refactor: reorganize project structure into tests/, data/, logs/
- Move all backtest/simulation scripts to tests/ - Add sys.path.insert to each script for correct import resolution - Move pkl cache files to data/ (git-ignored) - Move log files to logs/ (git-ignored) - Update main.py: trading.log path → logs/trading.log - Add ecosystem.config.js: pm2 log paths → logs/pm2*.log - Update .gitignore: ignore data/ and logs/ instead of *.pkl/*.log - core/fng.py: increase cache TTL 3600→86400s (API updates daily at KST 09:00) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
joungmin
189
tests/momentum_cmp.py
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189
tests/momentum_cmp.py
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"""모멘텀 필터 유/무 비교 시뮬레이션.
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A안: 추세(2h +5%) + 15분 워치리스트 (모멘텀 없음)
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B안: 추세(2h +5%) + 모멘텀 + 15분 워치리스트 (현행)
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"""
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import os as _os, sys as _sys
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_sys.path.insert(0, _os.path.dirname(_os.path.dirname(_os.path.abspath(__file__))))
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import os, time
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from dotenv import load_dotenv
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load_dotenv()
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import oracledb
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import pyupbit
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STOP_LOSS_PCT = float(os.getenv("STOP_LOSS_PCT", "1.5")) / 100
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TIME_STOP_HOURS = int(os.getenv("TIME_STOP_HOURS", "8"))
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TIME_STOP_MIN_PCT = float(os.getenv("TIME_STOP_MIN_GAIN_PCT", "3")) / 100
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TREND_MIN_PCT = 5.0
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MA_PERIOD = 20
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LOCAL_VOL_HOURS = 5
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VOL_MULT = float(os.getenv("VOLUME_MULTIPLIER", "2.0"))
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CONFIRM_MINUTES = 15
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FEE = 0.0005
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_daily_cache = {}
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_hourly_cache = {}
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def get_conn():
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return oracledb.connect(
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user=os.getenv('ORACLE_USER'), password=os.getenv('ORACLE_PASSWORD'),
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dsn=os.getenv('ORACLE_DSN'), config_dir=os.getenv('ORACLE_WALLET'))
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def load_prices(cur, ticker, from_dt):
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cur.execute("""SELECT price, recorded_at FROM price_history
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WHERE ticker=:t AND recorded_at>=:f ORDER BY recorded_at""", t=ticker, f=from_dt)
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return cur.fetchall()
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def get_ma20(ticker, dt):
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key = (ticker, dt.strftime("%Y-%m-%d"))
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if key not in _daily_cache:
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try:
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df = pyupbit.get_ohlcv(ticker, interval="day", count=MA_PERIOD+2,
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to=dt.strftime("%Y-%m-%d 09:00:00"))
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_daily_cache[key] = df
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time.sleep(0.1)
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except:
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_daily_cache[key] = None
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df = _daily_cache[key]
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if df is None or len(df) < MA_PERIOD:
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return None
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return df["close"].iloc[-MA_PERIOD:].mean()
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def get_vol_ratio(ticker, dt):
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key = (ticker, dt.strftime("%Y-%m-%d %H"))
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if key not in _hourly_cache:
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try:
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df = pyupbit.get_ohlcv(ticker, interval="minute60", count=LOCAL_VOL_HOURS+3,
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to=dt.strftime("%Y-%m-%d %H:%M:%S"))
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_hourly_cache[key] = df
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time.sleep(0.1)
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except:
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_hourly_cache[key] = None
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df = _hourly_cache[key]
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if df is None or len(df) < LOCAL_VOL_HOURS+1:
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return 0.0
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rv = df["volume"].iloc[-2]
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la = df["volume"].iloc[-(LOCAL_VOL_HOURS+1):-2].mean()
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return rv/la if la > 0 else 0.0
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def check_trend(prices, idx):
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lb = 12 # 2h = 12 * 10min
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if idx < lb: return False
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curr, past = prices[idx][0], prices[idx-lb][0]
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return past > 0 and (curr-past)/past*100 >= TREND_MIN_PCT
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def check_momentum(ticker, price, dt):
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ma = get_ma20(ticker, dt)
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if ma is None or price <= ma: return False
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return get_vol_ratio(ticker, dt) >= VOL_MULT
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def simulate_pos(prices, buy_idx, buy_price):
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buy_dt = prices[buy_idx][1]
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peak = buy_price
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for price, ts in prices[buy_idx+1:]:
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if price > peak: peak = price
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elapsed_h = (ts - buy_dt).total_seconds() / 3600
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pnl = (price - buy_price) / buy_price
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if (peak - price) / peak >= STOP_LOSS_PCT:
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net = (price*(1-FEE) - buy_price*(1+FEE)) / (buy_price*(1+FEE)) * 100
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return net > 0, price, ts, f"트레일링({pnl*100:+.1f}%)", net
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if elapsed_h >= TIME_STOP_HOURS and pnl < TIME_STOP_MIN_PCT:
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net = (price*(1-FEE) - buy_price*(1+FEE)) / (buy_price*(1+FEE)) * 100
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return net > 0, price, ts, f"타임스탑", net
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lp, lt = prices[-1]
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net = (lp*(1-FEE) - buy_price*(1+FEE)) / (buy_price*(1+FEE)) * 100
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return net > 0, lp, lt, "데이터종료", net
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def run_scenario(prices, ticker, use_momentum, label):
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wins = losses = 0
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total_pnl = 0.0
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watchlist_dt = None
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in_pos = False
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buy_idx = buy_price = None
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idx = 0
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trades = []
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while idx < len(prices):
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price, dt = prices[idx]
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if in_pos:
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is_win, sp, sdt, reason, pnl = simulate_pos(prices, buy_idx, buy_price)
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next_idx = next((i for i,(_, ts) in enumerate(prices) if ts > sdt), len(prices))
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if is_win: wins += 1
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else: losses += 1
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total_pnl += pnl
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trades.append((is_win, buy_price, sp, pnl, dt, sdt, reason))
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in_pos = False
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watchlist_dt = None
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idx = next_idx
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continue
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trend_ok = check_trend(prices, idx)
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mom_ok = check_momentum(ticker, price, dt) if (use_momentum and trend_ok) else True
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if trend_ok and mom_ok:
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if watchlist_dt is None:
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watchlist_dt = dt
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elif (dt - watchlist_dt).total_seconds() >= CONFIRM_MINUTES * 60:
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in_pos = True
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buy_idx = idx
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buy_price = price
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watchlist_dt = None
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else:
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watchlist_dt = None
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idx += 1
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total = wins + losses
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wr = wins/total*100 if total else 0
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return {'label': label, 'total': total, 'wins': wins, 'losses': losses,
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'wr': wr, 'pnl': total_pnl, 'trades': trades}
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def print_result(r):
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print(f"\n [{r['label']}]")
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print(f" 총 {r['total']}건 | 승률={r['wr']:.0f}% ({r['wins']}승 {r['losses']}패) | 누적={r['pnl']:+.2f}%")
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for i, (iw, bp, sp, pnl, bdt, sdt, reason) in enumerate(r['trades'], 1):
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mark = "✅" if iw else "❌"
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print(f" #{i}: {bp:.4f}→{sp:.4f}원 | {mark} {pnl:+.2f}% | {reason}"
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f" ({bdt.strftime('%m-%d %H:%M')}→{sdt.strftime('%m-%d %H:%M')})")
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def main():
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conn = get_conn()
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cur = conn.cursor()
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cur.execute("SELECT MAX(recorded_at) FROM price_history")
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end_dt = cur.fetchone()[0]
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print("=" * 62)
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print("모멘텀 필터 유/무 비교 (WF차단 발동 이후 전 기간)")
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print("A안: 추세+워치리스트만 B안: 추세+모멘텀+워치리스트(현행)")
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print("=" * 62)
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summary = []
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for ticker in ['KRW-DKA', 'KRW-LAYER', 'KRW-SIGN']:
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cur.execute("SELECT traded_at FROM trade_results WHERE ticker=:t ORDER BY traded_at", t=ticker)
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rows = cur.fetchall()
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wf_dt = rows[4][0]
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prices = load_prices(cur, ticker, wf_dt)
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print(f"\n{'─'*62}")
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print(f"[{ticker}] WF차단: {wf_dt.strftime('%m-%d %H:%M')} 데이터: {len(prices)}틱")
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rA = run_scenario(prices, ticker, use_momentum=False, label="A: 추세+워치만")
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rB = run_scenario(prices, ticker, use_momentum=True, label="B: 추세+모멘텀+워치(현행)")
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print_result(rA)
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print_result(rB)
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summary.append((ticker, rA, rB))
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print(f"\n{'='*62}")
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print(f"{'종목':<12} {'A안 거래':>6} {'A안 승률':>8} {'A안 PnL':>10} │ {'B안 거래':>6} {'B안 승률':>8} {'B안 PnL':>10}")
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print(f"{'─'*62}")
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for ticker, rA, rB in summary:
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print(f"{ticker:<12} {rA['total']:>6}건 {rA['wr']:>6.0f}% {rA['pnl']:>+9.2f}% │"
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f" {rB['total']:>6}건 {rB['wr']:>6.0f}% {rB['pnl']:>+9.2f}%")
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conn.close()
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if __name__ == "__main__":
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main()
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