0b264b304c
Backtest improvements: - Add backtest.py with Oracle DB-backed OHLCV cache (no repeated API calls) - Add backtest_trades table to cache simulation results by params hash (same params -> instant load, skip re-simulation) - Add walk-forward scenario comparison (--walkforward-cmp) - Add trend ceiling filter (--trend-cmp, max gain threshold) - Add ticker win-rate filter (--ticker-cmp, SQL-based instant analysis) - Precompute daily_features once per data load (not per scenario) Live bot fixes: - monitor: add hard stop-loss from buy price (in addition to trailing) - strategy: fix re-entry condition to require +1% above last sell price - price_collector: add 48h backfill on startup for trend calculation - main: call backfill_prices() at startup Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
79 lines
2.4 KiB
Python
79 lines
2.4 KiB
Python
"""Strategy C: 현재 기준 N시간 전 대비 상승 추세(DB) AND 거래량 모멘텀 동시 충족 시 매수 신호."""
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from __future__ import annotations
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import logging
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import os
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from .market import get_current_price, get_ohlcv
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from .price_db import get_price_n_hours_ago
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logger = logging.getLogger(__name__)
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# 추세 판단: 현재 기준 N시간 전 DB 가격 대비 +M% 이상이면 상승 중
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TREND_HOURS = float(os.getenv("TREND_HOURS", "12"))
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TREND_MIN_GAIN_PCT = float(os.getenv("TREND_MIN_GAIN_PCT", "3"))
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# 모멘텀: MA 기간, 거래량 급증 배수
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MA_PERIOD = 20
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VOLUME_MULTIPLIER = 2.0
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def check_trend(ticker: str) -> bool:
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"""상승 추세 조건: 현재가가 DB에 저장된 N시간 전 가격 대비 +M% 이상."""
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past_price = get_price_n_hours_ago(ticker, TREND_HOURS)
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if past_price is None:
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logger.debug(f"[추세] {ticker} {TREND_HOURS:.0f}h 전 가격 없음 (수집 중)")
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return False
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current = get_current_price(ticker)
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if not current:
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return False
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gain_pct = (current - past_price) / past_price * 100
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result = gain_pct >= TREND_MIN_GAIN_PCT
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if result:
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logger.info(
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f"[추세↑] {ticker} {TREND_HOURS:.0f}h 전={past_price:,.2f} "
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f"현재={current:,.2f} (+{gain_pct:.1f}%)"
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)
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else:
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logger.debug(
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f"[추세✗] {ticker} {gain_pct:+.1f}% (기준={TREND_MIN_GAIN_PCT:+.0f}%)"
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)
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return result
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def check_momentum(ticker: str) -> bool:
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"""모멘텀 조건: 현재가 > MA20 AND 오늘 거래량 > 20일 평균 × 2."""
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df = get_ohlcv(ticker, count=MA_PERIOD + 1)
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if df is None or len(df) < MA_PERIOD + 1:
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return False
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ma = df["close"].iloc[-MA_PERIOD:].mean()
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avg_vol = df["volume"].iloc[:-1].mean()
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today_vol = df["volume"].iloc[-1]
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current = get_current_price(ticker)
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if current is None:
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return False
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price_ok = current > ma
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vol_ok = today_vol > avg_vol * VOLUME_MULTIPLIER
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result = price_ok and vol_ok
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if result:
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logger.debug(
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f"[모멘텀] {ticker} 현재={current:,.0f} MA20={ma:,.0f} "
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f"거래량={today_vol:.0f} 평균={avg_vol:.0f}"
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)
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return result
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def should_buy(ticker: str) -> bool:
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"""Strategy C: 실시간 상승 추세 AND 거래량 모멘텀 모두 충족 시 True."""
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if not check_trend(ticker):
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return False
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return check_momentum(ticker)
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