fixed sac issues

gru_sac_predictor/main.py

@@ -97,7 +97,7 @@ SAC_REWARD_SCALE = 1.0 # Decreased from 10.0 -> 2.0 -> 1.0
 SAC_USE_BATCH_NORM = True
 SAC_USE_RESIDUAL = True
 SAC_MODEL_DIR = 'models/simplified_sac' # Default dir within the agent class
-SAC_EPOCHS = 50 # Keep this from previous config for training loop control
+SAC_EPOCHS = 5 # Keep this from previous config for training loop control
 
 # V7.9 Experience Generation Config (Based on instructions.txt)
 # TOTAL_TRAINING_STEPS = 1000 # Removed - Not used in current training loop

gru_sac_predictor/results/20250416_182038/backtest_performance_report_20250416_182038.md

@@ -0,0 +1,41 @@
+# GRU+SAC Backtesting Performance Report
+
+Report generated on: 2025-04-16 18:25:01.350032
+Data range: N/A
+Total duration: N/A
+
+## Strategy Performance Metrics
+
+* **Initial capital:** $0.00
+* **Final portfolio value:** $0.00
+* **Total return:** 0.00%
+* **Annualized return:** 0.00%
+* **Sharpe ratio (annualized):** 0.0000
+* **Sortino ratio (annualized):** 0.0000
+* **Volatility (annualized):** 0.00%
+* **Maximum drawdown:** 0.00%
+* **Total trades:** 0
+
+## Buy and Hold Benchmark
+
+* *Buy and Hold benchmark could not be calculated.*
+
+## Position & Prediction Analysis
+
+* **Average absolute position size:** 0.0000
+* **Position sign accuracy vs return:** 0.00%
+* **Prediction sign accuracy vs return:** 0.00%
+* **Prediction RMSE (on returns):** 0.000000
+
+## Correlations
+
+* **Prediction-Return correlation:** 0.0000
+* **Prediction-Position correlation:** 0.0000
+* **Uncertainty-Position Size correlation:** 0.0000
+
+## Notes
+
+* Transaction cost used: 0.0500% per position change value.
+* GRU lookback period: 60 minutes.
+* V6 features + return features used.
+* Uncertainty estimated via MC Dropout standard deviation.

gru_sac_predictor/results/20250416_183051/backtest_performance_report_20250416_183051.md

@@ -0,0 +1,41 @@
+# GRU+SAC Backtesting Performance Report
+
+Report generated on: 2025-04-16 18:31:42.150811
+Data range: N/A
+Total duration: N/A
+
+## Strategy Performance Metrics
+
+* **Initial capital:** $0.00
+* **Final portfolio value:** $0.00
+* **Total return:** 0.00%
+* **Annualized return:** 0.00%
+* **Sharpe ratio (annualized):** 0.0000
+* **Sortino ratio (annualized):** 0.0000
+* **Volatility (annualized):** 0.00%
+* **Maximum drawdown:** 0.00%
+* **Total trades:** 0
+
+## Buy and Hold Benchmark
+
+* *Buy and Hold benchmark could not be calculated.*
+
+## Position & Prediction Analysis
+
+* **Average absolute position size:** 0.0000
+* **Position sign accuracy vs return:** 0.00%
+* **Prediction sign accuracy vs return:** 0.00%
+* **Prediction RMSE (on returns):** 0.000000
+
+## Correlations
+
+* **Prediction-Return correlation:** 0.0000
+* **Prediction-Position correlation:** 0.0000
+* **Uncertainty-Position Size correlation:** 0.0000
+
+## Notes
+
+* Transaction cost used: 0.0500% per position change value.
+* GRU lookback period: 60 minutes.
+* V6 features + return features used.
+* Uncertainty estimated via MC Dropout standard deviation.

gru_sac_predictor/results/20250416_183051/config_20250416_183051.json

@@ -0,0 +1,66 @@
+{
+    "run_id": "20250416_183051",
+    "db_dir": "../downloaded_data",
+    "ticker": "BTC-USD",
+    "exchange": "COINBASE",
+    "start_date": "2025-03-01",
+    "end_date": "2025-03-10",
+    "interval": "1min",
+    "model_save_path": "gru_sac_predictor/models/run_20250416_183051",
+    "results_plot_path": "gru_sac_predictor/results/20250416_183051/backtest_results_20250416_183051.png",
+    "report_save_path": "gru_sac_predictor/results/20250416_183051/backtest_performance_report_20250416_183051.md",
+    "train_ratio": 0.6,
+    "validation_ratio": 0.2,
+    "gru_lookback": 60,
+    "gru_prediction_horizon": 1,
+    "gru_epochs": 20,
+    "gru_batch_size": 32,
+    "gru_patience": 10,
+    "gru_lr_factor": 0.5,
+    "gru_return_scale": 0.03,
+    "gru_model_load_run_id": "20250416_142744",
+    "sac_state_dim": 5,
+    "sac_hidden_size": 64,
+    "sac_gamma": 0.97,
+    "sac_tau": 0.02,
+    "sac_actor_lr": 1.5e-05,
+    "sac_critic_lr": 2.5e-05,
+    "sac_batch_size": 64,
+    "sac_buffer_max_size": 20000,
+    "sac_min_buffer_size": 1000,
+    "sac_update_interval": 1,
+    "sac_target_update_interval": 2,
+    "sac_gradient_clip": 1.0,
+    "sac_reward_scale": 1.0,
+    "sac_use_batch_norm": true,
+    "sac_use_residual": true,
+    "sac_model_dir": "models/simplified_sac",
+    "sac_epochs": 5,
+    "experience_config": {
+        "initial_experiences": 3000,
+        "experiences_per_batch": 64,
+        "batch_generation_interval": 500,
+        "balance_market_regimes": false,
+        "recency_bias_strength": 0.5,
+        "high_uncertainty_quantile": 0.75,
+        "extreme_return_quantile": 0.1,
+        "min_uncertainty_ratio": 0.2,
+        "min_extreme_return_ratio": 0.1,
+        "use_parallel_generation": false,
+        "precompute_all_gru_outputs": true,
+        "buffer_update_strategy": "fifo",
+        "training_iterations_per_step": 1
+    },
+    "initial_capital": 10000.0,
+    "transaction_cost": 0.0005,
+    "opportunity_cost_penalty_factor": 0.0,
+    "high_return_threshold": 0.002,
+    "action_tolerance": 0.3,
+    "load_existing_system": true,
+    "train_gru_model": false,
+    "train_sac_agent": true,
+    "load_sac_agent": false,
+    "run_backtest": true,
+    "generate_plots": true,
+    "generate_report": true
+}

gru_sac_predictor/results/20250416_183508/backtest_performance_report_20250416_183508.md

@@ -0,0 +1,42 @@
+# GRU+SAC Backtesting Performance Report
+
+Report generated on: 2025-04-16 18:36:19.355066
+Data range: 2025-03-06 15:23:00+00:00 to 2025-03-07 23:57:00+00:00
+Total duration: 1 days 08:34:00
+
+## Strategy Performance Metrics
+
+* **Initial capital:** $10,000.00
+* **Final portfolio value:** $10,102.70
+* **Total return:** 1.03%
+* **Annualized return:** 1484.12%
+* **Sharpe ratio (annualized):** 3.2039
+* **Sortino ratio (annualized):** 4.8489
+* **Volatility (annualized):** 102.65%
+* **Maximum drawdown:** 7.56%
+* **Total trades:** 1489
+
+## Buy and Hold Benchmark
+
+* **Final value (B&H):** $9,658.75
+* **Total return (B&H):** -3.41%
+
+## Position & Prediction Analysis
+
+* **Average absolute position size:** 0.9056
+* **Position sign accuracy vs return:** 50.93%
+* **Prediction sign accuracy vs return:** 48.92%
+* **Prediction RMSE (on returns):** 0.004036
+
+## Correlations
+
+* **Prediction-Return correlation:** -0.0042
+* **Prediction-Position correlation:** 0.1459
+* **Uncertainty-Position Size correlation:** 0.8410
+
+## Notes
+
+* Transaction cost used: 0.0500% per position change value.
+* GRU lookback period: 60 minutes.
+* V6 features + return features used.
+* Uncertainty estimated via MC Dropout standard deviation.

gru_sac_predictor/results/20250416_183508/config_20250416_183508.json

@@ -0,0 +1,66 @@
+{
+    "run_id": "20250416_183508",
+    "db_dir": "../downloaded_data",
+    "ticker": "BTC-USD",
+    "exchange": "COINBASE",
+    "start_date": "2025-03-01",
+    "end_date": "2025-03-10",
+    "interval": "1min",
+    "model_save_path": "gru_sac_predictor/models/run_20250416_183508",
+    "results_plot_path": "gru_sac_predictor/results/20250416_183508/backtest_results_20250416_183508.png",
+    "report_save_path": "gru_sac_predictor/results/20250416_183508/backtest_performance_report_20250416_183508.md",
+    "train_ratio": 0.6,
+    "validation_ratio": 0.2,
+    "gru_lookback": 60,
+    "gru_prediction_horizon": 1,
+    "gru_epochs": 20,
+    "gru_batch_size": 32,
+    "gru_patience": 10,
+    "gru_lr_factor": 0.5,
+    "gru_return_scale": 0.03,
+    "gru_model_load_run_id": "20250416_142744",
+    "sac_state_dim": 5,
+    "sac_hidden_size": 64,
+    "sac_gamma": 0.97,
+    "sac_tau": 0.02,
+    "sac_actor_lr": 1.5e-05,
+    "sac_critic_lr": 2.5e-05,
+    "sac_batch_size": 64,
+    "sac_buffer_max_size": 20000,
+    "sac_min_buffer_size": 1000,
+    "sac_update_interval": 1,
+    "sac_target_update_interval": 2,
+    "sac_gradient_clip": 1.0,
+    "sac_reward_scale": 1.0,
+    "sac_use_batch_norm": true,
+    "sac_use_residual": true,
+    "sac_model_dir": "models/simplified_sac",
+    "sac_epochs": 5,
+    "experience_config": {
+        "initial_experiences": 3000,
+        "experiences_per_batch": 64,
+        "batch_generation_interval": 500,
+        "balance_market_regimes": false,
+        "recency_bias_strength": 0.5,
+        "high_uncertainty_quantile": 0.75,
+        "extreme_return_quantile": 0.1,
+        "min_uncertainty_ratio": 0.2,
+        "min_extreme_return_ratio": 0.1,
+        "use_parallel_generation": false,
+        "precompute_all_gru_outputs": true,
+        "buffer_update_strategy": "fifo",
+        "training_iterations_per_step": 1
+    },
+    "initial_capital": 10000.0,
+    "transaction_cost": 0.0005,
+    "opportunity_cost_penalty_factor": 0.0,
+    "high_return_threshold": 0.002,
+    "action_tolerance": 0.3,
+    "load_existing_system": true,
+    "train_gru_model": false,
+    "train_sac_agent": true,
+    "load_sac_agent": false,
+    "run_backtest": true,
+    "generate_plots": true,
+    "generate_report": true
+}

gru_sac_predictor/src/trading_system.py

@@ -375,7 +375,7 @@ class TradingSystem:
         if self.gru_model and self.gru_model.is_loaded:
             self.feature_scaler = self.gru_model.feature_scaler
             self.y_scaler = self.gru_model.y_scaler
-            self._logger.info("Scalers initialized from pre-loaded GRU model.")
+            _logger.info("Scalers initialized from pre-loaded GRU model.")
             # V7.23: Attempt to set indices if scaler loaded
             self._set_feature_indices()
 
@@ -1262,6 +1262,13 @@ class ExtendedBacktester:
              feature_logger.error(f"Error during pre-computation evaluate call on test data: {e}", exc_info=True) # Use feature_logger
              return None
 
+        # --- Calculate num_sequences FIRST ---
+        # Moved from below to be available for feature extraction
+        num_sequences = len(all_pred_returns)
+        if num_sequences <= 1:
+            feature_logger.warning("Not enough sequences generated from test data to perform backtest.") # Use feature_logger
+            return None
+
         # --- V7.13 START: Extract Momentum and Volatility Features ---
         # These features should be aligned with the *sequences* used for GRU prediction
         # Use test_features_df which is aligned with the sequences' start times
@@ -1300,11 +1307,6 @@ class ExtendedBacktester:
              return None
         # --- V7.13 END: Extract Momentum and Volatility Features ---
 
-        num_sequences = len(all_pred_returns)
-        if num_sequences <= 1:
-            feature_logger.warning("Not enough sequences generated from test data to perform backtest.") # Use feature_logger
-            return None
-
         feature_logger.info("--- GRU Pre-computation Complete. Starting Backtest Simulation ---") # Use feature_logger
 
         # --- Refined Timestamp Handling START (from original test_data before preprocessing) ---