diff --git a/config/current_config.json b/config/current_config.json
new file mode 100644
index 0000000..65d2da6
--- /dev/null
+++ b/config/current_config.json
@@ -0,0 +1,84 @@
+{
+  "model_type": "xgboost",
+  "features": {
+    "technical_indicators": [
+      "RSI_14",
+      "RSI_7",
+      "RSI_21",
+      "MACD_line",
+      "MACD_signal",
+      "MACD_hist",
+      "BB_upper",
+      "BB_lower",
+      "BB_width",
+      "ATR_14",
+      "SMA_5",
+      "SMA_10",
+      "SMA_20",
+      "SMA_50",
+      "SMA_200",
+      "EMA_5",
+      "EMA_10",
+      "EMA_20",
+      "EMA_50",
+      "OBV",
+      "stoch_k",
+      "stoch_d",
+      "williams_r",
+      "CCI_20",
+      "ROC_10",
+      "keltner_upper",
+      "keltner_lower"
+    ],
+    "lookback_periods": [
+      3,
+      5,
+      10,
+      20
+    ],
+    "use_volume_features": true,
+    "use_volatility_features": true,
+    "use_candle_patterns": true,
+    "use_lag_features": true,
+    "lag_periods": [
+      1,
+      2,
+      3,
+      5
+    ]
+  },
+  "target": {
+    "type": "classification",
+    "direction": "long",
+    "horizon_candles": 6,
+    "threshold_pct": 1.0
+  },
+  "hyperparameters": {
+    "learning_rate": 0.05,
+    "max_depth": 6,
+    "n_estimators": 500,
+    "subsample": 0.8,
+    "colsample_bytree": 0.8,
+    "min_child_weight": 5,
+    "gamma": 0.1,
+    "reg_alpha": 0.1,
+    "reg_lambda": 1.0
+  },
+  "strategy": {
+    "entry_threshold": 0.6,
+    "exit_type": "trailing_stop",
+    "stop_loss_pct": 2.0,
+    "take_profit_pct": 4.0,
+    "trailing_stop_pct": 1.5,
+    "position_sizing": "confidence_scaled",
+    "max_position_pct": 100,
+    "min_confidence_to_trade": 0.55
+  },
+  "training": {
+    "walk_forward_windows": 5,
+    "train_pct": 0.7,
+    "validation_pct": 0.15,
+    "test_pct": 0.15
+  },
+  "timeframe": "4h"
+}
\ No newline at end of file
diff --git a/llm_client/__pycache__/analyzer.cpython-313.pyc b/llm_client/__pycache__/analyzer.cpython-313.pyc
new file mode 100644
index 0000000..9e5dfd5
Binary files /dev/null and b/llm_client/__pycache__/analyzer.cpython-313.pyc differ
diff --git a/ml_engine/train_and_backtest.py b/ml_engine/train_and_backtest.py
index 8853ab2..d856b35 100755
--- a/ml_engine/train_and_backtest.py
+++ b/ml_engine/train_and_backtest.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
-BTC ML Trading Strategy — Train & Backtest Engine
+BTC ML Trading Strategy -- Train & Backtest Engine
 Self-contained script that runs on the Windows PC with GPU.
 
 Usage:
@@ -280,7 +280,7 @@ def walk_forward_train_test(df: pd.DataFrame, feature_cols: list, config: dict)
         try:
             model.fit(X_train, y_train)
         except Exception as e:
-            print(f"  Window {w+1}: training failed — {e}", file=sys.stderr)
+            print(f"  Window {w+1}: training failed -- {e}", file=sys.stderr)
             continue
 
         # Get predictions on test set
@@ -492,7 +492,7 @@ def compile_results(trades: list, per_window_sharpe: list,
 # ---------------------------------------------------------------------------
 
 def main():
-    parser = argparse.ArgumentParser(description="BTC ML Trading — Train & Backtest")
+    parser = argparse.ArgumentParser(description="BTC ML Trading -- Train & Backtest")
     parser.add_argument("--config", required=True, help="Path to config JSON")
     parser.add_argument("--data", required=True, help="Path to OHLCV CSV")
     parser.add_argument("--output", required=True, help="Path to output results JSON")
@@ -505,7 +505,7 @@ def main():
     # Load data
     print(f"Loading data from {args.data}...")
     df = pd.read_csv(args.data, parse_dates=["timestamp"])
-    print(f"  {len(df)} rows, {df['timestamp'].iloc[0]} → {df['timestamp'].iloc[-1]}")
+    print(f"  {len(df)} rows, {df['timestamp'].iloc[0]} -> {df['timestamp'].iloc[-1]}")
 
     # Compute features
     print("Computing features...")