moen0
29 lines
1.3 KiB
Python
29 lines
1.3 KiB
Python
from data.loader import load_candles, resample_candles
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from engine.backtester import run_backtest
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from strategies.categorical_strategy import CategoricalStrategy
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candles_1m = load_candles("data/gbpjpy_jan.csv")
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candles_5m = resample_candles(candles_1m, period=5)
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best_pnl = float("-inf")
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best_params = None
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for lookback in [10, 15, 20, 30, 40, 50]:
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for threshold in [0.2, 0.3, 0.4, 0.5, 0.7, 1.0]:
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for atr_mult in [0.3, 0.4, 0.5, 0.6, 0.7]:
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strategy = CategoricalStrategy(
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lookback=lookback,
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range_threshold=threshold,
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atr_multiplier=atr_mult
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)
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trades = run_backtest(candles_5m, strategy, 10000)
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if len(trades) < 50:
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continue
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total_pnl = sum(t.pnl for t in trades)
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win_rate = len([t for t in trades if t.pnl > 0]) / len(trades) * 100
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if total_pnl > best_pnl:
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best_pnl = total_pnl
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best_params = (lookback, threshold, atr_mult)
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print(f"New best: LB={lookback}, TH={threshold}, ATR={atr_mult} -> PnL={total_pnl:.2f}, WR={win_rate:.1f}%, Trades={len(trades)}")
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print(f"\nBest: lookback={best_params[0]}, threshold={best_params[1]}, atr_mult={best_params[2]}, PnL={best_pnl:.2f}") |