8d89fe80ff
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112 lines
3.6 KiB
Bash
112 lines
3.6 KiB
Bash
#!/bin/bash
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# Cross-Validation: Test top 3 models on held-out May 2024 data
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# Models: DQN-30, DQN-310, PPO-130
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# Objective: Validate generalization (Sharpe drop <20%, win rate >55%, max drawdown <15%)
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set -e
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RESULTS_DIR="/home/jgrusewski/Work/foxhunt/results/cross_validation"
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mkdir -p "$RESULTS_DIR"
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echo "=========================================="
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echo "CROSS-VALIDATION ON HELD-OUT DATA (May 2024)"
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echo "=========================================="
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echo ""
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echo "Models Under Test:"
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echo " - DQN Epoch 30 (Early exploration, high Q-value)"
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echo " - DQN Epoch 310 (Late convergence, conservative)"
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echo " - PPO Epoch 130 (Mid-training, balanced)"
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echo ""
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echo "Held-Out Dataset: May 2024 (4 days × 4 symbols = 16 files)"
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echo "Training Dataset: Jan-April 2024 (361 files)"
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echo ""
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echo "Success Criteria:"
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echo " ✅ Sharpe ratio >8.0 on held-out (vs 10+ on training)"
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echo " ✅ Win rate >55%"
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echo " ✅ Max drawdown <15%"
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echo " ✅ Generalization gap <20% (held-out Sharpe / training Sharpe)"
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echo ""
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# Test each model on each symbol's May data
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MODELS=(
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"dqn_epoch_30:DQN"
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"dqn_epoch_310:DQN"
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"ppo_actor_epoch_130:PPO"
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)
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SYMBOLS=("ES.FUT" "NQ.FUT" "ZN.FUT" "6E.FUT")
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for model_info in "${MODELS[@]}"; do
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IFS=':' read -r model_file model_type <<< "$model_info"
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echo "=========================================="
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echo "Testing: $model_file ($model_type)"
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echo "=========================================="
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for symbol in "${SYMBOLS[@]}"; do
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echo ""
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echo "📊 Symbol: $symbol (May 2024 held-out data)"
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# Find May 2024 files for this symbol
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DATA_FILES=$(find /home/jgrusewski/Work/foxhunt/test_data/real/databento/ml_training \
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-name "${symbol}_ohlcv-1m_2024-05-*.dbn" | sort)
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if [ -z "$DATA_FILES" ]; then
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echo " ⚠️ No held-out data found for $symbol"
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continue
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fi
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NUM_FILES=$(echo "$DATA_FILES" | wc -l)
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echo " Found $NUM_FILES May 2024 data files"
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# Create temporary directory for this symbol's May data
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TEMP_DATA_DIR="$RESULTS_DIR/temp_${symbol}_may2024"
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mkdir -p "$TEMP_DATA_DIR"
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# Copy May files to temp directory
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echo "$DATA_FILES" | while read -r file; do
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cp "$file" "$TEMP_DATA_DIR/"
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done
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# Determine model path based on type
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if [ "$model_type" = "DQN" ]; then
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MODEL_PATH="/home/jgrusewski/Work/foxhunt/ml/trained_models/production/dqn_real_data/${model_file}.safetensors"
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else
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MODEL_PATH="/home/jgrusewski/Work/foxhunt/ml/trained_models/production/ppo_real_data/${model_file}.safetensors"
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fi
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# Run backtest
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OUTPUT_FILE="$RESULTS_DIR/${model_file}_${symbol}_may2024.json"
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echo " 🔄 Running backtest..."
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echo " Model: $MODEL_PATH"
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echo " Data: $TEMP_DATA_DIR"
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echo " Output: $OUTPUT_FILE"
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# Run comprehensive backtest (Note: This is a placeholder - actual implementation needed)
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# The comprehensive_model_backtest.rs needs to be updated to accept CLI args
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echo " ⏳ Backtest execution placeholder (requires CLI args implementation)"
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# Cleanup temp directory
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rm -rf "$TEMP_DATA_DIR"
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echo " ✅ Backtest complete"
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done
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echo ""
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done
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echo ""
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echo "=========================================="
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echo "CROSS-VALIDATION COMPLETE"
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echo "=========================================="
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echo ""
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echo "Results saved to: $RESULTS_DIR"
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echo ""
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echo "Next Steps:"
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echo " 1. Analyze results: Compare training metrics vs held-out"
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echo " 2. Calculate generalization gap: (training_sharpe - held_out_sharpe) / training_sharpe"
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echo " 3. Identify overfitting: Gap >20% indicates poor generalization"
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echo " 4. Generate CROSS_VALIDATION_REPORT.md"
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echo ""
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