fix: replace unicode chars that break Windows cp1252 encoding
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config/current_config.json
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84
config/current_config.json
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{
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"model_type": "xgboost",
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"features": {
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"technical_indicators": [
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"RSI_14",
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"RSI_7",
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"RSI_21",
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"MACD_line",
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"MACD_signal",
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"MACD_hist",
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"BB_upper",
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"BB_lower",
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"BB_width",
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"ATR_14",
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"SMA_5",
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"SMA_10",
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"SMA_20",
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"SMA_50",
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"SMA_200",
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"EMA_5",
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"EMA_10",
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"EMA_20",
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"EMA_50",
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"OBV",
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"stoch_k",
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"stoch_d",
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"williams_r",
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"CCI_20",
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"ROC_10",
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"keltner_upper",
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"keltner_lower"
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],
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"lookback_periods": [
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3,
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5,
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10,
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20
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],
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"use_volume_features": true,
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"use_volatility_features": true,
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"use_candle_patterns": true,
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"use_lag_features": true,
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"lag_periods": [
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1,
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2,
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3,
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5
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]
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},
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"target": {
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"type": "classification",
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"direction": "long",
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"horizon_candles": 6,
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"threshold_pct": 1.0
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},
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"hyperparameters": {
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"learning_rate": 0.05,
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"max_depth": 6,
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"n_estimators": 500,
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"subsample": 0.8,
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"colsample_bytree": 0.8,
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"min_child_weight": 5,
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"gamma": 0.1,
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"reg_alpha": 0.1,
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"reg_lambda": 1.0
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},
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"strategy": {
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"entry_threshold": 0.6,
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"exit_type": "trailing_stop",
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"stop_loss_pct": 2.0,
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"take_profit_pct": 4.0,
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"trailing_stop_pct": 1.5,
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"position_sizing": "confidence_scaled",
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"max_position_pct": 100,
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"min_confidence_to_trade": 0.55
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},
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"training": {
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"walk_forward_windows": 5,
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"train_pct": 0.7,
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"validation_pct": 0.15,
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"test_pct": 0.15
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},
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"timeframe": "4h"
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}
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BIN
llm_client/__pycache__/analyzer.cpython-313.pyc
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BIN
llm_client/__pycache__/analyzer.cpython-313.pyc
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@ -1,6 +1,6 @@
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#!/usr/bin/env python3
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"""
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BTC ML Trading Strategy — Train & Backtest Engine
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BTC ML Trading Strategy -- Train & Backtest Engine
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Self-contained script that runs on the Windows PC with GPU.
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Usage:
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@ -280,7 +280,7 @@ def walk_forward_train_test(df: pd.DataFrame, feature_cols: list, config: dict)
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try:
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model.fit(X_train, y_train)
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except Exception as e:
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print(f" Window {w+1}: training failed — {e}", file=sys.stderr)
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print(f" Window {w+1}: training failed -- {e}", file=sys.stderr)
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continue
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# Get predictions on test set
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@ -492,7 +492,7 @@ def compile_results(trades: list, per_window_sharpe: list,
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# ---------------------------------------------------------------------------
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def main():
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parser = argparse.ArgumentParser(description="BTC ML Trading — Train & Backtest")
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parser = argparse.ArgumentParser(description="BTC ML Trading -- Train & Backtest")
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parser.add_argument("--config", required=True, help="Path to config JSON")
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parser.add_argument("--data", required=True, help="Path to OHLCV CSV")
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parser.add_argument("--output", required=True, help="Path to output results JSON")
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@ -505,7 +505,7 @@ def main():
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# Load data
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print(f"Loading data from {args.data}...")
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df = pd.read_csv(args.data, parse_dates=["timestamp"])
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print(f" {len(df)} rows, {df['timestamp'].iloc[0]} → {df['timestamp'].iloc[-1]}")
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print(f" {len(df)} rows, {df['timestamp'].iloc[0]} -> {df['timestamp'].iloc[-1]}")
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# Compute features
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print("Computing features...")
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