feat: strategy parameter sweep and production param optimization

- Add independent backtest engine (backtester.py) with walk-forward support
- Add backtest sanity check validator (backtest_validator.py)
- Add CLI tools: run_backtest.py, strategy_sweep.py (with --combined mode)
- Fix train-serve skew: unify feature z-score normalization (ml_features.py)
- Add strategy params (SL/TP ATR mult, ADX filter, volume multiplier) to
  config.py, indicators.py, dataset_builder.py, bot.py, backtester.py
- Fix WalkForwardBacktester not propagating strategy params to test folds
- Update production defaults: SL=2.0x, TP=2.0x, ADX=25, Vol=2.5
  (3-symbol combined PF: 0.71 → 1.24, MDD: 65.9% → 17.1%)
- Retrain ML models with new strategy parameters

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

tests/test_bot.py

@@ -246,7 +246,7 @@ async def test_process_candle_fetches_oi_and_funding(config, sample_df):
         mock_ind.get_signal.return_value = "LONG"
         mock_ind_cls.return_value = mock_ind
 
-        with patch("src.bot.build_features") as mock_build:
+        with patch("src.bot.build_features_aligned") as mock_build:
             from src.ml_features import FEATURE_COLS
             mock_build.return_value = pd.Series({col: 0.0 for col in FEATURE_COLS})
             bot.ml_filter.is_model_loaded = MagicMock(return_value=False)