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kis_bot/tail_engine.py
Hwang f61c471aac 브랜치 분리 방식: A / B / C
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작업 시점: 지금 / 운영 데이터 1~2일 쌓고 / 주말
2026-05-05 21:04:17 +09:00

668 lines
28 KiB
Python

#!/usr/bin/env python3
"""
tail_engine.py — 꼬리잡기 백테스트·실매매 공통 엔진
====================================================
백테스트(backtest_web), 파라미터 탐색(tail_param_search), 실매매(kis_short_ver3)가
모두 동일한 진입/청산 계산식과 '고급 방어 로직'을 쓰도록 통합된 단일 소스 엔진.
■ 엔진 공통 로직 (백테·실매 동일)
매수: 당일 낙폭(drop), 회복률(rec_day), 망치봉 꼬리(tail_ratio/tail_pct), RSI < rsi_threshold,
고점추격 방지, 시간대/쿨다운, + [V3 추가] MA20 필터, 일일 변동폭(피뢰침) 방어, 최소 가격.
매도: ATR 기반 동적 손절/목표가, 어깨컷(trailing), 금액손실컷, 최소 보유 시간, 장마감 강제 청산.
"""
from datetime import datetime
from typing import List, Dict, Any, Optional
def _slot_key(candle_time: str, scan_interval_min: int = 1) -> str:
"""봉 시각을 N분 단위 슬롯 키로 변환.
신봇 기준: caller 가 ``TradeDBExt.get_universe_by_candle_time()`` 으로
1분 캔들 시각 키 dict 를 만들어 주입하므로 기본값은 1분(= passthrough).
``--fallback-universe`` 시뮬레이션은 caller 가 ``scan_interval_min=5`` 를
명시해 5분 버킷팅으로 사용.
"""
date = candle_time[:8]
hm = int(candle_time[8:12])
total_min = (hm // 100) * 60 + (hm % 100)
slot_min = (total_min // scan_interval_min) * scan_interval_min
slot_hm = (slot_min // 60) * 100 + (slot_min % 60)
return date + str(slot_hm).zfill(4)
def get_tail_defaults_from_db(db=None) -> Dict[str, Any]:
"""
env_config 최신 행에서 꼬리잡기 관련 값과 고급 방어 로직 값을 전부 로드.
백테스트·파라미터서치·실매매가 동일 DB 값을 쓰도록 단일 소스.
"""
own_db = None
try:
if db is None:
from database import TradeDB
own_db = TradeDB()
db = own_db
row = db.conn.execute("SELECT * FROM env_config ORDER BY id DESC LIMIT 1").fetchone()
if row:
r = dict(row)
# 기본 전략 파라미터
min_drop = float(r.get("MIN_DROP_RATE") or 0.03)
min_rec = float(r.get("MIN_RECOVERY_RATIO_SHORT") or 0.5)
tail_ratio = float(r.get("TAIL_RATIO_MIN") or 1.5)
tail_pct = float(r.get("TAIL_PCT_MIN") or 0.003)
sl_pct = abs(float(r.get("STOP_LOSS_PCT") or -0.03))
tp_pct = float(r.get("TAKE_PROFIT_PCT") or 0.05)
shoulder_high = float(r.get("SHOULDER_MIN_HIGH_PCT") or 0.015)
shoulder_cut = float(r.get("SHOULDER_CUT_PCT") or 0.03)
cooldown_sec = int(float(r.get("REENTRY_COOLDOWN_SEC") or 900))
rsi_period = int(r.get("RSI_PERIOD") or 14)
rsi_threshold = float(r.get("RSI_OVERHEAT_THRESHOLD") or 78)
max_rec_3m = float(r.get("MAX_RECOVERY_RATIO_3M") or 0.8)
high_chase = float(r.get("HIGH_PRICE_CHASE_THRESHOLD") or 0.96)
time_start = int(r.get("TAIL_TIME_START") or r.get("TIME_START") or 930)
time_end = int(r.get("TAIL_TIME_END") or r.get("TIME_END") or 1500)
max_daily = int(r.get("MAX_DAILY_TAIL") or r.get("MAX_STOCKS") or 3)
# 고급 방어 필터 파라미터 (V3 통합)
min_price = float(r.get("MIN_PRICE_TAIL") or 1000.0)
max_daily_change = float(r.get("MAX_DAILY_CHANGE_PCT") or 20.0)
ma20_max_above = float(r.get("MA20_MAX_ABOVE_PCT") or 3.0)
stop_atr_mult = float(r.get("STOP_ATR_MULTIPLIER_TAIL") or 2.5)
target_atr_mult = float(r.get("TARGET_ATR_MULTIPLIER_TAIL") or 8.0)
max_loss_krw = int(r.get("MAX_LOSS_PER_TRADE_KRW") or 200000)
_min_drop_loss = r.get("MIN_DROP_PCT_FOR_LOSS_CUT")
min_drop_pct_for_loss_cut = 0.015 # 기본 1.5%: 이 하락률 미만이면 금액손실컷 미발동(흔들림 방지)
if _min_drop_loss not in (None, ""):
v = float(_min_drop_loss)
min_drop_pct_for_loss_cut = v / 100.0 if v >= 1 else v
risk_pct = float(r.get("RISK_PCT_PER_TRADE") or 0.01)
kelly_mult = float(r.get("KELLY_MULTIPLIER") or 0.25)
min_hold_sec = float(r.get("MIN_HOLD_AFTER_BUY_SEC") or 30.0)
capital = float(r.get("BACKTEST_CAPITAL") or 100000000.0) # 백테스트용 기본 자본
else:
min_drop, min_rec = 0.03, 0.5
tail_ratio, tail_pct = 1.5, 0.003
sl_pct, tp_pct = 0.03, 0.05
shoulder_high, shoulder_cut = 0.015, 0.03
cooldown_sec, rsi_period, rsi_threshold = 900, 14, 78.0
max_rec_3m, high_chase = 0.8, 0.96
time_start, time_end, max_daily = 930, 1500, 3
min_price, max_daily_change, ma20_max_above = 1000.0, 20.0, 3.0
stop_atr_mult, target_atr_mult = 2.5, 8.0
max_loss_krw, risk_pct, kelly_mult = 200000, 0.01, 0.25
min_drop_pct_for_loss_cut = 0.015
min_hold_sec, capital = 30.0, 100000000.0
except Exception:
min_drop, min_rec = 0.03, 0.5
tail_ratio, tail_pct = 1.5, 0.003
sl_pct, tp_pct = 0.03, 0.05
shoulder_high, shoulder_cut = 0.015, 0.03
cooldown_sec, rsi_period, rsi_threshold = 900, 14, 78.0
max_rec_3m, high_chase = 0.8, 0.96
time_start, time_end, max_daily = 930, 1500, 3
min_price, max_daily_change, ma20_max_above = 1000.0, 20.0, 3.0
stop_atr_mult, target_atr_mult = 2.5, 8.0
max_loss_krw, risk_pct, kelly_mult = 200000, 0.01, 0.25
min_drop_pct_for_loss_cut = 0.015
min_hold_sec, capital = 30.0, 100000000.0
finally:
if own_db is not None:
try:
own_db.close()
except Exception:
pass
return {
"min_drop_rate": min_drop,
"min_recovery_ratio": min_rec,
"max_rec_3m": max_rec_3m,
"tail_ratio_min": tail_ratio,
"tail_pct_min": tail_pct,
"sl_pct": sl_pct,
"tp_pct": tp_pct,
"shoulder_min_high": shoulder_high,
"shoulder_cut_pct": shoulder_cut,
"rsi_period": rsi_period,
"rsi_threshold": rsi_threshold,
"high_chase_thr": high_chase,
"cooldown_min": cooldown_sec // 60,
"time_start_hm": time_start,
"time_end_hm": time_end,
"max_daily": max_daily,
# 고급 방어 파라미터 반환
"min_price": min_price,
"max_daily_change": max_daily_change,
"ma20_max_above": ma20_max_above,
"stop_atr_mult": stop_atr_mult,
"target_atr_mult": target_atr_mult,
"max_loss_krw": max_loss_krw,
"min_drop_pct_for_loss_cut": min_drop_pct_for_loss_cut,
"risk_pct": risk_pct,
"kelly_mult": kelly_mult,
"min_hold_sec": min_hold_sec,
"capital": capital,
}
def compute_rsi_series(closes: List[float], period: int = 14) -> List[Optional[float]]:
"""RSI 시리즈 (Wilder 스무딩)."""
rsi_list: List[Optional[float]] = [None] * len(closes)
if len(closes) < period + 1:
return rsi_list
deltas = [closes[i] - closes[i - 1] for i in range(1, len(closes))]
gains = [max(d, 0) for d in deltas]
losses = [max(-d, 0) for d in deltas]
avg_gain = sum(gains[:period]) / period
avg_loss = sum(losses[:period]) / period
for i in range(period, len(closes)):
idx = i - 1
if i > period:
avg_gain = (avg_gain * (period - 1) + gains[idx]) / period
avg_loss = (avg_loss * (period - 1) + losses[idx]) / period
rs = avg_gain / avg_loss if avg_loss > 0 else float("inf")
rsi_val = 100 - (100 / (1 + rs)) if avg_loss > 0 else 100.0
rsi_list[i] = rsi_val
return rsi_list
def compute_sma_series(closes: List[float], period: int = 20) -> List[Optional[float]]:
"""단순 이동평균(SMA) 계산기 (엔진 내부용)."""
sma_list: List[Optional[float]] = [None] * len(closes)
if len(closes) < period:
return sma_list
running_sum = sum(closes[:period])
sma_list[period - 1] = running_sum / period
for i in range(period, len(closes)):
running_sum += closes[i] - closes[i - period]
sma_list[i] = running_sum / period
return sma_list
def compute_atr_series(candles: List[Dict], period: int = 14) -> List[Optional[float]]:
"""ATR(Average True Range) 변동성 지표 계산기 (엔진 내부용)."""
atr_list: List[Optional[float]] = [None] * len(candles)
if len(candles) < period + 1:
return atr_list
trs = [0.0] * len(candles)
for i in range(1, len(candles)):
hi = float(candles[i]["high"])
lo = float(candles[i]["low"])
prev_cl = float(candles[i - 1]["close"])
trs[i] = max(hi - lo, abs(hi - prev_cl), abs(lo - prev_cl))
# ATR = SMA of TR
running_sum = sum(trs[1:period+1])
atr_list[period] = running_sum / period
for i in range(period + 1, len(candles)):
running_sum += trs[i] - trs[i - period]
atr_list[i] = running_sum / period
return atr_list
def _t2dt(t: str) -> datetime:
"""candle_time 문자열 → datetime."""
return datetime.strptime(t, "%Y%m%d%H%M")
def check_buy_signal_live(
candles: List[Dict],
params: Dict[str, Any],
state: Dict[str, Any],
) -> tuple:
"""
실시간: 마지막 봉이 백테스트(run_tail_backtest)와 동일한 꼬리잡기 매수 조건을 만족하는지 판단.
[V3 통합]: MA20, 피뢰침, 최소가격 필터 등 고급 방어 로직 엔진 내장.
candles: 3분봉 리스트 (candle_time, open, high, low, close, volume)
state: { "last_exit_dt": datetime|None, "daily_cnt": int }
반환: (reject_reason, reject_msg, signal_dict)
"""
if len(candles) < 20: # MA20 계산을 위해 최소 20봉 필요
return ("탈락-데이터", f"봉 수 부족 (len={len(candles)} < 20)", None)
i = len(candles) - 1
c = candles[i]
day = c["candle_time"][:8]
hm = int(c["candle_time"][8:12])
op = float(c["open"])
hi = float(c["high"])
lo = float(c["low"])
cl = float(c["close"])
# 엔진 파라미터 로드
min_drop_rate = float(params.get("min_drop_rate", 0.03))
min_recovery_ratio = float(params.get("min_recovery_ratio", 0.5))
max_rec_3m = float(params.get("max_rec_3m", 0.8))
tail_ratio_min = float(params.get("tail_ratio_min", 1.5))
tail_pct_min = float(params.get("tail_pct_min", 0.003))
rsi_period = int(params.get("rsi_period", 14))
rsi_threshold = float(params.get("rsi_threshold", 78))
high_chase_thr = float(params.get("high_chase_thr", 0.96))
time_start_hm = int(params.get("time_start_hm", 930))
time_end_hm = int(params.get("time_end_hm", 1500))
cooldown_min = float(params.get("cooldown_min", 15))
max_daily = int(params.get("max_daily", 3))
# 방어 로직 파라미터
min_price = float(params.get("min_price", 1000.0))
max_daily_change = float(params.get("max_daily_change", 20.0))
ma20_max_above = float(params.get("ma20_max_above", 3.0))
if hm < time_start_hm or hm > time_end_hm:
return (None, None, None) # 시간대 탈락
if state.get("daily_cnt", 0) >= max_daily:
return (None, None, None)
last_exit_dt = state.get("last_exit_dt")
if last_exit_dt is not None:
elapsed = (_t2dt(c["candle_time"]) - last_exit_dt).total_seconds() / 60
if elapsed < cooldown_min:
return (None, None, None)
if cl <= 0 or cl < min_price:
return ("탈락-가격", f"현재가 부적절 (현재 {cl:,.0f}원, 최소 {min_price:,.0f}원)", None)
# 당일 누적 OHLC 및 피뢰침 검사
running_open = op
running_high = hi
running_low = lo if lo > 0 else hi
for j in range(i - 1, -1, -1):
if candles[j]["candle_time"][:8] != day:
break
running_open = float(candles[j]["open"])
running_high = max(running_high, float(candles[j]["high"]))
lj = float(candles[j]["low"])
if lj > 0:
running_low = min(running_low, lj)
if cl <= 0 or running_open <= 0:
return (None, None, None)
# 일일 변동폭(피뢰침) 검사
if running_low > 0:
range_change_pct = (running_high - running_low) / running_low * 100
if range_change_pct > max_daily_change:
return ("탈락-피뢰침 급등주", f"일일 변동폭 {range_change_pct:.1f}% > {max_daily_change:.0f}%", None)
# 낙폭 검사
drop = (running_open - running_low) / running_open
if drop < min_drop_rate:
return (
"탈락-낙폭",
f"낙폭 {drop*100:.2f}% < {min_drop_rate*100:.1f}% (시가 {running_open:,.0f} → 저점 {running_low:,.0f})",
None,
)
# 회복률 검사
day_range = running_high - running_low
rec_day = (cl - running_low) / day_range if day_range > 0 else 0
if rec_day < min_recovery_ratio:
return (
"탈락-회복률",
f"회복률 {rec_day*100:.1f}% < {min_recovery_ratio*100:.0f}% (저점 {running_low:,.0f} → 현재 {cl:,.0f})",
None,
)
# 망치봉 꼬리 검사 (최대 3봉 전까지 탐색)
body_top = max(op, cl)
body_bot = min(op, cl)
body_len = body_top - body_bot if body_top > body_bot else 1.0
tail_len = body_bot - lo if lo > 0 else 0.0
lo_use = lo
if tail_len <= 0:
for j in range(i - 1, max(i - 4, rsi_period), -1):
prev = candles[j]
o2, c2, l2 = float(prev["open"]), float(prev["close"]), float(prev["low"])
if l2 <= 0:
continue
bt2, bb2 = max(o2, c2), min(o2, c2)
bl2 = bt2 - bb2 if bt2 > bb2 else 1.0
tl2 = bb2 - l2
if tl2 > 0:
tail_len, body_len, lo_use = tl2, bl2, l2
break
tail_ratio = tail_len / body_len if body_len > 0 else 0
tail_pct = tail_len / lo_use if lo_use > 0 and tail_len > 0 else 0.0
if tail_ratio < tail_ratio_min or tail_pct < tail_pct_min:
return (
"탈락-꼬리",
f"꼬리비율 {tail_ratio:.2f} (기준 {tail_ratio_min}) 또는 꼬리% {tail_pct*100:.2f}% (기준 {tail_pct_min*100:.2f}%)",
None,
)
# 3분봉 내 회복 위치 상한 검사
c_range = hi - lo if hi > lo else 0
rec_3m = (cl - lo) / c_range if c_range > 0 else 0
if not (min_recovery_ratio <= rec_3m <= max_rec_3m):
return (
"탈락-회복3분",
f"3분봉 회복률 {rec_3m*100:.1f}% (기준 {min_recovery_ratio*100:.0f}~{max_rec_3m*100:.0f}%)",
None,
)
# 고점 추격 방지
if cl >= running_high * high_chase_thr:
return (
"탈락-피뢰침 고점추격",
f"현재가 {cl:,.0f} ≥ 고점대비 {high_chase_thr*100:.0f}%",
None,
)
# RSI 검사
closes = [float(x["close"]) for x in candles]
rsis = compute_rsi_series(closes, rsi_period)
rsi_val = rsis[i] if i < len(rsis) else None
if rsi_val is None or rsi_val >= rsi_threshold:
return (
"탈락-RSI",
(f"RSI {rsi_val:.1f}" if rsi_val is not None else "RSI None") + f"{rsi_threshold:.0f}",
None,
)
# MA20 방어 로직 (역배열 및 이격도 과열 방지)
ma20 = sum(closes[i-19:i+1]) / 20.0
if cl < ma20:
return ("탈락-MA20", f"현재가 {cl:,.0f} < MA20 {ma20:,.0f} (역배열)", None)
if ma20 > 0 and cl > ma20 * (1 + ma20_max_above / 100):
return ("탈락-MA20초과", f"MA20 대비 {ma20_max_above:.0f}% 이격 초과", None)
return (
None,
None,
{"signal": True, "tail_ratio": tail_ratio, "tail_pct": tail_pct, "recovery_pos": rec_3m, "rsi_val": rsi_val, "atr_calc_val": None},
)
def check_sell_signal_live(
position: Dict[str, Any],
current_candle: Dict[str, Any],
params: Dict[str, Any],
is_eod: bool = False,
) -> Optional[tuple]:
"""
실시간 및 백테스트 공통 청산 조건.
[V3 통합]: 금액손실컷, 어깨컷, 최소 보유 시간 검사 추가.
position: entry_price, entry_time(YYYYMMDDHHMM), stop, target, max_price, qty
current_candle: high, low, close, candle_time
반환: (reason_str, exit_price) 또는 None
"""
shoulder_min_high = float(params.get("shoulder_min_high", 0.015))
shoulder_cut_pct = float(params.get("shoulder_cut_pct", 0.03))
max_loss_krw = int(params.get("max_loss_krw", 200000))
min_hold_sec = float(params.get("min_hold_sec", 30.0))
hi = float(current_candle.get("high", current_candle["close"]))
lo = float(current_candle.get("low", current_candle["close"]))
cl = float(current_candle["close"])
candle_time = current_candle.get("candle_time", "")
max_p = max(position["max_price"], hi)
ep = position["entry_price"]
stop = position["stop"]
target = position["target"]
qty = position.get("qty", 1) # 백테스트 시 동적 계산된 수량
# 최소 보유 시간 검사 (너무 짧으면 청산 무시)
if candle_time and position["entry_time"]:
try:
entry_dt = _t2dt(position["entry_time"])
curr_dt = _t2dt(candle_time)
if (curr_dt - entry_dt).total_seconds() < min_hold_sec:
return None
except Exception:
pass
reason = None
exit_price = cl
profit_val = (lo - ep) * qty # 최악의 경우(저가) 기준 손실 평가
drop_pct = (ep - lo) / ep if ep > 0 else 0 # 매수가 대비 하락률 (흔들림/슬리피지 수준이면 미발동 위해 사용)
min_drop_pct = float(params.get("min_drop_pct_for_loss_cut", 0.015))
# 1순위: 금액 손실컷 방어 — 손실 금액이 한도 초과 **이면서** 하락률이 최소값 이상일 때만 발동
# (슬리피지/흔들림만으로 20만원 도달 시 어깨컷 기회 전에 잘리는 것 방지)
if profit_val <= -max_loss_krw and drop_pct >= min_drop_pct:
reason = f"금액손실컷"
exit_price = ep - (max_loss_krw / qty) if qty > 0 else lo
# 2순위: 동적 손절선
elif lo > 0 and lo <= stop:
reason = "손절"
exit_price = stop
# 3순위: 동적 익절선
elif hi >= target:
reason = "익절"
exit_price = target
# 4순위: 어깨 컷 (Trailing Stop)
elif max_p >= ep * (1 + shoulder_min_high) and cl <= max_p * (1 - shoulder_cut_pct):
reason = "어깨컷"
exit_price = cl
# 5순위: 장 마감 강제 청산
elif reason is None and is_eod:
reason = "장마감"
exit_price = cl
if reason:
return (reason, exit_price)
return None
def run_tail_backtest(
candles_by_code: Dict[str, List[Dict]],
params: Dict[str, Any],
universe_by_slot: Optional[Dict[str, List[str]]] = None,
) -> List[Dict]:
"""
백테스트 1회 실행. (backtest_web 및 tail_param_search 호출용)
[V3 통합]: ATR 기반 동적 목표/손절, Kelly/리스크 비율 기반 포지션 사이징을 백테스트에 완벽 적용.
universe_by_slot이 주어지면 5분마다 해당 슬롯의 후보 종목에서만 매수 검사 (유니버스 히스토리 풀백).
"""
# 파라미터 준비
min_drop_rate = float(params.get("min_drop_rate", 0.03))
min_recovery_ratio = float(params.get("min_recovery_ratio", 0.5))
max_rec_3m = float(params.get("max_rec_3m", 0.8))
tail_ratio_min = float(params.get("tail_ratio_min", 1.5))
tail_pct_min = float(params.get("tail_pct_min", 0.003))
shoulder_min_high = float(params.get("shoulder_min_high", 0.015))
shoulder_cut_pct = float(params.get("shoulder_cut_pct", 0.03))
rsi_period = int(params.get("rsi_period", 14))
rsi_threshold = float(params.get("rsi_threshold", 78))
high_chase_thr = float(params.get("high_chase_thr", 0.96))
time_start_hm = int(params.get("time_start_hm", 930))
time_end_hm = int(params.get("time_end_hm", 1500))
cooldown_min = float(params.get("cooldown_min", 15))
max_daily = int(params.get("max_daily", 3))
# 방어 로직 (동적 계산용)
stop_atr_mult = float(params.get("stop_atr_mult", 2.5))
target_atr_mult = float(params.get("target_atr_mult", 8.0))
max_loss_krw = int(params.get("max_loss_krw", 200000))
risk_pct = float(params.get("risk_pct", 0.01))
kelly_mult = float(params.get("kelly_mult", 0.25))
capital = float(params.get("capital", 100000000.0))
static_sl_pct = abs(float(params.get("sl_pct", 0.03)))
all_trades: List[Dict] = []
for code, candles in candles_by_code.items():
if len(candles) < rsi_period + 5:
continue
# 벡터 연산으로 지표 선행 계산 (백테스트 속도 최적화)
closes = [float(c["close"]) for c in candles]
rsis = compute_rsi_series(closes, rsi_period)
ma20s = compute_sma_series(closes, 20)
atrs = compute_atr_series(candles, 14)
position = None
last_exit_dt: Dict[str, datetime] = {}
daily_cnt: Dict[str, int] = {}
cur_day = None
running_open, running_high, running_low = 0.0, 0.0, 0.0
i = rsi_period + 1
while i < len(candles):
c = candles[i]
day = c["candle_time"][:8]
hm = int(c["candle_time"][8:12])
op = float(c["open"])
hi = float(c["high"])
lo = float(c["low"])
cl = float(c["close"])
# 일일 변수 초기화 및 갱신
if day != cur_day:
cur_day = day
running_open = op
running_high = hi
running_low = lo if lo > 0 else hi
else:
running_high = max(running_high, hi)
if lo > 0:
running_low = min(running_low, lo)
is_eod = (i == len(candles) - 1) or (candles[i + 1]["candle_time"][:8] != day)
# ── 1. 청산 검사 (포지션 보유 중일 때) ──
if position is not None:
max_p = max(position["max_price"], hi)
position["max_price"] = max_p
cur_c_info = {"high": hi, "low": lo, "close": cl, "candle_time": c["candle_time"]}
res = check_sell_signal_live(position, cur_c_info, params, is_eod=is_eod)
if res:
reason, exit_price = res
all_trades.append({
"code": code,
"entry_time": position["entry_time"],
"exit_time": c["candle_time"],
"entry": round(position["entry_price"]),
"exit": round(exit_price),
"pnl": 0, # 후처리 로직(웹/서치)에서 qty와 세금 곱해서 갱신됨
"reason": reason,
"hold_min": 0,
})
last_exit_dt[day] = _t2dt(c["candle_time"])
daily_cnt[day] = daily_cnt.get(day, 0) + 1
position = None
i += 1
continue
# ── 2. 매수 검사 (포지션 없을 때, 유니버스 시뮬레이션 시 해당 슬롯 후보만) ──
if universe_by_slot is not None:
# 신봇 기본: 1분봉 == 슬롯 키 (TradeDBExt.get_universe_by_candle_time 키 포맷).
slot_key = _slot_key(c["candle_time"], params.get("scan_interval_min", 1))
if code not in universe_by_slot.get(slot_key, []):
i += 1
continue
if cl <= 0 or running_open <= 0 or hm < time_start_hm or hm > time_end_hm:
i += 1
continue
if daily_cnt.get(day, 0) >= max_daily:
i += 1
continue
if day in last_exit_dt:
elapsed = (_t2dt(c["candle_time"]) - last_exit_dt[day]).total_seconds() / 60
if elapsed < cooldown_min:
i += 1
continue
drop = (running_open - running_low) / running_open
if drop < min_drop_rate:
i += 1
continue
day_range = running_high - running_low
rec_day = (cl - running_low) / day_range if day_range > 0 else 0
if rec_day < min_recovery_ratio:
i += 1
continue
# 꼬리 비율 검사
body_top, body_bot = max(op, cl), min(op, cl)
body_len = body_top - body_bot if body_top > body_bot else 1.0
tail_len = body_bot - lo if lo > 0 else 0.0
lo_use = lo
if tail_len <= 0:
for j in range(i - 1, max(i - 4, rsi_period), -1):
prev = candles[j]
o2, l2, c2 = float(prev["open"]), float(prev["low"]), float(prev["close"])
if l2 <= 0: continue
bt2, bb2 = max(o2, c2), min(o2, c2)
bl2 = bt2 - bb2 if bt2 > bb2 else 1.0
tl2 = bb2 - l2
if tl2 > 0:
tail_len, body_len, lo_use = tl2, bl2, l2
break
tail_ratio = tail_len / body_len if body_len > 0 else 0
tail_pct = tail_len / lo_use if lo_use > 0 and tail_len > 0 else 0.0
if tail_ratio < tail_ratio_min or tail_pct < tail_pct_min:
i += 1
continue
c_range = hi - lo if hi > lo else 0
rec_3m = (cl - lo) / c_range if c_range > 0 else 0
if not (min_recovery_ratio <= rec_3m <= max_rec_3m):
i += 1
continue
rsi_val = rsis[i]
if rsi_val is None or rsi_val >= rsi_threshold:
i += 1
continue
if cl >= running_high * high_chase_thr:
i += 1
continue
# MA20 방어 로직 (역배열 및 이격도 과열 차단)
ma20 = ma20s[i]
if ma20 is None or cl < ma20:
i += 1
continue
ma20_max_above = float(params.get("ma20_max_above", 3.0))
if ma20 > 0 and cl > ma20 * (1 + ma20_max_above / 100):
i += 1
continue
# 피뢰침 변동폭 방어
if running_low > 0 and ((running_high - running_low) / running_low * 100) > float(params.get("max_daily_change", 20.0)):
i += 1
continue
# ── 3. 매수 실행 (다음 봉 시가 진입) ──
if i + 1 >= len(candles):
i += 1
continue
next_c = candles[i + 1]
if next_c["candle_time"][:8] != day:
i += 1
continue
entry_price = float(next_c["open"])
if entry_price <= 0:
entry_price = cl
# ATR 기반 동적 목표/손절 계산
atr = atrs[i] if atrs[i] is not None else entry_price * 0.01
stop_p = entry_price - (atr * stop_atr_mult)
target_p = entry_price + (atr * target_atr_mult)
# 포지션 사이징 로직 (Risk % 및 Max Loss 반영)
from_risk = (capital * risk_pct * kelly_mult) / static_sl_pct if static_sl_pct > 0 else capital
from_cap = max_loss_krw / static_sl_pct if static_sl_pct > 0 else capital
invest_amount = min(from_risk, from_cap)
calc_qty = max(1, int(invest_amount / entry_price))
position = {
"entry_price": entry_price,
"entry_time": next_c["candle_time"],
"stop": stop_p,
"target": target_p,
"max_price": entry_price,
"qty": calc_qty,
}
i += 1 # 진입 봉 건너뜀
continue
return all_trades