Files
kis_bot/tail_engine.py
2026-03-17 12:33:30 +09:00

484 lines
20 KiB
Python

#!/usr/bin/env python3
"""
tail_engine.py — 꼬리잡기 백테스트·실매매 공통 엔진
====================================================
백테스트(backtest_web)와 실매매(kis_short_ver3)가 동일한 진입/청산 계산식을 쓰도록 공통 로직만 둠.
■ 엔진 공통 로직 (백테·실매 동일)
매수: 당일 낙폭(drop) ≥ min_drop_rate, 당일 회복률(rec_day) ≥ min_recovery_ratio,
망치봉 꼬리(tail_ratio/tail_pct), 3분봉 회복(rec_3m) 구간, RSI < rsi_threshold,
고점추격 방지(high_chase_thr), 시간대/쿨다운/max_daily.
매도: 손절가(sl_pct), 익절가(tp_pct), 어깨컷(shoulder_min_high + shoulder_cut_pct), 장마감.
■ 엔진 밖(실매매 전용): 금액손실컷, ATR 기반 손절/목표가, 퀵프로핏, MA20/ML 필터 등.
"""
from datetime import datetime
from typing import List, Dict, Any, Optional
def get_tail_defaults_from_db(db=None) -> Dict[str, Any]:
"""
env_config 최신 행에서 꼬리잡기 관련 값 전부 로드.
백테스트·파라미터서치·실매매가 동일 DB 값을 쓰도록 단일 소스.
db: 기존 TradeDB 인스턴스. 주면 연결 생성/종료 없이 재사용 (봇 메인 루프에서 반복 호출 시 로그 스팸·연결 낭비 방지).
결과에 영향을 주는 env 키: MIN_DROP_RATE, MIN_RECOVERY_RATIO_SHORT, TAIL_RATIO_MIN, TAIL_PCT_MIN,
STOP_LOSS_PCT, TAKE_PROFIT_PCT, SHOULDER_MIN_HIGH_PCT, SHOULDER_CUT_PCT, RSI_PERIOD, RSI_OVERHEAT_THRESHOLD,
REENTRY_COOLDOWN_SEC, HIGH_PRICE_CHASE_THRESHOLD, MAX_RECOVERY_RATIO_3M, (시간/일일한도).
"""
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)
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)
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
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
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,
}
def compute_rsi_series(closes: List[float], period: int = 14) -> List[Optional[float]]:
"""RSI 시리즈 (Wilder 스무딩). backtest_web과 동일."""
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 _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.
로직 단일 소스: run_tail_backtest와 완전 동일한 조건·계산식.
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)
- 통과 시: (None, None, {"signal": True, "tail_ratio", "recovery_pos", "rsi_val"})
- 탈락 시: ("탈락-XXX", "상세메시지(숫자포함)", None) → 호출측에서 "🔍 [탈락-XXX] name code: 상세메시지" 로그
"""
if len(candles) < 10:
return ("탈락-데이터", "봉 수 부족 (len<10)", 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"])
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))
if hm < time_start_hm or hm > time_end_hm:
return (None, None, None) # 시간대 탈락 (로그 생략 가능)
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)
# 당일 누적 OHLC (run_tail_backtest와 동일)
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)
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}% (당일 시가 {running_open:,.0f}원 → 저점 {running_low:,.0f}원)",
None,
)
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}원 → 현재 {cl:,.0f}원 / 범위 {day_range:,.0f}원)",
None,
)
# 망치봉 꼬리 (run_tail_backtest와 동일: 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 = float(prev["open"])
l2 = float(prev["low"])
c2 = 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:
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,
)
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,
)
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,
)
if cl >= running_high * high_chase_thr:
return (
"탈락-피뢰침 고점추격",
f"현재가 {cl:,.0f} ≥ 고점대비 {high_chase_thr*100:.0f}%",
None,
)
return (
None,
None,
{"signal": True, "tail_ratio": tail_ratio, "tail_pct": tail_pct, "recovery_pos": rec_3m, "rsi_val": rsi_val},
)
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: 백테스트와 동일한 청산 조건 (손절/익절/어깨컷/장마감).
position: entry_price, entry_time, stop, target, max_price
current_candle: high, low, close
반환: (reason_str, exit_price) 또는 None
"""
sl_pct = float(params.get("sl_pct", 0.03))
tp_pct = float(params.get("tp_pct", 0.05))
shoulder_min_high = float(params.get("shoulder_min_high", 0.015))
shoulder_cut_pct = float(params.get("shoulder_cut_pct", 0.03))
hi = float(current_candle.get("high", current_candle["close"]))
lo = float(current_candle.get("low", current_candle["close"]))
cl = float(current_candle["close"])
max_p = max(position["max_price"], hi)
ep = position["entry_price"]
stop = position.get("stop", ep * (1 - sl_pct))
target = position.get("target", ep * (1 + tp_pct))
reason = None
exit_price = cl
if lo > 0 and lo <= stop:
reason = "손절"
exit_price = stop
elif hi >= target:
reason = "익절"
exit_price = target
elif max_p >= ep * (1 + shoulder_min_high) and cl <= max_p * (1 - shoulder_cut_pct):
reason = "어깨컷"
exit_price = cl
if 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],
) -> List[Dict]:
"""
백테스트 1회 실행 (backtest_web과 동일 로직). API에서 호출해 단일 소스 유지.
candles_by_code: code -> list of {candle_time, open, high, low, close, volume}
params: get_tail_defaults_from_db() + sl_pct, tp_pct 등
반환: all_trades 리스트
"""
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))
sl_pct = float(params.get("sl_pct", 0.03))
tp_pct = float(params.get("tp_pct", 0.05))
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))
all_trades: List[Dict] = []
for code, candles in candles_by_code.items():
if len(candles) < rsi_period + 5:
continue
closes = [float(c["close"]) for c in candles]
rsis = compute_rsi_series(closes, rsi_period)
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"])
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)
if position is not None:
max_p = max(position["max_price"], hi)
position["max_price"] = max_p
reason = None
exit_price = cl
if lo > 0 and lo <= position["stop"]:
reason = "손절"
exit_price = position["stop"]
elif hi >= position["target"]:
reason = "익절"
exit_price = position["target"]
elif max_p >= position["entry_price"] * (1 + shoulder_min_high) and cl <= max_p * (1 - shoulder_cut_pct):
reason = "어깨컷"
exit_price = cl
elif is_eod:
reason = "장마감"
exit_price = cl
if reason:
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,
"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
if cl <= 0 or running_open <= 0:
i += 1
continue
if 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
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, 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 i < len(rsis) else None
if rsi_val is None or rsi_val >= rsi_threshold:
i += 1
continue
if cl >= running_high * high_chase_thr:
i += 1
continue
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
position = {
"entry_price": entry_price,
"entry_time": next_c["candle_time"],
"stop": entry_price * (1 - sl_pct),
"target": entry_price * (1 + tp_pct),
"max_price": entry_price,
}
i += 1 # 진입 봉(next) 건너뜀 — 다음 봉부터 포지션 보유로 청산 체크
continue
return all_trades