5f7702469e
- Removed v10 TradingView indicator (moneyline_v10_momentum_dots.pinescript) - Removed v10 penalty system from signal-quality.ts (-30/-25 point penalties) - Removed backtest result files (sweep_*.csv) - Updated copilot-instructions.md to remove v10 references - Simplified direction-specific quality thresholds (LONG 90+, SHORT 80+) Rationale: - 1,944 parameter combinations tested in backtest - All top results IDENTICAL (568 trades, $498 P&L, 61.09% WR) - Momentum parameters had ZERO impact on trade selection - Profit factor 1.027 too low (barely profitable after fees) - Max drawdown -$1,270 vs +$498 profit = terrible risk-reward - v10 penalties were blocking good trades (bug: applied to wrong positions) Keeping v9 as production system - simpler, proven, effective.
71 lines
2.8 KiB
Python
71 lines
2.8 KiB
Python
from __future__ import annotations
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import argparse
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import dataclasses
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from pathlib import Path
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from typing import Optional
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import pandas as pd
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from backtester.data_loader import load_csv
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from backtester.indicators.money_line import MoneyLineInputs
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from backtester.simulator import TradeConfig, simulate_money_line
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def parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser(description="Run Money Line backtests against CSV OHLCV data.")
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parser.add_argument("--csv", type=Path, required=True, help="Path to CSV file with timestamp, open, high, low, close, volume columns")
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parser.add_argument("--symbol", type=str, required=True, help="Symbol label (e.g., SOL-PERP)")
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parser.add_argument("--timeframe", type=str, default="5", help="Timeframe label for reference (default: 5)")
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parser.add_argument("--start", type=str, default=None, help="Optional ISO timestamp for start filter (e.g., 2024-01-01)")
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parser.add_argument("--end", type=str, default=None, help="Optional ISO timestamp for end filter")
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parser.add_argument("--position-size", type=float, default=1000.0, dest="position_size", help="Notional size in USD for each simulated trade")
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parser.add_argument("--max-bars", type=int, default=None, help="Maximum bars to hold a trade before force exit")
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parser.add_argument("--export-trades", type=Path, default=None, help="Optional path to write detailed trade results as CSV")
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return parser.parse_args()
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def main() -> None:
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args = parse_args()
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data_slice = load_csv(
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path=args.csv,
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symbol=args.symbol,
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timeframe=args.timeframe,
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start=args.start,
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end=args.end,
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)
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df = data_slice.data
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if not isinstance(df.index, pd.DatetimeIndex):
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df = df.copy()
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df.index = pd.to_datetime(df.index)
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config = TradeConfig(position_size=args.position_size, max_bars_per_trade=args.max_bars)
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inputs = MoneyLineInputs()
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result = simulate_money_line(df=df, symbol=data_slice.symbol, inputs=inputs, config=config)
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print("=== Backtest Summary ===")
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print(f"Symbol: {data_slice.symbol}")
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print(f"Rows processed: {len(df)}")
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print(f"Trades: {len(result.trades)}")
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print(f"Total PnL: ${result.total_pnl:,.2f}")
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print(f"Average PnL: ${result.average_pnl:,.2f}")
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print(f"Win rate: {result.win_rate * 100:.2f}%")
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print(f"Max drawdown: ${result.max_drawdown:,.2f}")
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if args.export_trades:
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trades_df = pd.DataFrame(
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[
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{k: v for k, v in dataclasses.asdict(trade).items() if k != "_exit_index"}
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for trade in result.trades
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]
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)
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trades_df.to_csv(args.export_trades, index=False)
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print(f"Detailed trades exported to {args.export_trades}")
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if __name__ == "__main__":
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main()
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