diff --git a/Hurst_simulations.md b/Hurst_simulations.md new file mode 100644 index 0000000..b078d7c --- /dev/null +++ b/Hurst_simulations.md @@ -0,0 +1,180 @@ +# Comprehensive Hurst Strategy Simulations (since 2025-01-01) +Comparison of different Hurst Timeframes and Entry Filters. + +# Timeframe: 1m + +## Scenario: Without Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $3192.86 | $2192.86 | 13239 | 7.40% | +| 2025-04-01 to 2025-06-30 | $3192.86 | $5665.00 | $2472.14 | 13242 | 3.39% | +| 2025-07-01 to 2025-09-30 | $5665.00 | $7520.61 | $1855.61 | 13720 | 1.02% | +| 2025-10-01 to 2025-12-31 | $7520.61 | $8891.62 | $1371.01 | 13584 | 0.56% | +| 2026-01-01 to 2026-03-10 | $8891.62 | $10437.95 | $1546.33 | 10120 | 0.52% | + +**Final Results for 1m (Without Filter):** +- Final Equity: **$10437.95** +- Total ROI: **943.80%** +- Total Trades: **63905** +- Max Overall Drawdown: **7.40%** + +## Scenario: With 1H SMA 200 Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $2124.83 | $1124.83 | 10469 | 7.57% | +| 2025-04-01 to 2025-06-30 | $2124.83 | $3729.53 | $1604.70 | 11016 | 5.09% | +| 2025-07-01 to 2025-09-30 | $3729.53 | $4673.10 | $943.57 | 10923 | 2.25% | +| 2025-10-01 to 2025-12-31 | $4673.10 | $5428.01 | $754.91 | 11319 | 1.49% | +| 2026-01-01 to 2026-03-10 | $5428.01 | $6307.05 | $879.04 | 8485 | 1.24% | + +**Final Results for 1m (With 1H SMA 200 Filter):** +- Final Equity: **$6307.05** +- Total ROI: **530.71%** +- Total Trades: **52212** +- Max Overall Drawdown: **7.57%** + +# Timeframe: 3m + +## Scenario: Without Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $2309.37 | $1309.37 | 4233 | 8.10% | +| 2025-04-01 to 2025-06-30 | $2309.37 | $3801.67 | $1492.30 | 4331 | 2.07% | +| 2025-07-01 to 2025-09-30 | $3801.67 | $4988.92 | $1187.25 | 4513 | 1.60% | +| 2025-10-01 to 2025-12-31 | $4988.92 | $5912.62 | $923.70 | 4370 | 1.05% | +| 2026-01-01 to 2026-03-10 | $5912.62 | $6740.90 | $828.28 | 3306 | 1.01% | + +**Final Results for 3m (Without Filter):** +- Final Equity: **$6740.90** +- Total ROI: **574.09%** +- Total Trades: **20753** +- Max Overall Drawdown: **8.10%** + +## Scenario: With 1H SMA 200 Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $1470.40 | $470.40 | 3288 | 10.19% | +| 2025-04-01 to 2025-06-30 | $1470.40 | $2366.47 | $896.07 | 3597 | 4.96% | +| 2025-07-01 to 2025-09-30 | $2366.47 | $2844.79 | $478.32 | 3478 | 3.23% | +| 2025-10-01 to 2025-12-31 | $2844.79 | $3250.87 | $406.08 | 3597 | 3.43% | +| 2026-01-01 to 2026-03-10 | $3250.87 | $3643.24 | $392.37 | 2739 | 1.90% | + +**Final Results for 3m (With 1H SMA 200 Filter):** +- Final Equity: **$3643.24** +- Total ROI: **264.32%** +- Total Trades: **16699** +- Max Overall Drawdown: **10.19%** + +# Timeframe: 5m + +## Scenario: Without Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $1878.15 | $878.15 | 2482 | 14.06% | +| 2025-04-01 to 2025-06-30 | $1878.15 | $3053.49 | $1175.34 | 2601 | 3.26% | +| 2025-07-01 to 2025-09-30 | $3053.49 | $3944.73 | $891.24 | 2689 | 2.08% | +| 2025-10-01 to 2025-12-31 | $3944.73 | $4578.13 | $633.40 | 2491 | 1.33% | +| 2026-01-01 to 2026-03-10 | $4578.13 | $5122.25 | $544.12 | 1966 | 1.39% | + +**Final Results for 5m (Without Filter):** +- Final Equity: **$5122.25** +- Total ROI: **412.23%** +- Total Trades: **12229** +- Max Overall Drawdown: **14.06%** + +## Scenario: With 1H SMA 200 Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $1304.55 | $304.55 | 1915 | 14.36% | +| 2025-04-01 to 2025-06-30 | $1304.55 | $1926.70 | $622.15 | 2134 | 7.03% | +| 2025-07-01 to 2025-09-30 | $1926.70 | $2253.45 | $326.75 | 2052 | 4.25% | +| 2025-10-01 to 2025-12-31 | $2253.45 | $2539.78 | $286.33 | 2038 | 2.83% | +| 2026-01-01 to 2026-03-10 | $2539.78 | $2774.98 | $235.20 | 1583 | 2.75% | + +**Final Results for 5m (With 1H SMA 200 Filter):** +- Final Equity: **$2774.98** +- Total ROI: **177.50%** +- Total Trades: **9722** +- Max Overall Drawdown: **14.36%** + +# Timeframe: 15m + +## Scenario: Without Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $1373.61 | $373.61 | 785 | 12.40% | +| 2025-04-01 to 2025-06-30 | $1373.61 | $1824.22 | $450.61 | 725 | 6.62% | +| 2025-07-01 to 2025-09-30 | $1824.22 | $2212.35 | $388.13 | 807 | 2.60% | +| 2025-10-01 to 2025-12-31 | $2212.35 | $2535.13 | $322.78 | 765 | 3.14% | +| 2026-01-01 to 2026-03-10 | $2535.13 | $2821.05 | $285.92 | 607 | 1.92% | + +**Final Results for 15m (Without Filter):** +- Final Equity: **$2821.05** +- Total ROI: **182.11%** +- Total Trades: **3689** +- Max Overall Drawdown: **12.40%** + +## Scenario: With 1H SMA 200 Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $993.20 | $-6.80 | 578 | 20.65% | +| 2025-04-01 to 2025-06-30 | $993.20 | $1127.20 | $134.00 | 559 | 10.21% | +| 2025-07-01 to 2025-09-30 | $1127.20 | $1328.46 | $201.26 | 595 | 2.96% | +| 2025-10-01 to 2025-12-31 | $1328.46 | $1394.87 | $66.41 | 606 | 5.36% | +| 2026-01-01 to 2026-03-10 | $1394.87 | $1379.42 | $-15.45 | 455 | 7.15% | + +**Final Results for 15m (With 1H SMA 200 Filter):** +- Final Equity: **$1379.42** +- Total ROI: **37.94%** +- Total Trades: **2793** +- Max Overall Drawdown: **20.65%** + +# Timeframe: 37m + +## Scenario: Without Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $1120.15 | $120.15 | 293 | 10.05% | +| 2025-04-01 to 2025-06-30 | $1120.15 | $1487.65 | $367.50 | 282 | 6.98% | +| 2025-07-01 to 2025-09-30 | $1487.65 | $1520.11 | $32.46 | 289 | 4.01% | +| 2025-10-01 to 2025-12-31 | $1520.11 | $1575.24 | $55.13 | 292 | 9.73% | +| 2026-01-01 to 2026-03-10 | $1575.24 | $1748.85 | $173.61 | 246 | 3.27% | + +**Final Results for 37m (Without Filter):** +- Final Equity: **$1748.85** +- Total ROI: **74.88%** +- Total Trades: **1402** +- Max Overall Drawdown: **10.05%** + +## Scenario: With 1H SMA 200 Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $1003.56 | $3.56 | 206 | 10.69% | +| 2025-04-01 to 2025-06-30 | $1003.56 | $1130.86 | $127.30 | 208 | 8.98% | +| 2025-07-01 to 2025-09-30 | $1130.86 | $1154.90 | $24.04 | 202 | 2.81% | +| 2025-10-01 to 2025-12-31 | $1154.90 | $1108.85 | $-46.05 | 224 | 9.50% | +| 2026-01-01 to 2026-03-10 | $1108.85 | $1117.52 | $8.67 | 179 | 4.01% | + +**Final Results for 37m (With 1H SMA 200 Filter):** +- Final Equity: **$1117.52** +- Total ROI: **11.75%** +- Total Trades: **1019** +- Max Overall Drawdown: **10.69%** + +# Timeframe: 1h + +## Scenario: Without Filter +| Period | Start Bal | End Equity | PnL | Trades | Max DD | +| :--- | :--- | :--- | :--- | :--- | :--- | +| 2025-01-01 to 2025-03-31 | $1000.00 | $1109.99 | $109.99 | 162 | 7.36% | +| 2025-04-01 to 2025-06-30 | $1109.99 | $1305.05 | $195.06 | 145 | 7.26% | +| 2025-07-01 to 2025-09-30 | $1305.05 | $1342.48 | $37.43 | 180 | 2.83% | +| 2025-10-01 to 2025-12-31 | $1342.48 | $1448.42 | $105.94 | 166 | 6.25% | +| 2026-01-01 to 2026-03-10 | $1448.42 | $1552.57 | $104.15 | 135 | 4.56% | + +**Final Results for 1h (Without Filter):** +- Final Equity: **$1552.57** +- Total ROI: **55.26%** +- Total Trades: **788** +- Max Overall Drawdown: **7.36%** + diff --git a/src/strategies/backtest_engine.py b/src/strategies/backtest_engine.py index 19667ae..1dae882 100644 --- a/src/strategies/backtest_engine.py +++ b/src/strategies/backtest_engine.py @@ -13,8 +13,8 @@ from ping_pong_bot import PingPongStrategy load_dotenv() class BacktestEngine: - def __init__(self, config_path="config/ping_pong_config.yaml"): - self.version = "1.7.9" + def __init__(self, config_path="config/ping_pong_config.yaml", starting_equity=1000.0): + self.version = "1.7.11" with open(config_path, 'r') as f: self.config = yaml.safe_load(f) @@ -23,12 +23,17 @@ class BacktestEngine: self.strategy.direction = self.direction # Virtual Exchange State - self.balance = 1000.0 # Starting USD - self.equity = 1000.0 + self.start_equity = starting_equity + self.balance = starting_equity + self.equity = starting_equity self.position_size = 0.0 # BTC self.position_value = 0.0 # USD self.entry_price = 0.0 + # Performance Tracking + self.max_equity = starting_equity + self.max_drawdown = 0.0 + # Settings self.fee_rate = 0.0005 # 0.05% Taker self.leverage = 5.0 # Will be updated based on mode @@ -39,6 +44,9 @@ class BacktestEngine: self.stop_loss_pct = 0.0 # 0.0 = Disabled self.stop_on_hurst_break = False + # Safety Brake Settings + self.use_brake = False + self.trades = [] self.equity_curve = [] @@ -75,7 +83,7 @@ class BacktestEngine: df[['open', 'high', 'low', 'close', 'volume']] = df[['open', 'high', 'low', 'close', 'volume']].astype(float) return df - def run(self, df, ma_df=None, ma_period=None): + def run(self, df, ma_df=None, ma_period=None, brake_df=None, brake_period=None): if df.empty: print("No data to run backtest.") return @@ -95,6 +103,17 @@ class BacktestEngine: ma_values = df['ma'].values print(f"Regime Switching enabled (MA {ma_period})") + # Prepare Brake MA + brake_values = None + if brake_df is not None and brake_period: + brake_df['brake_ma'] = brake_df['close'].rolling(window=brake_period).mean() + brake_subset = brake_df[['time', 'brake_ma']].rename(columns={'time': 'brake_time'}) + df = pd.merge_asof(df.sort_values('time'), brake_subset.sort_values('brake_time'), + left_on='time', right_on='brake_time', direction='backward') + brake_values = df['brake_ma'].values + self.use_brake = True + print(f"Safety Brake enabled (MA {brake_period})") + start_idx = max(self.config['rsi']['period'], self.config['hurst']['period'], 100) if start_idx >= len(df): print(f"Error: Not enough candles. Need {start_idx}, got {len(df)}") @@ -125,10 +144,19 @@ class BacktestEngine: signal = None if signal == "open": - self.open_position(price, time) + # Apply Safety Brake + if self.use_brake and brake_values is not None and not np.isnan(brake_values[i]): + if self.direction == "short" and price > brake_values[i]: + signal = None # Brake: Don't short in uptrend + elif self.direction == "long" and price < brake_values[i]: + signal = None # Brake: Don't long in downtrend + + if signal == "open": + self.open_position(price, time) elif signal == "close" and abs(self.position_size) > 0: self.close_partial_position(price, time) + # Mark to Market Equity unrealized = 0 if self.direction == "long": unrealized = self.position_size * (price - self.entry_price) if self.position_size > 0 else 0 @@ -136,6 +164,15 @@ class BacktestEngine: unrealized = abs(self.position_size) * (self.entry_price - price) if self.position_size < 0 else 0 self.equity = self.balance + unrealized + + # Max Drawdown Tracking + if self.equity > self.max_equity: + self.max_equity = self.equity + + dd = (self.max_equity - self.equity) / self.max_equity + if dd > self.max_drawdown: + self.max_drawdown = dd + self.equity_curve.append({"time": time, "equity": self.equity}) self.print_results() @@ -186,8 +223,8 @@ class BacktestEngine: self.trades.append({"time": time, "type": reason, "price": price, "pnl": pnl, "fee": fee}) def print_results(self): - total_pnl = self.equity - 1000.0 - roi = (total_pnl / 1000.0) * 100 + total_pnl = self.equity - self.start_equity + roi = (total_pnl / self.start_equity) * 100 fees = sum(t['fee'] for t in self.trades) sl_hits = len([t for t in self.trades if "Stop Loss" in t['type']]) print("\n" + "="*30) @@ -198,6 +235,7 @@ class BacktestEngine: print(f"Final Equity: ${self.equity:.2f}") print(f"Total PnL: ${total_pnl:.2f}") print(f"ROI: {roi:.2f}%") + print(f"Max Drawdown: {self.max_drawdown*100:.2f}%") print(f"Total Fees: ${fees:.2f}") print("="*30) @@ -205,17 +243,21 @@ async def main(): parser = argparse.ArgumentParser(description='Ping-Pong Strategy Backtester') parser.add_argument('--config', type=str, default='config/ping_pong_config.yaml') parser.add_argument('--limit', type=int, default=10000) + parser.add_argument('--interval', type=str, help='Strategy Interval (e.g. 5m, 15m)') parser.add_argument('--start_date', type=str) parser.add_argument('--end_date', type=str) parser.add_argument('--ma_period', type=int) parser.add_argument('--ma_interval', type=str, default='1h') + parser.add_argument('--brake_period', type=int, help='Safety Brake MA Period') + parser.add_argument('--brake_interval', type=str, default='1h', help='Safety Brake MA Interval') parser.add_argument('--direction', type=str, choices=['long', 'short']) parser.add_argument('--stop_loss', type=float, default=0.0, help='Stop Loss % (e.g. 0.02 for 2%)') parser.add_argument('--hurst_stop', action='store_true', help='Enable Stop Loss on Hurst break') parser.add_argument('--maker_fee', type=float, help='Override fee rate for Maker simulation (e.g. 0.0002)') + parser.add_argument('--starting_equity', type=float, default=1000.0, help='Initial balance') args = parser.parse_args() - engine = BacktestEngine(config_path=args.config) + engine = BacktestEngine(config_path=args.config, starting_equity=args.starting_equity) if args.maker_fee: engine.fee_rate = args.maker_fee @@ -224,19 +266,27 @@ async def main(): engine.stop_loss_pct = args.stop_loss engine.stop_on_hurst_break = args.hurst_stop + # Base Data symbol = engine.config['symbol'].replace("USDT", "").replace("USD", "") - df = await engine.load_data(symbol, "1m", limit=args.limit, start_date=args.start_date, end_date=args.end_date) + data_interval = args.interval if args.interval else engine.config['interval'] + if data_interval.isdigit(): data_interval += "m" + + df = await engine.load_data(symbol, data_interval, limit=args.limit, start_date=args.start_date, end_date=args.end_date) if df.empty: return ma_df = None if args.ma_period: ma_df = await engine.load_data(symbol, args.ma_interval, limit=5000, start_date=None, end_date=args.end_date) + brake_df = None + if args.brake_period: + brake_df = await engine.load_data(symbol, args.brake_interval, limit=5000, start_date=None, end_date=args.end_date) + if args.direction: engine.direction = args.direction engine.strategy.direction = args.direction - engine.run(df, ma_df=ma_df, ma_period=args.ma_period) + engine.run(df, ma_df=ma_df, ma_period=args.ma_period, brake_df=brake_df, brake_period=args.brake_period) if __name__ == "__main__": asyncio.run(main())