""" Backtest ULTRA RAPIDE - 100 meilleures configs seulement """ import pandas as pd import numpy as np from apollo_client import ApolloDegenClient print('\n' + '='*80) print('⚡ ULTRA FAST BACKTEST') print('='*80) client = ApolloDegenClient() df = client.get_klines('BTCUSDT', '1m', limit=1500) print(f'✅ {len(df)} bougies') print() # MA df['ma_20'] = df['close'].rolling(20).mean() def backtest(df, ma_period, sl_pct, tp_ratio, leverage): """Backtest simple""" cap = 100 trades = [] pos = None for i in range(ma_period + 10, len(df), 2): # Skip 1 bougie sur 2 pour vitesse close = df.iloc[i]['close'] ma = df.iloc[i][f'ma_{ma_period}'] if pd.isna(ma): continue # Position ouverte? if pos: # Check SL/TP hit_sl = (pos['side'] == 'LONG' and close <= pos['sl']) or \ (pos['side'] == 'SHORT' and close >= pos['sl']) hit_tp = (pos['side'] == 'LONG' and close >= pos['tp']) or \ (pos['side'] == 'SHORT' and close <= pos['tp']) if hit_sl or hit_tp: if pos['side'] == 'LONG': pnl_pct = (close - pos['entry']) / pos['entry'] else: pnl_pct = (pos['entry'] - close) / pos['entry'] pnl = pnl_pct * leverage * pos['margin'] cap += pnl trades.append(pnl) pos = None # Nouveau signal if not pos and cap > 0: side = 'LONG' if close > ma else 'SHORT' if side == 'LONG': sl = close * (1 - sl_pct) tp = close * (1 + sl_pct * tp_ratio) else: sl = close * (1 + sl_pct) tp = close * (1 - sl_pct * tp_ratio) pos = { 'side': side, 'entry': close, 'sl': sl, 'tp': tp, 'margin': cap * 0.05 } # Close final if pos: close = df.iloc[-1]['close'] if pos['side'] == 'LONG': pnl_pct = (close - pos['entry']) / pos['entry'] else: pnl_pct = (pos['entry'] - close) / pos['entry'] pnl = pnl_pct * leverage * pos['margin'] cap += pnl trades.append(pnl) if not trades: return None ret = ((cap - 100) / 100) * 100 wins = [t for t in trades if t > 0] wr = (len(wins) / len(trades)) * 100 return { 'return': round(ret, 2), 'trades': len(trades), 'win_rate': round(wr, 1), 'capital': round(cap, 2) } # Test configs prometteuses results = [] print('🧪 Test de 100 configurations prometteuses...') print() configs = [ # MA20 - configs autour de la baseline (20, 0.00025, 6, 250), # Baseline (20, 0.0001, 8, 250), # SL plus serré, TP plus large (20, 0.0002, 10, 200), (20, 0.0003, 8, 200), (20, 0.0005, 6, 150), (20, 0.0001, 10, 250), (20, 0.00015, 8, 250), (20, 0.0002, 6, 250), (20, 0.00025, 8, 250), (20, 0.0003, 6, 200), # MA10 - fast trend (10, 0.0001, 10, 250), (10, 0.00025, 8, 250), (10, 0.0002, 10, 200), (10, 0.0001, 8, 250), (10, 0.00015, 10, 250), (10, 0.0003, 6, 200), (10, 0.0002, 8, 250), (10, 0.00025, 10, 200), (10, 0.0001, 6, 250), (10, 0.0005, 5, 150), # MA30 - slower trend (30, 0.0001, 10, 250), (30, 0.00025, 8, 250), (30, 0.0002, 8, 200), (30, 0.0003, 6, 200), (30, 0.0001, 8, 250), (30, 0.00015, 10, 250), (30, 0.0002, 10, 250), (30, 0.00025, 6, 250), (30, 0.0005, 5, 150), (30, 0.0001, 12, 250), # MA50 - long trend (50, 0.0001, 10, 250), (50, 0.0002, 8, 200), (50, 0.00025, 6, 200), (50, 0.0003, 8, 200), (50, 0.0001, 12, 250), (50, 0.00015, 10, 250), (50, 0.0002, 10, 200), (50, 0.00025, 8, 250), (50, 0.0005, 5, 150), (50, 0.0001, 8, 250), # Aggressive SL configs (20, 0.00005, 15, 250), (20, 0.00008, 12, 250), (10, 0.00005, 15, 250), (10, 0.00008, 12, 250), (30, 0.00005, 15, 250), # High TP ratio configs (20, 0.0001, 15, 250), (20, 0.0001, 20, 250), (10, 0.0001, 15, 250), (10, 0.0001, 20, 250), (30, 0.0001, 15, 250), # Medium leverage configs (20, 0.0002, 8, 150), (20, 0.0003, 6, 150), (10, 0.0002, 10, 150), (30, 0.0002, 8, 150), (50, 0.0002, 8, 150), # Lower leverage high SL (20, 0.001, 5, 100), (20, 0.002, 4, 100), (10, 0.001, 6, 100), (30, 0.001, 5, 100), (50, 0.001, 5, 100), # Mixed configs (15, 0.0001, 10, 250), (15, 0.00025, 8, 250), (15, 0.0002, 8, 200), (25, 0.0001, 10, 250), (25, 0.00025, 8, 250), (25, 0.0002, 8, 200), (40, 0.0001, 10, 250), (40, 0.00025, 8, 250), (40, 0.0002, 8, 200), # Ultra tight SL (20, 0.00003, 20, 250), (20, 0.00004, 15, 250), (10, 0.00003, 20, 250), (30, 0.00003, 20, 250), # Balanced configs (20, 0.0004, 6, 200), (20, 0.0006, 5, 200), (10, 0.0004, 8, 200), (30, 0.0004, 6, 200), (50, 0.0004, 6, 200), # High leverage low SL (20, 0.0001, 6, 250), (20, 0.00015, 6, 250), (10, 0.0001, 8, 250), (30, 0.0001, 6, 250), (50, 0.0001, 6, 250), # Additional promising (12, 0.0001, 10, 250), (12, 0.00025, 8, 250), (35, 0.0001, 10, 250), (35, 0.00025, 8, 250), (45, 0.0001, 10, 250), (45, 0.00025, 8, 250), ] print(f'Testing {len(configs)} configurations...\n') # Calculer toutes les MA nécessaires for ma in set([c[0] for c in configs]): df[f'ma_{ma}'] = df['close'].rolling(ma).mean() for i, (ma, sl, tp, lev) in enumerate(configs, 1): if i % 20 == 0: print(f'⏳ {i}/{len(configs)}...') result = backtest(df, ma, sl, tp, lev) if result: results.append({ 'ma': ma, 'sl': sl, 'tp': tp, 'lev': lev, **result }) print(f'\n✅ {len(results)} résultats') print() # Sort results.sort(key=lambda x: x['return'], reverse=True) # TOP 20 print('='*80) print('🏆 TOP 20 CONFIGURATIONS') print('='*80) print() for i, r in enumerate(results[:20], 1): print(f"{i}. MA{r['ma']} | SL {r['sl']*100:.3f}% | TP {r['tp']}:1 | Lev {r['lev']}x") print(f" 💵 Return: {r['return']:+.2f}% (${r['capital']:.2f})") print(f" ✅ WR: {r['win_rate']:.1f}% | Trades: {r['trades']}") print() # Champion if results: c = results[0] print('='*80) print('👑 CHAMPION') print('='*80) print(f"MA{c['ma']} Cross Strategy") print(f"Stop-Loss: {c['sl']*100:.4f}%") print(f"Take-Profit: {c['tp']}:1 ratio") print(f"Leverage: {c['lev']}x") print(f"Return: {c['return']:+.2f}%") print(f"Win Rate: {c['win_rate']:.1f}%") print(f"Trades: {c['trades']}") print(f"Capital final: ${c['capital']:.2f}") print('='*80)