upbit-trader/momentum_cmp.py

"""모멘텀 필터 유/무 비교 시뮬레이션.

A안: 추세(2h +5%) + 15분 워치리스트  (모멘텀 없음)
B안: 추세(2h +5%) + 모멘텀 + 15분 워치리스트  (현행)
"""

import os, time
from dotenv import load_dotenv
load_dotenv()
import oracledb
import pyupbit

STOP_LOSS_PCT     = float(os.getenv("STOP_LOSS_PCT", "1.5")) / 100
TIME_STOP_HOURS   = int(os.getenv("TIME_STOP_HOURS", "8"))
TIME_STOP_MIN_PCT = float(os.getenv("TIME_STOP_MIN_GAIN_PCT", "3")) / 100
TREND_MIN_PCT     = 5.0
MA_PERIOD         = 20
LOCAL_VOL_HOURS   = 5
VOL_MULT          = float(os.getenv("VOLUME_MULTIPLIER", "2.0"))
CONFIRM_MINUTES   = 15
FEE               = 0.0005

_daily_cache  = {}
_hourly_cache = {}

def get_conn():
    return oracledb.connect(
        user=os.getenv('ORACLE_USER'), password=os.getenv('ORACLE_PASSWORD'),
        dsn=os.getenv('ORACLE_DSN'), config_dir=os.getenv('ORACLE_WALLET'))

def load_prices(cur, ticker, from_dt):
    cur.execute("""SELECT price, recorded_at FROM price_history
        WHERE ticker=:t AND recorded_at>=:f ORDER BY recorded_at""", t=ticker, f=from_dt)
    return cur.fetchall()

def get_ma20(ticker, dt):
    key = (ticker, dt.strftime("%Y-%m-%d"))
    if key not in _daily_cache:
        try:
            df = pyupbit.get_ohlcv(ticker, interval="day", count=MA_PERIOD+2,
                                   to=dt.strftime("%Y-%m-%d 09:00:00"))
            _daily_cache[key] = df
            time.sleep(0.1)
        except:
            _daily_cache[key] = None
    df = _daily_cache[key]
    if df is None or len(df) < MA_PERIOD:
        return None
    return df["close"].iloc[-MA_PERIOD:].mean()

def get_vol_ratio(ticker, dt):
    key = (ticker, dt.strftime("%Y-%m-%d %H"))
    if key not in _hourly_cache:
        try:
            df = pyupbit.get_ohlcv(ticker, interval="minute60", count=LOCAL_VOL_HOURS+3,
                                   to=dt.strftime("%Y-%m-%d %H:%M:%S"))
            _hourly_cache[key] = df
            time.sleep(0.1)
        except:
            _hourly_cache[key] = None
    df = _hourly_cache[key]
    if df is None or len(df) < LOCAL_VOL_HOURS+1:
        return 0.0
    rv = df["volume"].iloc[-2]
    la = df["volume"].iloc[-(LOCAL_VOL_HOURS+1):-2].mean()
    return rv/la if la > 0 else 0.0

def check_trend(prices, idx):
    lb = 12  # 2h = 12 * 10min
    if idx < lb: return False
    curr, past = prices[idx][0], prices[idx-lb][0]
    return past > 0 and (curr-past)/past*100 >= TREND_MIN_PCT

def check_momentum(ticker, price, dt):
    ma = get_ma20(ticker, dt)
    if ma is None or price <= ma: return False
    return get_vol_ratio(ticker, dt) >= VOL_MULT

def simulate_pos(prices, buy_idx, buy_price):
    buy_dt = prices[buy_idx][1]
    peak = buy_price
    for price, ts in prices[buy_idx+1:]:
        if price > peak: peak = price
        elapsed_h = (ts - buy_dt).total_seconds() / 3600
        pnl = (price - buy_price) / buy_price
        if (peak - price) / peak >= STOP_LOSS_PCT:
            net = (price*(1-FEE) - buy_price*(1+FEE)) / (buy_price*(1+FEE)) * 100
            return net > 0, price, ts, f"트레일링({pnl*100:+.1f}%)", net
        if elapsed_h >= TIME_STOP_HOURS and pnl < TIME_STOP_MIN_PCT:
            net = (price*(1-FEE) - buy_price*(1+FEE)) / (buy_price*(1+FEE)) * 100
            return net > 0, price, ts, f"타임스탑", net
    lp, lt = prices[-1]
    net = (lp*(1-FEE) - buy_price*(1+FEE)) / (buy_price*(1+FEE)) * 100
    return net > 0, lp, lt, "데이터종료", net

def run_scenario(prices, ticker, use_momentum, label):
    wins = losses = 0
    total_pnl = 0.0
    watchlist_dt = None
    in_pos = False
    buy_idx = buy_price = None
    idx = 0
    trades = []

    while idx < len(prices):
        price, dt = prices[idx]

        if in_pos:
            is_win, sp, sdt, reason, pnl = simulate_pos(prices, buy_idx, buy_price)
            next_idx = next((i for i,(_, ts) in enumerate(prices) if ts > sdt), len(prices))
            if is_win: wins += 1
            else: losses += 1
            total_pnl += pnl
            trades.append((is_win, buy_price, sp, pnl, dt, sdt, reason))
            in_pos = False
            watchlist_dt = None
            idx = next_idx
            continue

        trend_ok = check_trend(prices, idx)
        mom_ok = check_momentum(ticker, price, dt) if (use_momentum and trend_ok) else True

        if trend_ok and mom_ok:
            if watchlist_dt is None:
                watchlist_dt = dt
            elif (dt - watchlist_dt).total_seconds() >= CONFIRM_MINUTES * 60:
                in_pos = True
                buy_idx = idx
                buy_price = price
                watchlist_dt = None
        else:
            watchlist_dt = None

        idx += 1

    total = wins + losses
    wr = wins/total*100 if total else 0
    return {'label': label, 'total': total, 'wins': wins, 'losses': losses,
            'wr': wr, 'pnl': total_pnl, 'trades': trades}

def print_result(r):
    print(f"\n  [{r['label']}]")
    print(f"  총 {r['total']}건 | 승률={r['wr']:.0f}% ({r['wins']}승 {r['losses']}패) | 누적={r['pnl']:+.2f}%")
    for i, (iw, bp, sp, pnl, bdt, sdt, reason) in enumerate(r['trades'], 1):
        mark = "✅" if iw else "❌"
        print(f"    #{i}: {bp:.4f}→{sp:.4f}원 | {mark} {pnl:+.2f}% | {reason}"
              f" ({bdt.strftime('%m-%d %H:%M')}→{sdt.strftime('%m-%d %H:%M')})")

def main():
    conn = get_conn()
    cur = conn.cursor()
    cur.execute("SELECT MAX(recorded_at) FROM price_history")
    end_dt = cur.fetchone()[0]

    print("=" * 62)
    print("모멘텀 필터 유/무 비교 (WF차단 발동 이후 전 기간)")
    print("A안: 추세+워치리스트만  B안: 추세+모멘텀+워치리스트(현행)")
    print("=" * 62)

    summary = []
    for ticker in ['KRW-DKA', 'KRW-LAYER', 'KRW-SIGN']:
        cur.execute("SELECT traded_at FROM trade_results WHERE ticker=:t ORDER BY traded_at", t=ticker)
        rows = cur.fetchall()
        wf_dt = rows[4][0]
        prices = load_prices(cur, ticker, wf_dt)

        print(f"\n{'─'*62}")
        print(f"[{ticker}]  WF차단: {wf_dt.strftime('%m-%d %H:%M')}  데이터: {len(prices)}틱")

        rA = run_scenario(prices, ticker, use_momentum=False, label="A: 추세+워치만")
        rB = run_scenario(prices, ticker, use_momentum=True,  label="B: 추세+모멘텀+워치(현행)")
        print_result(rA)
        print_result(rB)
        summary.append((ticker, rA, rB))

    print(f"\n{'='*62}")
    print(f"{'종목':<12} {'A안 거래':>6} {'A안 승률':>8} {'A안 PnL':>10} │ {'B안 거래':>6} {'B안 승률':>8} {'B안 PnL':>10}")
    print(f"{'─'*62}")
    for ticker, rA, rB in summary:
        print(f"{ticker:<12} {rA['total']:>6}건  {rA['wr']:>6.0f}%  {rA['pnl']:>+9.2f}% │"
              f" {rB['total']:>6}건  {rB['wr']:>6.0f}%  {rB['pnl']:>+9.2f}%")

    conn.close()

if __name__ == "__main__":
    main()