit_pct,
+                        "qty": qty,
+                        "price": current_price,
+                    })
+                
+                time.sleep(random.uniform(0.3, 0.7))
+            except Exception as e:
+                logger.error(f"매도 신호 체크 실패({code}): {e}")
+                continue
+        
+        return sell_signals
+
+    def execute_buy(self, signal):
+        """
+        매수 실행
+        - 키움 봇과 동일하게 대형주/소형주 비율 맞추는 로직 포함
+        - 대형주: 기본 금액 100% / 중형주: 85% / 소형주: 70%
+        - 켈리 기반 매수 금액 + 종목당 최대 15% 제한
+        """
+        code = signal["code"]
+        name = signal["name"]
+        price = signal["price"]
+        
+        # 이미 보유 중이면 스킵
+        if code in self.holdings:
+            logger.warning(f"⚠️ [{name}] 이미 보유 중 -> 매수 스킵")
+            return False
+        
+        # 최대 보유 종목 수 체크
+        if len(self.holdings) >= self.max_stocks:
+            logger.warning(f"⚠️ 최대 보유 종목 수 도달 ({self.max_stocks}개)")
+            return False
+        
+        # 🔥 매수 직전 예수금 실시간 확인
+        if not self._update_account_light(profit_val=0):
+            logger.warning(f"⚠️ [{name}] 예수금 조회 실패 -> 매수 스킵")
+            return False
+        
+        # ============================================================
+        # [대/중/소형주 구분] - 일봉 거래대금 평균 (키움 봇과 동일)
+        # ============================================================
+        size_class = None
+        try:
+            df = self.client.get_daily_chart(code, limit=10)
+            if not df.empty and "volume" in df.columns and "close" in df.columns:
+                trade_values = df["volume"] * df["close"]
+                avg_trade_value = trade_values.mean()
+                large_min = get_env_float("SIZE_CLASS_LARGE_MIN", 5000000000)  # 50억 (대형주)
+                mid_min = get_env_float("SIZE_CLASS_MID_MIN", 500000000)       # 5억 (중형주)
+                if avg_trade_value >= large_min:
+                    size_class = "대"
+                elif avg_trade_value >= mid_min:
+                    size_class = "중"
+                else:
+                    size_class = "소"
+                logger.info(
+                    f"📊 [{name}] 거래대금 평균 {avg_trade_value/1e8:.1f}억원 → {size_class}형주"
+                )
+        except Exception as e:
+            logger.debug(f"대/중/소형 조회 스킵({code}): {e}")
+        
+        # ============================================================
+        # [매수 금액] 변동성 역가중 (Volatility Inverse Weighting)
+        # ============================================================
+        # ATR 계산용 분봉 데이터 (변동성 계산에 필요)
+        df_minute = None
+        try:
+            df_minute = self.client.get_minute_chart(code, period="3", limit=20)
+        except Exception as e:
+            logger.debug(f"분봉 조회 실패({code}): {e}")
+        
+        # RiskManager 사용 시: 변동성 역가중으로 매수 금액 계산
+        if self.risk_mgr is not None:
+            # 켈리 비율 (DB에서 계산, 없으면 None)
+            kelly_fraction = None
+            if self.risk_mgr.use_kelly:
+                try:
+                    kelly_fraction = self.db.calculate_half_kelly()
+                except Exception as e:
+                    logger.debug(f"켈리 비율 계산 스킵: {e}")
+            
+            # 변동성 역가중 매수 금액 계산
+            amount = self.risk_mgr.get_position_size(
+                stock_name=name,
+                current_balance=self.current_cash,
+                df=df_minute,  # ATR 계산용 분봉 데이터
+                kelly_fraction=kelly_fraction,
+                size_class=size_class,  # 대/중/소형 구분
+            )
+            
+            if amount <= 0:
+                logger.warning(f"⚠️ [{name}] RiskManager 계산 금액 0원 -> 매수 스킵")
+                return False
+            
+            # 수량 계산 (수수료 고려)
+            qty = self.risk_mgr.calculate_quantity(price, amount)
+        else:
+            # 폴백: 기존 고정 슬롯 방식 (RiskManager 미사용 시)
+            if self.max_stocks > 0:
+                slot_money = int(self.current_cash * 0.9 / self.max_stocks)
+            else:
+                slot_money = 100000
+            base_amount = min(slot_money, 100000)
+            if self.stop_loss_pct != 0:
+                stop_pct_abs = abs(self.stop_loss_pct)
+            else:
+                stop_pct_abs = 0.04
+            if stop_pct_abs > 0:
+                kelly_risk_amount = self.current_cash * self.risk_pct_per_trade * self.kelly_multiplier
+                kelly_based_amount = int(kelly_risk_amount / stop_pct_abs)
+                base_amount = min(base_amount, kelly_based_amount)
+            if size_class == "소":
+                amount = int(base_amount * 0.7)
+                logger.info(f"💰 [{name}] 소형주 → 매수 금액 70%: {amount:,.0f}원")
+            elif size_class == "중":
+                amount = int(base_amount * 0.85)
+                logger.info(f"💰 [{name}] 중형주 → 매수 금액 85%: {amount:,.0f}원")
+            else:
+                amount = base_amount
+            max_limit = int(self.current_cash * self.max_position_pct)
+            if amount > max_limit:
+                logger.info(f"📐 [{name}] 최대 포지션 제한: {amount:,.0f}원 → {max_limit:,.0f}원")
+                amount = max_limit
+            amount = max(amount, self.min_position_amount)
+            qty = int(amount / price)
+        if qty <= 0:
+            logger.warning(f"⚠️ [{name}] 매수 수량 0 (가격: {price:,.0f}원, 금액: {amount:,.0f}원)")
+            return False
+        
+        required_amount = price * qty * 1.05
+        if self.current_cash < required_amount:
+            logger.warning(
+                f"⚠️ [{name}] 예수금 부족: 필요 {required_amount:,.0f}원 / "
+                f"보유 {self.current_cash:,.0f}원 -> 매수 스킵"
+            )
+            return False
+        
+        # ATR 계산 (변동성 기반 손절가/목표가 설정용)
+        # df_minute는 위에서 이미 조회했으므로 재사용
+        atr = 0
+        stop_price = price * (1 + self.stop_loss_pct)
+        target_price = price * (1 + self.take_profit_pct)
+        if df_minute is not None and not df_minute.empty:
+            try:
+                atr = self.calculate_atr(df_minute)
+                if atr > 0:
+                    # ATR 기반 손절가/목표가 설정
+                    stop_price = price - (atr * self.stop_atr_multiplier)
+                    target_price = price + (atr * self.target_atr_multiplier)
+                    logger.info(f"📊 [{name}] ATR 기반 손절가/목표가: ATR={atr:.0f}원, 손절={stop_price:,.0f}원, 목표={target_price:,.0f}원")
+            except Exception as e:
+                logger.debug(f"ATR 계산 스킵({code}): {e}")
+                atr = price * 0.01  # 기본값 1%
+        else:
+            atr = price * 0.01  # 기본값 1%
+        
+        success = self.client.buy_market_order(code, qty)
+        if success:
+            self._update_account_light(profit_val=0)
+            buy_time = dt.now().strftime("%Y-%m-%d %H:%M:%S")
+            self.holdings[code] = {
+                "buy_price": price,
+                "qty": qty,
+                "buy_time": buy_time,
+                "name": name,
+                "max_price": price,  # 고점 추적
+                "atr_entry": atr,  # 매수 시점 ATR 저장
+                "stop_price": stop_price,  # 손절가
+                "target_price": target_price,  # 목표가
+            }
+            self.db.upsert_trade({
+                "code": code,
+                "name": name,
+                "strategy": "SHORT_ANT_SHAKING",
+                "avg_buy_price": price,
+                "current_price": price,
+                "target_qty": qty,
+                "current_qty": qty,
+                "status": "HOLDING",
+                "buy_date": buy_time,
+                "stop_price": stop_price,
+                "target_price": target_price,
+                "atr_entry": atr,
+            })
+            logger.info(f"💰 [매수 체결] {name} ({code}): {price:,.0f}원 × {qty}주 | 손절={stop_price:,.0f}원, 목표={target_price:,.0f}원")
+            return True
+        return False
+
+    def execute_sell(self, signal):
+        """매도 실행"""
+        code = signal["code"]
+        name = signal["name"]
+        qty = signal["qty"]
+        
+        if code not in self.holdings:
+            logger.warning(f"⚠️ [{name}] 보유 종목 아님")
+            return False
+        
+        # 매도 주문
+        success = self.client.sell_market_order(code, qty)
+        if success:
+            # 현재가 조회
+            price_data = self.client.inquire_price(code)
+            if price_data:
+                sell_price = abs(float(price_data.get("stck_prpr", 0)))
+            else:
+                sell_price = signal.get("price", 0)
+            
+            # 손익 계산 (매도 후 총자산 반영용)
+            holding = self.holdings.get(code, {})
+            buy_price = holding.get("buy_price", sell_price)
+            profit_val = (sell_price - buy_price) * qty  # 손익 금액
+            
+            # DB에서 매도 처리
+            self.db.close_trade(
+                code=code,
+                sell_price=sell_price,
+                sell_reason=signal['reason'],
+            )
+            
+            del self.holdings[code]
+            
+            # 🔥 매도 후 예수금 + 총자산 즉시 업데이트 (손익 반영)
+            self._update_account_light(profit_val=profit_val)
+            
+            logger.info(f"💸 [매도 체결] {name} ({code}): {qty}주 ({signal['reason']}, {signal['profit_pct']*100:+.2f}%)")
+            return True
+        
+        return False
+
+    def run(self):
+        """메인 루프 (진입점). 내부적으로 asyncio.run(_run_async()) 호출."""
+        asyncio.run(self._run_async())
+    
+    async def _run_async(self):
+        """비동기 메인 루프 - 백그라운드 태스크 시작 후 동기 매매 루프 실행"""
+        logger.info("🚀 단타 트레이딩 봇 시작 (비동기 백그라운드 작업 활성화)")
+        
+        # 백그라운드 태스크 시작
+        self._universe_task = asyncio.create_task(self._universe_scan_scheduler())
+        self._report_task = asyncio.create_task(self._report_scheduler())
+        self._asset_task = asyncio.create_task(self._asset_update_scheduler())
+        logger.info("✅ 백그라운드 태스크 시작 완료 (유니버스 스캔, 리포트, 자산 업데이트)")
+        
+        # 동기 매매 루프는 별도 스레드에서 실행 (메인 이벤트 루프 블로킹 방지)
+        loop = asyncio.get_event_loop()
+        await loop.run_in_executor(None, self._sync_trading_loop)
+    
+    def _sync_trading_loop(self):
+        """동기 매매 루프 (메인 로직) - 백그라운드 작업과 분리"""
+        logger.info("📈 매매 루프 시작 (동기 모드)")
+        
+        while True:
+            try:
+                now = dt.now()
+                current_date = now.strftime("%Y-%m-%d")
+                
+                # 날짜 변경 시 리포트 플래그 리셋
+                if current_date != self.today_date:
+                    self.today_date = current_date
+                    self.morning_report_sent = False
+                    self.closing_report_sent = False
+                    self.final_report_sent = False
+                    self.ai_report_sent = False
+                    self.start_day_asset = 0
+                    logger.info(f"📅 날짜 변경: {current_date}")
+                
+                # 리포트 전송은 백그라운드 태스크에서 처리하므로 여기서는 제거
+                # (기존 코드와의 호환성을 위해 주석 처리)
+                # if now.hour == 13 and now.minute == 0:
+                #     self.send_morning_report()
+                #     self.send_ai_report()
+                # elif now.hour == 15 and now.minute == 15:
+                #     self.send_closing_report()
+                # elif now.hour == 15 and now.minute == 35:
+                #     self.send_final_report()
+                
+                # 장 상태 체크
+                if not self.check_market_status():
+                    logger.info("⏸ 장 시간 아님 - 대기 중...")
+                    time.sleep(60)
+                    continue
+                
+                # 자산 정보 업데이트는 백그라운드 태스크에서 처리하므로 여기서는 제거
+                # (기존 코드와의 호환성을 위해 주석 처리)
+                # if now.minute % 30 == 0:  # 30분마다
+                #     self._update_assets()
+                
+                # 매도 신호 체크 (우선) - 메인 루프에서 처리
+                sell_signals = self.check_sell_signals()
+                for signal in sell_signals:
+                    self.execute_sell(signal)
+                    db_candidates = self.db.get_target_candidates()
+                    if db_candidates:
+                        logger.info(f"🔍 [매수 기회 탐색] 타겟:{len(db_candidates)}개 | 보유:{active_count}/{self.max_stocks}")
+                        # DB 후보군이 있으면 사용
+                        for db_item in db_candidates[:1]:  # 상위 1개만
+                            code = db_item['code']
+                            name = db_item['name']
+                            # 실제 가격 확인 후 매수
+                            price_data = self.client.inquire_price(code)
+                            if price_data:
+                                current_price = abs(float(price_data.get("stck_prpr", 0)))
+                                candidate = {
+                                    'code': code,
+                                    'name': name,
+                                    'price': current_price,
+                                    'score': db_item.get('score', 0),
+                                }
+                                self.execute_buy(candidate)
+                                time.sleep(random.uniform(1, 2))
+                                break
+                    else:
+                        # DB 후보군이 없으면 대기 (유니버스 업데이트 대기)
+                        # ⚠️ 직접 스캔하지 않음 - 백그라운드 태스크에서 5분마다 업데이트됨
+                        if active_count == 0:  # 첫 실행 시에만 로그
+                            logger.info(f"🔍 [매수 기회 탐색] 타겟:0개 (유니버스 스캔 대기 중) | 보유:{active_count}/{self.max_stocks}")
+                
+                # 대기
+                time.sleep(random.uniform(3, 5))
+                
+            except KeyboardInterrupt:
+                logger.info("⏹ 봇 종료")
+                # 백그라운드 태스크 취소
+                if self._universe_task:
+                    self._universe_task.cancel()
+                if self._report_task:
+                    self._report_task.cancel()
+                if self._asset_task:
+                    self._asset_task.cancel()
+                break
+            except Exception as e:
+                logger.error(f"❌ 루프 에러: {e}")
+                time.sleep(5)
+
+
+if __name__ == "__main__":
+    bot = ShortTradingBot()
+    bot.run()
diff --git a/ml_predictor.py b/ml_predictor.py
new file mode 100644
index 0000000..4ff41fa
--- /dev/null
+++ b/ml_predictor.py
@@ -0,0 +1,229 @@
+#!/usr/bin/env python3
+"""
+KIS Bot용 ML 승률 예측 모델
+- kis_bot/quant_bot.db의 trade_history 데이터로 학습
+- 매수 신호의 승률 예측 (0.0 ~ 1.0)
+- 주간 단위 자동 재학습
+"""
+import os
+import pickle
+import sqlite3
+import logging
+from pathlib import Path
+from datetime import datetime, timedelta
+
+import numpy as np
+import pandas as pd
+
+# Logger 설정
+logger = logging.getLogger("KIS_MLPredictor")
+
+try:
+    from sklearn.ensemble import RandomForestClassifier
+    from sklearn.model_selection import train_test_split
+    from sklearn.metrics import accuracy_score, precision_score, recall_score
+    ML_AVAILABLE = True
+except ImportError:
+    ML_AVAILABLE = False
+    logger.warning("⚠️ scikit-learn 미설치! ML 기능 사용 불가")
+    logger.warning("   설치: pip install scikit-learn")
+
+
+SCRIPT_DIR = Path(__file__).resolve().parent
+
+
+class MLPredictor:
+    """매수 신호 승률 예측 모델"""
+    
+    def __init__(
+        self,
+        db_path: str = None,
+        model_path: str = None,
+    ):
+        # 기본값: kis_bot/quant_bot.db, kis_bot/ml_model.pkl
+        self.db_path = db_path or str(SCRIPT_DIR / "quant_bot.db")
+        self.model_path = model_path or str(SCRIPT_DIR / "ml_model.pkl")
+        self.model = None
+        self.feature_names = [
+            "rsi",
+            "volume_ratio",
+            "tail_length_pct",
+            "ma5_gap_pct",
+            "ma20_gap_pct",
+            "foreign_net_buy",
+            "institution_net_buy",
+            "market_hour",
+        ]
+        self.min_train_samples = 30
+        
+        if not ML_AVAILABLE:
+            logger.error("❌ scikit-learn이 설치되지 않았습니다!")
+            return
+        
+        self.load_model()
+    
+    def extract_features_from_db(self, days: int = 90) -> pd.DataFrame:
+        """DB에서 학습용 피처 추출
+        
+        현재는 trade_history의 profit_rate 기반으로 승/패 라벨만 생성하고,
+        피처는 프로토타입 단계로 랜덤 값을 사용한다.
+        (실전에서는 active_trades에 진입 시점 피처를 저장해서 사용해야 함)
+        """
+        try:
+            conn = sqlite3.connect(self.db_path)
+            cutoff_date = (datetime.now() - timedelta(days=days)).strftime("%Y-%m-%d")
+            
+            query = f"""
+                SELECT profit_rate, buy_date, sell_date, strategy
+                FROM trade_history
+                WHERE sell_date >= '{cutoff_date}'
+                ORDER BY sell_date DESC
+            """
+            
+            df = pd.read_sql_query(query, conn)
+            conn.close()
+            
+            if len(df) < self.min_train_samples:
+                logger.warning(
+                    f"⚠️ 학습 데이터 부족: {len(df)}건 (최소 {self.min_train_samples}건 필요)"
+                )
+                return None
+            
+            df["is_win"] = (df["profit_rate"] > 0).astype(int)
+            logger.info(
+                f"📊 학습 데이터 로드: {len(df)}건 "
+                f"(익절: {df['is_win'].sum()}건, 손절: {(1 - df['is_win']).sum()}건)"
+            )
+            
+            return df
+            
+        except Exception as e:
+            logger.error(f"❌ 피처 추출 실패: {e}")
+            return None
+    
+    def train_model(self, retrain: bool = False) -> bool:
+        """모델 학습"""
+        if not ML_AVAILABLE:
+            logger.error("❌ scikit-learn 미설치로 학습 불가")
+            return False
+        
+        if self.model is not None and not retrain:
+            logger.info("✅ 기존 모델 사용")
+            return True
+        
+        df = self.extract_features_from_db(days=90)
+        
+        if df is None or len(df) < self.min_train_samples:
+            logger.warning("⚠️ 학습 데이터 부족 - ML 모델 사용 불가")
+            return False
+        
+        logger.warning("⚠️ [프로토타입] 랜덤 피처로 학습 중")
+        logger.warning("   → 실제 운영 시: active_trades 테이블에 진입 피처 저장 후 사용")
+        
+        # TODO: 실제 피처 데이터로 교체 필요
+        # 현재는 데모용 랜덤 피처 사용
+        np.random.seed(42)
+        X = pd.DataFrame(
+            {
+                "rsi": np.random.uniform(20, 80, len(df)),
+                "volume_ratio": np.random.uniform(0.5, 5.0, len(df)),
+                "tail_length_pct": np.random.uniform(0, 5, len(df)),
+                "ma5_gap_pct": np.random.uniform(-5, 5, len(df)),
+                "ma20_gap_pct": np.random.uniform(-10, 10, len(df)),
+                "foreign_net_buy": np.random.uniform(-1000, 1000, len(df)),
+                "institution_net_buy": np.random.uniform(-500, 500, len(df)),
+                "market_hour": np.random.randint(9, 15, len(df)),
+            }
+        )
+        y = df["is_win"].values
+        
+        X_train, X_test, y_train, y_test = train_test_split(
+            X, y, test_size=0.2, random_state=42, stratify=y
+        )
+        
+        logger.info("🤖 RandomForest 학습 시작...")
+        self.model = RandomForestClassifier(
+            n_estimators=100,
+            max_depth=10,
+            min_samples_split=5,
+            random_state=42,
+        )
+        self.model.fit(X_train, y_train)
+        
+        y_pred = self.model.predict(X_test)
+        accuracy = accuracy_score(y_test, y_pred)
+        precision = precision_score(y_test, y_pred, zero_division=0)
+        recall = recall_score(y_test, y_pred, zero_division=0)
+        
+        logger.info("✅ 학습 완료!")
+        logger.info(f"   정확도: {accuracy:.2%}")
+        logger.info(f"   정밀도: {precision:.2%}")
+        logger.info(f"   재현율: {recall:.2%}")
+        
+        feature_importance = sorted(
+            zip(self.feature_names, self.model.feature_importances_),
+            key=lambda x: x[1],
+            reverse=True,
+        )
+        logger.info("   중요 피처:")
+        for fname, importance in feature_importance[:5]:
+            logger.info(f"      {fname}: {importance:.3f}")
+        
+        self.save_model()
+        return True
+    
+    def predict_win_probability(self, features: dict) -> float:
+        """매수 신호의 승률 예측 (0.0 ~ 1.0)"""
+        if not ML_AVAILABLE or self.model is None:
+            return 0.5
+        
+        try:
+            X = pd.DataFrame([features])[self.feature_names]
+            proba = self.model.predict_proba(X)[0]
+            win_prob = proba[1]
+            return float(win_prob)
+        except Exception as e:
+            logger.error(f"❌ 예측 실패: {e}")
+            return 0.5
+    
+    def save_model(self) -> None:
+        """모델 파일로 저장"""
+        try:
+            with open(self.model_path, "wb") as f:
+                pickle.dump(self.model, f)
+            logger.info(f"💾 모델 저장: {self.model_path}")
+        except Exception as e:
+            logger.error(f"❌ 모델 저장 실패: {e}")
+    
+    def load_model(self) -> bool:
+        """저장된 모델 로드"""
+        if not ML_AVAILABLE:
+            return False
+        
+        if os.path.exists(self.model_path):
+            try:
+                with open(self.model_path, "rb") as f:
+                    self.model = pickle.load(f)
+                logger.info(f"✅ 모델 로드: {self.model_path}")
+                return True
+            except Exception as e:
+                logger.error(f"❌ 모델 로드 실패: {e}")
+        else:
+            logger.info("ℹ️ 저장된 모델 없음 - 첫 실행 시 학습 필요")
+        
+        return False
+    
+    def should_retrain(self) -> bool:
+        """재학습이 필요한지 체크 (7일 경과 시)"""
+        if not os.path.exists(self.model_path):
+            return True
+        
+        model_mtime = datetime.fromtimestamp(os.path.getmtime(self.model_path))
+        days_old = (datetime.now() - model_mtime).days
+        
+        if days_old >= 7:
+            logger.info(f"🔄 모델 {days_old}일 경과 → 재학습 필요")
+            return True
+        
+        return False
+
diff --git a/modify_db_schema.py b/modify_db_schema.py
new file mode 100644
index 0000000..8b615f7
--- /dev/null
+++ b/modify_db_schema.py
@@ -0,0 +1,37 @@
+import sqlite3
+import os
+
+# 데이터베이스 파일 경로
+db_path = os.path.join(os.path.dirname(__file__), 'quant_bot.db')
+
+# 연결 생성
+conn = sqlite3.connect(db_path)
+cursor = conn.cursor()
+
+# 기존 필드 이름 변경
+print("기존 테이블 필드 변경 중...")
+cursor.execute("ALTER TABLE env_config RENAME COLUMN KIS_APP_KEY TO KIS_APP_KEY_REAL")
+cursor.execute("ALTER TABLE env_config RENAME COLUMN KIS_APP_SECRET TO KIS_APP_SECRET_REAL")
+cursor.execute("ALTER TABLE env_config RENAME COLUMN KIS_ACCOUNT_NO TO KIS_ACCOUNT_NO_REAL")
+cursor.execute("ALTER TABLE env_config RENAME COLUMN KIS_ACCOUNT_CODE TO KIS_ACCOUNT_CODE_REAL")
+
+# 모의계좌용 필드 추가
+print("모의계좌용 필드 추가 중...")
+cursor.execute("ALTER TABLE env_config ADD COLUMN KIS_APP_KEY_MOCK TEXT")
+cursor.execute("ALTER TABLE env_config ADD COLUMN KIS_APP_SECRET_MOCK TEXT")
+cursor.execute("ALTER TABLE env_config ADD COLUMN KIS_ACCOUNT_NO_MOCK TEXT")
+cursor.execute("ALTER TABLE env_config ADD COLUMN KIS_ACCOUNT_CODE_MOCK TEXT")
+
+# 변경된 필드명으로 데이터 이동 (기존 데이터 복사)
+print("기존 데이터 이동 중...")
+# 실제 데이터베이스에서 KIS_APP_KEY_REAL을 KIS_APP_KEY_MOCK로 복사 (모의계좌용으로 사용)
+cursor.execute("UPDATE env_config SET KIS_APP_KEY_MOCK = KIS_APP_KEY_REAL")
+cursor.execute("UPDATE env_config SET KIS_APP_SECRET_MOCK = KIS_APP_SECRET_REAL")
+cursor.execute("UPDATE env_config SET KIS_ACCOUNT_NO_MOCK = KIS_ACCOUNT_NO_REAL")
+cursor.execute("UPDATE env_config SET KIS_ACCOUNT_CODE_MOCK = KIS_ACCOUNT_CODE_REAL")
+
+# 변경 내용 저장
+conn.commit()
+
+print("데이터베이스 스키마 변경 완료")
+conn.close()
\ No newline at end of file
diff --git a/quant_bot.db b/quant_bot.db
new file mode 100644
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diff --git a/risk_manager.py b/risk_manager.py
new file mode 100644
index 0000000..52d2e08
--- /dev/null
+++ b/risk_manager.py
@@ -0,0 +1,270 @@
+"""
+변동성 기반 리스크 관리 모듈
+- 예수금 비율 기반 비중 조절
+- ATR/변동성 역가중 (Volatility Inverse Weighting)
+- 종목별 안전 매수 금액 계산
+"""
+import logging
+import pandas as pd
+import numpy as np
+from typing import List, Dict
+
+logger = logging.getLogger("RiskManager")
+
+
+class RiskManager:
+    """
+    [예수금 연동 리스크 관리 모듈]
+    - 고정 금액이 아닌 '현재 예수금' 대비 퍼센트로 투자금 계산
+    - 변동성 큰 종목 = 적게 매수, 변동성 작은 종목 = 많이 매수
+    """
+    
+    def __init__(
+        self, 
+        risk_pct_per_trade: float = 0.02,  # 1회 거래 시 허용 손실 비율 (2%)
+        max_position_pct: float = 0.20,    # 종목당 최대 비중 (20%)
+        min_position_amount: int = 50000,  # 최소 매수 금액 (5만원)
+        use_kelly: bool = False,           # 켈리 공식 사용 여부
+        kelly_multiplier: float = 0.5      # 켈리 배율 (0.5 = 하프 켈리)
+    ):
+        """
+        Args:
+            risk_pct_per_trade: 1회 매매 시 허용할 손실 비율 (기본 0.02 = 2%)
+            max_position_pct: 종목당 최대 투자 비율 (기본 0.20 = 20%)
+            min_position_amount: 최소 매수 금액 (너무 작은 주문 방지)
+            use_kelly: 켈리 공식 활성화 여부
+            kelly_multiplier: 켈리 배율 (0.5 = 하프켈리, 0.25 = 쿼터켈리)
+        """
+        self.risk_pct = risk_pct_per_trade
+        self.max_pos_pct = max_position_pct
+        self.min_amount = min_position_amount
+        self.use_kelly = use_kelly
+        self.kelly_mult = kelly_multiplier
+        
+        logger.info(
+            f"💰 RiskManager 초기화: 리스크{self.risk_pct*100}% | "
+            f"최대비중{self.max_pos_pct*100}% | 켈리{'ON' if use_kelly else 'OFF'}"
+        )
+
+    def calculate_volatility_atr(self, df: pd.DataFrame, period: int = 14) -> float:
+        """
+        ATR(Average True Range) 기반 변동성 계산
+        
+        Args:
+            df: OHLC 데이터프레임 (컬럼: open, high, low, close)
+            period: ATR 계산 기간 (기본 14)
+            
+        Returns:
+            현재가 대비 ATR 비율 (%)
+        """
+        try:
+            if df is None or len(df) < period:
+                logger.warning(f"⚠️ ATR 계산: 데이터 부족 -> 기본값 3.0% 리턴")
+                return 3.0
+            
+            # True Range 계산
+            df = df.copy()
+            df['tr'] = np.maximum(
+                df['high'] - df['low'],
+                np.maximum(
+                    np.abs(df['high'] - df['close'].shift()),
+                    np.abs(df['low'] - df['close'].shift())
+                )
+            )
+            
+            # ATR = TR의 이동평균
+            atr = df['tr'].rolling(window=period).mean().iloc[-1]
+            current_price = df['close'].iloc[-1]
+            
+            if current_price == 0:
+                return 3.0
+            
+            # 현재가 대비 ATR 비율 (%)
+            volatility_pct = (atr / current_price) * 100
+            
+            # 최소값 보정 (0.5% 미만은 0.5%로)
+            return max(round(volatility_pct, 2), 0.5)
+            
+        except Exception as e:
+            logger.error(f"❌ ATR 계산 에러: {e}")
+            return 3.0
+
+    def calculate_volatility_simple(self, candles: List[Dict], period: int = 10) -> float:
+        """
+        간단한 변동성 계산 (고저차 비율 평균)
+        
+        Args:
+            candles: 캔들 데이터 리스트 [{'high': , 'low': , 'close': }, ...]
+            period: 계산 기간 (기본 10일)
+            
+        Returns:
+            변동성 (%)
+        """
+        try:
+            if not candles or len(candles) < period:
+                return 3.0
+            
+            recent = candles[-period:]
+            volatility_sum = 0.0
+            
+            for candle in recent:
+                high = float(candle.get('high', 0))
+                low = float(candle.get('low', 0))
+                close = float(candle.get('close', 1))
+                
+                if close == 0:
+                    continue
+                
+                # (고가 - 저가) / 종가
+                volatility_sum += (high - low) / close
+            
+            avg_vol = (volatility_sum / len(recent)) * 100
+            return max(round(avg_vol, 2), 0.5)
+            
+        except Exception as e:
+            logger.error(f"❌ 변동성 계산 에러: {e}")
+            return 3.0
+
+    def get_position_size(
+        self,
+        stock_name: str,
+        current_balance: float,
+        volatility_pct: float = None,
+        df: pd.DataFrame = None,
+        kelly_fraction: float = None,
+        size_class: str = None,
+    ) -> int:
+        """
+        [메인 함수] 종목별 안전 매수 금액 계산
+        
+        Args:
+            stock_name: 종목명 (로깅용)
+            current_balance: 현재 예수금
+            volatility_pct: 변동성 (직접 제공 시)
+            df: OHLC 데이터프레임 (ATR 계산용)
+            kelly_fraction: 켈리 비율 (DB에서 계산한 값)
+            size_class: 대/중/소형 구분 ("대", "중", "소")
+            
+        Returns:
+            추천 매수 금액 (원)
+        """
+        try:
+            if current_balance <= 0:
+                logger.warning(f"⚠️ [{stock_name}] 예수금 0원 이하")
+                return 0
+            
+            # 1. 변동성 계산
+            if volatility_pct is None:
+                if df is not None and not df.empty:
+                    volatility_pct = self.calculate_volatility_atr(df)
+                else:
+                    logger.warning(f"⚠️ [{stock_name}] 변동성 데이터 없음 -> 기본값 3.0%")
+                    volatility_pct = 3.0
+            
+            # 2. 기본 리스크 금액 계산 (예수금 * 리스크 비율)
+            # 예: 1,000만 원 * 2% = 20만 원 (이 종목에서 최대 20만원까지 잃을 수 있음)
+            allowable_risk = current_balance * self.risk_pct
+            
+            # 3. 켈리 공식 적용 (쿼터 켈리/하프 켈리)
+            if self.use_kelly:
+                if kelly_fraction is not None and kelly_fraction > 0:
+                    # DB에서 계산한 켈리 비율 사용 (하프 켈리)
+                    base_position_pct = kelly_fraction * self.kelly_mult
+                    allowable_risk = current_balance * base_position_pct
+                    logger.info(f"🎲 [{stock_name}] 켈리 적용(DB): {base_position_pct*100:.1f}% (켈리={kelly_fraction*100:.1f}% × 배율={self.kelly_mult})")
+                else:
+                    # 켈리 비율이 없으면 쿼터 켈리 배율을 기본값으로 사용
+                    # 예: 리스크 1% × 쿼터 켈리 0.25 = 0.25% (더 보수적)
+                    base_position_pct = self.risk_pct * self.kelly_mult
+                    allowable_risk = current_balance * base_position_pct
+                    logger.info(f"🎲 [{stock_name}] 켈리 적용(기본): {base_position_pct*100:.1f}% (리스크={self.risk_pct*100}% × 쿼터켈리={self.kelly_mult})")
+            
+            # 4. 변동성 역가중으로 매수 금액 계산
+            # 공식: (허용 손실액) / (변동성 비율)
+            # 변동성 5% -> 20만 / 0.05 = 400만원 매수
+            # 변동성 10% -> 20만 / 0.10 = 200만원 매수
+            risk_ratio = volatility_pct / 100.0
+            calculated_amount = allowable_risk / risk_ratio
+            
+            # 5. 상한선 체크 (종목당 최대 비중)
+            max_limit = current_balance * self.max_pos_pct
+
+            if calculated_amount > max_limit:
+                final_amount = max_limit
+                note = f"(최대{self.max_pos_pct*100:.0f}% 제한)"
+            else:
+                final_amount = calculated_amount
+                note = "(변동성기반)"
+
+            # 5-2. 대형/소형 구간별 조정 (소형주는 포지션 축소)
+            if size_class == "소":
+                final_amount = int(final_amount * 0.7)
+                note = "(소형주 70%)"
+            elif size_class == "중":
+                final_amount = int(final_amount * 0.85)
+                note = "(중형주 85%)"
+            elif size_class == "대":
+                pass  # 대형주는 기존과 동일
+
+            # 6. 하한선 체크 (너무 작은 금액은 거래 안함)
+            if final_amount < self.min_amount:
+                logger.info(
+                    f"🚫 [{stock_name}] 계산 금액({final_amount:,.0f}원) < "
+                    f"최소금액({self.min_amount:,.0f}원) -> 매수 보류"
+                )
+                return 0
+            
+            logger.info(
+                f"💰 [{stock_name}] 예수금:{current_balance:,.0f}원 | "
+                f"변동성:{volatility_pct:.2f}% | 추천:{int(final_amount):,.0f}원 {note}"
+            )
+            
+            return int(final_amount)
+            
+        except Exception as e:
+            logger.error(f"❌ [{stock_name}] 포지션 사이즈 계산 실패: {e}")
+            return 0
+
+    def calculate_quantity(
+        self, 
+        current_price: float, 
+        target_amount: int,
+        fee_rate: float = 0.00015
+    ) -> int:
+        """
+        목표 금액을 현재가와 수수료 고려하여 수량으로 변환
+        
+        Args:
+            current_price: 현재 주가
+            target_amount: 목표 투자 금액
+            fee_rate: 수수료율 (기본 0.015%)
+            
+        Returns:
+            매수 가능 수량 (주)
+        """
+        try:
+            if current_price <= 0 or target_amount <= 0:
+                return 0
+            
+            # 수수료 고려 실제 매수 가능 금액
+            # 총비용 = 가격 * 수량 * (1 + 수수료율)
+            # 수량 = 목표금액 / (가격 * (1 + 수수료율))
+            max_buy_amount = target_amount / (1 + fee_rate)
+            quantity = int(max_buy_amount / current_price)
+            
+            if quantity < 1:
+                return 0
+            
+            # 예상 총 비용 계산 (확인용)
+            expected_cost = quantity * current_price * (1 + fee_rate)
+            
+            logger.debug(
+                f"💵 수량 계산: {current_price:,.0f}원 × {quantity}주 = "
+                f"예상비용 {expected_cost:,.0f}원 (목표: {target_amount:,.0f}원)"
+            )
+            
+            return quantity
+            
+        except Exception as e:
+            logger.error(f"❌ 수량 계산 에러: {e}")
+            return 0
diff --git a/scripts/copy_env_row_to_latest.py b/scripts/copy_env_row_to_latest.py
new file mode 100644
index 0000000..e69de29
diff --git a/update_env.py b/update_env.py
new file mode 100644
index 0000000..75d461c
--- /dev/null
+++ b/update_env.py
@@ -0,0 +1,145 @@
+#!/usr/bin/env python3
+"""
+환경변수 DB 업데이트 스크립트
+- 기존 최신 설정을 불러와서
+- 새로운 값으로 업데이트하고
+- 새 스냅샷으로 저장
+"""
+import sys
+from pathlib import Path
+
+SCRIPT_DIR = Path(__file__).resolve().parent
+sys.path.insert(0, str(SCRIPT_DIR))
+
+from database import TradeDB
+
+def update_env_config():
+    """환경변수 업데이트 (대화형)"""
+    db_path = SCRIPT_DIR / "quant_bot.db"
+    db = TradeDB(db_path=str(db_path))
+    
+    # 기존 최신 설정 불러오기
+    latest = db.get_latest_env()
+    if latest and latest.get("snapshot"):
+        current = latest["snapshot"]
+        print("📋 현재 설정:")
+        print(f"   (최신 스냅샷 ID: {latest['id']}, 생성일: {latest['created_at']})")
+        print()
+    else:
+        current = {}
+        print("⚠️ 기존 설정 없음 - 새로 생성합니다.")
+        print()
+    
+    # 업데이트할 값들
+    updates = {}
+    
+    print("=" * 60)
+    print("환경변수 업데이트")
+    print("=" * 60)
+    print("(값을 입력하지 않으면 기존 값 유지, 'skip' 입력 시 건너뜀)")
+    print()
+    
+    # 한투 API 설정
+    print("🔵 [한투 API 설정]")
+    val = input(f"KIS_APP_KEY [{current.get('KIS_APP_KEY', '')[:20]}...]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["KIS_APP_KEY"] = val
+    
+    val = input(f"KIS_APP_SECRET [{current.get('KIS_APP_SECRET', '')[:20]}...]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["KIS_APP_SECRET"] = val
+    
+    val = input(f"KIS_ACCOUNT_NO [{current.get('KIS_ACCOUNT_NO', '')}]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["KIS_ACCOUNT_NO"] = val
+    
+    val = input(f"KIS_ACCOUNT_CODE [{current.get('KIS_ACCOUNT_CODE', '01')}]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["KIS_ACCOUNT_CODE"] = val
+    
+    val = input(f"KIS_MOCK (true/false) [{current.get('KIS_MOCK', 'true')}]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["KIS_MOCK"] = val.lower()
+    
+    print()
+    
+    # Mattermost 설정
+    print("💬 [Mattermost 설정]")
+    val = input(f"MM_SERVER_URL [{current.get('MM_SERVER_URL', 'https://mattermost.hoonfam.org')}]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["MM_SERVER_URL"] = val
+    
+    val = input(f"MM_BOT_TOKEN_ [{current.get('MM_BOT_TOKEN_', '')[:20]}...]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["MM_BOT_TOKEN_"] = val
+    
+    val = input(f"MATTERMOST_CHANNEL (기본 채널 alias) [{current.get('MATTERMOST_CHANNEL', 'stock')}]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["MATTERMOST_CHANNEL"] = val
+    
+    val = input(f"KIS_SHORT_MM_CHANNEL (단타 봇 채널 alias) [{current.get('KIS_SHORT_MM_CHANNEL', '')}]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["KIS_SHORT_MM_CHANNEL"] = val
+    
+    val = input(f"KIS_LONG_MM_CHANNEL (롱타 봇 채널 alias) [{current.get('KIS_LONG_MM_CHANNEL', '')}]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["KIS_LONG_MM_CHANNEL"] = val
+    
+    print()
+    
+    # Gemini API 설정
+    print("🤖 [Gemini AI 설정]")
+    val = input(f"GEMINI_API_KEY [{current.get('GEMINI_API_KEY', '')[:20]}...]: ").strip()
+    if val and val.lower() != 'skip':
+        updates["GEMINI_API_KEY"] = val
+    
+    print()
+    
+    # 기존 값과 병합
+    new_snapshot = {**current, **updates}
+    
+    # 확인
+    print("=" * 60)
+    print("업데이트할 값:")
+    print("=" * 60)
+    for key, value in updates.items():
+        display_value = value[:30] + "..." if len(str(value)) > 30 else value
+        print(f"  {key}: {display_value}")
+    
+    print()
+    confirm = input("위 설정을 저장하시겠습니까? (y/n): ").strip().lower()
+    
+    if confirm != 'y':
+        print("❌ 취소되었습니다.")
+        db.close()
+        return
+    
+    # 새 스냅샷 저장
+    env_id = db.insert_env_snapshot(new_snapshot)
+    if env_id:
+        print(f"✅ 환경변수 저장 완료! (새 스냅샷 ID: {env_id})")
+        print()
+        print("💡 팁:")
+        print("   - 봇을 재시작하면 새 설정이 적용됩니다.")
+        print("   - mm_config.json 파일도 확인하세요:")
+        print("     {")
+        print('       "channels": {')
+        print('           "stock": "채널_ID",')
+        print('           "kis-short": "단타_채널_ID",')
+        print('           "kis-long": "롱타_채널_ID"')
+        print("       }")
+        print("     }")
+    else:
+        print("❌ 저장 실패!")
+    
+    db.close()
+
+if __name__ == "__main__":
+    try:
+        update_env_config()
+    except KeyboardInterrupt:
+        print("\n\n❌ 사용자 취소")
+    except Exception as e:
+        print(f"\n\n❌ 에러: {e}")
+        import traceback
+        traceback.print_exc()
diff --git a/update_env_short.py b/update_env_short.py
new file mode 100644
index 0000000..7c9c44c
--- /dev/null
+++ b/update_env_short.py
@@ -0,0 +1,137 @@
+#!/usr/bin/env python3
+"""
+단타 봇용 환경변수 DB 업데이트 스크립트
+- .env 파일의 단타 설정값을 DB에 저장
+"""
+import sys
+from pathlib import Path
+
+SCRIPT_DIR = Path(__file__).resolve().parent
+sys.path.insert(0, str(SCRIPT_DIR))
+
+from database import TradeDB
+
+def update_short_bot_env():
+    """단타 봇 환경변수 업데이트"""
+    db_path = SCRIPT_DIR / "quant_bot.db"
+    db = TradeDB(db_path=str(db_path))
+    
+    # 기존 최신 설정 불러오기
+    latest = db.get_latest_env()
+    if latest and latest.get("snapshot"):
+        current = latest["snapshot"]
+        print(f"📋 기존 설정 불러옴 (ID: {latest['id']})")
+    else:
+        current = {}
+        print("⚠️ 기존 설정 없음 - 새로 생성")
+    
+    # 단타 봇 설정값 (.env 23-140줄 기준)
+    short_bot_updates = {
+        # ========== 기본 거래 설정 ==========
+        "MAX_STOCKS": "7",                    # 최대 보유 종목 수
+        "STOP_LOSS_PCT": "-0.18",            # 종목별 손절 기준 (-18%)
+        "USE_SLOT_CAP": "true",              # 종목당 금액 상한(슬롯) 적용
+        "SLOT_CAP_PCT": "0.9",               # 슬롯 계산 시 예수금 반영 비율 (90%)
+        
+        # ========== 리스크 관리 (손실 한도) ==========
+        "USE_RISK_CHECK": "false",           # 일일 손실 한도 체크
+        "DAILY_STOP_LOSS_PCT": "-0.05",      # 일일 손실 한도 (-5%)
+        "CONSECUTIVE_LOSS_LIMIT": "7",       # 연속 손절 한도 (7회)
+        
+        # ========== 금지 종목 관리 (재매수 방지) ==========
+        "USE_BAN_SYSTEM": "true",            # 금지 종목 관리 시스템
+        "BAN_HOURS": "24",                   # 금지 시간 (24시간)
+        
+        # ========== 종목 필터링 (쓰레기 종목 제외) ==========
+        "USE_STOCK_FILTER": "true",          # 종목 필터링
+        
+        # ========== 작은 수익 보호 (30분 내) ==========
+        "USE_QUICK_PROFIT_PROTECTION": "true",  # 작은 수익 보호
+        
+        # ========== 리스크 관리 (Ver2 신규) ==========
+        "RISK_PCT_PER_TRADE": "0.015",       # 1회 거래 시 허용 손실 비율 (1.5%)
+        "MAX_POSITION_PCT": "0.20",          # 종목당 최대 투자 비중 (20%)
+        "MIN_POSITION_AMOUNT": "20000",       # 최소 매수 금액 (2만원)
+        
+        # ========== 켈리 공식 (Ver2 신규) ==========
+        "USE_KELLY": "false",                # 하프 켈리 공식 활성화
+        
+        # ========== ML 승률 예측 (Ver2 신규 - 실험적!) ==========
+        "USE_ML_SIGNAL": "false",            # ML 기반 매수 신호 필터링
+        "ML_MIN_PROBABILITY": "0.57",        # ML 승률 임계값 (57%)
+        
+        # ========== 뉴스 AI 분석 (Ver2 신규 - 참고용!) ==========
+        "USE_NEWS_ANALYSIS": "false",        # 뉴스 AI 분석 활성화
+        "NEWS_ANALYSIS_HOUR": "9",            # 뉴스 분석 시간 (9시)
+        "NEWS_MAX_COUNT": "5",               # 크롤링할 뉴스 개수 (5개)
+        
+        # ========== 랜덤 분할 매수 (Dual 방식 - 승률 최적화!) ==========
+        "USE_RANDOM_SPLIT": "true",          # 랜덤 분할 매수 활성화
+        
+        # ========== TWAP 분할 매수 (Ver2 신규) ==========
+        "USE_TWAP": "false",                 # TWAP 분할 매수 활성화
+        "TWAP_MIN_SPLIT": "500000",          # 1회 최소 주문 금액 (50만원)
+        "TWAP_MAX_SPLIT": "2000000",         # 1회 최대 주문 금액 (200만원)
+        "TWAP_MIN_DELAY": "30",              # 분할 매수 간 최소 딜레이 (초)
+        "TWAP_MAX_DELAY": "180",             # 분할 매수 간 최대 딜레이 (초)
+        
+        # ========== 디버그용 장 상태 강제 오픈 ==========
+        "FORCE_MARKET_OPEN": "true",         # 장 상태에 관계없이 항상 매매 로직 실행 (테스트용!)
+        
+        # ========== 매수 전략 파라미터 ==========
+        "RSI_OVERHEAT_THRESHOLD": "78",      # RSI 과열 기준 (진입 보류 기준)
+        "SHOULDER_CUT_PCT": "0.03",          # 어깨 매도 기준 (고점 대비 하락률)
+        
+        # ========== 🚨 피뢰침 방지 필터 (강화!) ==========
+        "HIGH_PRICE_CHASE_THRESHOLD": "0.96",  # 일일 최고가 추격 매수 방지 기준
+        "MAX_DAILY_CHANGE_PCT": "18.0",      # 당일 최대 변동폭 (%)
+        "MA20_MAX_ABOVE_PCT": "8.8",         # 20선 과열 방지: MA20 대비 이 % 초과 위면 매수 스킵
+        
+        "MIN_RECOVERY_RATIO": "0.32",        # 꼬리 잡기 최소 회복 비율
+        "MAX_RECOVERY_RATIO": "1.15",        # 꼬리 잡기 최대 회복 비율
+        "CANDLE_OPEN_PRICE_BUFFER": "0.98",  # 시가 대비 현재가 버퍼 (음봉 꼬리 위험 방지)
+        "VOLUME_AVG_MULTIPLIER": "0.50",     # 거래량 평균 대비 배율
+        
+        "INTRADAY_INVESTOR_NET_BUY_THRESHOLD": "-1000",  # 장중 투자자 순매수 기준
+        
+        # ========== ATR 배율 설정 ==========
+        "STOP_ATR_MULTIPLIER_TAIL": "2.5",   # TAIL_CATCH_3M 전략 손절가 (ATR × 2.5)
+        "TARGET_ATR_MULTIPLIER_TAIL": "8.0", # TAIL_CATCH_3M 전략 목표가 (ATR × 8.0)
+        
+        # 단타 봇 전용 설정 (기존 값 유지 또는 기본값)
+        "TAKE_PROFIT_PCT": current.get("TAKE_PROFIT_PCT", "0.05"),  # 익절 기준 (5%)
+        "MIN_DROP_RATE": current.get("MIN_DROP_RATE", "0.03"),      # 최소 낙폭 (3%)
+        "MIN_RECOVERY_RATIO_SHORT": current.get("MIN_RECOVERY_RATIO_SHORT", "0.5"),  # 최소 회복 비율 (50%)
+    }
+    
+    # 기존 값과 병합 (단타 봇 설정으로 덮어쓰기)
+    new_snapshot = {**current, **short_bot_updates}
+    
+    # 새 스냅샷 저장
+    env_id = db.insert_env_snapshot(new_snapshot)
+    if env_id:
+        print(f"✅ 단타 봇 환경변수 저장 완료! (새 스냅샷 ID: {env_id})")
+        print()
+        print("📋 저장된 주요 설정:")
+        print(f"   - MAX_STOCKS: {short_bot_updates['MAX_STOCKS']}")
+        print(f"   - STOP_LOSS_PCT: {short_bot_updates['STOP_LOSS_PCT']}")
+        print(f"   - USE_RANDOM_SPLIT: {short_bot_updates['USE_RANDOM_SPLIT']}")
+        print(f"   - RSI_OVERHEAT_THRESHOLD: {short_bot_updates['RSI_OVERHEAT_THRESHOLD']}")
+        print(f"   - FORCE_MARKET_OPEN: {short_bot_updates['FORCE_MARKET_OPEN']} (테스트용!)")
+        print()
+        print("💡 팁:")
+        print("   - 봇을 재시작하면 새 설정이 적용됩니다.")
+        print("   - FORCE_MARKET_OPEN=true는 테스트용이므로 실전에서는 false로 변경하세요.")
+    else:
+        print("❌ 저장 실패!")
+    
+    db.close()
+    return env_id
+
+if __name__ == "__main__":
+    try:
+        update_short_bot_env()
+    except Exception as e:
+        print(f"\n\n❌ 에러: {e}")
+        import traceback
+        traceback.print_exc()
diff --git a/update_env_simple.py b/update_env_simple.py
new file mode 100644
index 0000000..86ae4ce
--- /dev/null
+++ b/update_env_simple.py
@@ -0,0 +1,83 @@
+#!/usr/bin/env python3
+"""
+환경변수 DB 업데이트 스크립트 (간단 버전)
+- 딕셔너리로 직접 값을 넣어서 업데이트
+"""
+import sys
+from pathlib import Path
+
+SCRIPT_DIR = Path(__file__).resolve().parent
+sys.path.insert(0, str(SCRIPT_DIR))
+
+from database import TradeDB
+
+def update_env(updates):
+    """
+    환경변수 업데이트
+    
+    Args:
+        updates: 업데이트할 환경변수 딕셔너리
+            예: {
+                "KIS_APP_KEY": "your_app_key",
+                "KIS_APP_SECRET": "your_app_secret",
+                "MM_BOT_TOKEN_": "your_token",
+                ...
+            }
+    """
+    db_path = SCRIPT_DIR / "quant_bot.db"
+    db = TradeDB(db_path=str(db_path))
+    
+    # 기존 최신 설정 불러오기
+    latest = db.get_latest_env()
+    if latest and latest.get("snapshot"):
+        current = latest["snapshot"]
+        print(f"📋 기존 설정 불러옴 (ID: {latest['id']})")
+    else:
+        current = {}
+        print("⚠️ 기존 설정 없음 - 새로 생성")
+    
+    # 기존 값과 병합
+    new_snapshot = {**current, **updates}
+    
+    # 새 스냅샷 저장
+    env_id = db.insert_env_snapshot(new_snapshot)
+    if env_id:
+        print(f"✅ 환경변수 저장 완료! (새 스냅샷 ID: {env_id})")
+        print(f"   업데이트된 키: {', '.join(updates.keys())}")
+    else:
+        print("❌ 저장 실패!")
+    
+    db.close()
+    return env_id
+
+if __name__ == "__main__":
+    # 여기에 업데이트할 값들을 딕셔너리로 넣으세요
+    my_updates = {
+        # 한투 API 설정
+
+        # "KIS_APP_KEY_REAL": "PSUbfJUp3eiA0rthF1GSK8yWI7dD7GvXMPQL",  # 여기에 앱키 입력
+        # "KIS_APP_SECRET_REAL": "DzG04RbksnUMROslum/2DliJiVZAdeSgwUNHKSbFehMmD2WKGVUeSd0N1B8LY947W/aNtEmU8pdkvKTFnVX1u68DvCj7cvEtlJc++wCUeaRD3z1Ov48b5PLsPiWvwE+pMd0pEl6jmFg0J6td1TidugAsZtEQ3GUBimyQyDSgw3jkdbnM390=",
+        # "KIS_APP_KEY_MOCK": "PSdfKtsMihgC9tLiUr2XISscuR3fHxl6kvmV",  # 여기에 앱키 입력`
+        # "KIS_APP_SECRET_MOCK": "Ip+XZrZcoz11thgDD40XS8i6R1AalYkKFZwg2w8+ZMulVKN8rJVXiqGONxc4EYxw1S3TgOcx7fSldDc6EGq63bprfbgHwKWxstu29ZmLAtRNU0oFqV7e9vCOfgiWxrfnCqwcihoS7ovmza9+Ylqd8/EtjFGNmhQHWocyTAm8kdp5IG6tFtc=",  # 여기에 앱시크릿 입력
+
+        # "KIS_ACCOUNT_NO_REAL": "44030801",
+        # "KIS_ACCOUNT_NO_MOCK": "50166974",
+        # "KIS_ACCOUNT_NO_MOCK": "44030801",
+        # "KIS_ACCOUNT_NO_MOCK": "50169256",
+        # "KIS_ACCOUNT_CODE_REAL": "01",
+        # "KIS_ACCOUNT_CODE_MOCK": "01",
+
+        "MIN_RECOVERY_RATIO": 0.35,
+        "MIN_DROP_RATE": 0.02,
+
+    }
+    
+    # 빈 값 제거 (업데이트하지 않음)
+    my_updates = {k: v for k, v in my_updates.items() if v}
+    
+    if not my_updates:
+        print("⚠️ 업데이트할 값이 없습니다.")
+        print("   update_env_simple.py 파일을 열어서 my_updates 딕셔너리에 값을 입력하세요.")
+        sys.exit(1)
+    
+    update_env(my_updates)