perf(qav3): tune pivot labeling optimization thresholds

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>

diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
index 1cdb079899579154297b6ac48607597aa8bbdbd6..a1c2800138c28f1486b563c796e98d630e39fe76 100644 (file)
--- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
+++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
@@ -549,12 +549,8 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
         label_period_candles: int,
     ) -> tuple[float, float]:
         label_period_cycles = fit_live_predictions_candles / label_period_candles
-        thresholds_candles = int(
-            self.freqai_info.get(
-                "prediction_thresholds_candles",
-                max(2, int(label_period_cycles)) * label_period_candles,
-            )
-        )
+        thresholds_candles = max(2, int(label_period_cycles)) * label_period_candles
+
         pred_extrema = pred_df.get(EXTREMA_COLUMN).iloc[-thresholds_candles:].copy()
         thresholds_smoothing = str(
             self.freqai_info.get("prediction_thresholds_smoothing", "mean")
@@ -1420,7 +1416,7 @@ def label_objective(
         max_label_period_candles,
         step=candles_step,
     )
-    label_natr_ratio = trial.suggest_float("label_natr_ratio", 8.5, 15.5, step=0.05)
+    label_natr_ratio = trial.suggest_float("label_natr_ratio", 8.5, 14.5, step=0.05)
 
     label_period_cycles = fit_live_predictions_candles / label_period_candles
     df = df.iloc[-(max(2, int(label_period_cycles)) * label_period_candles) :]

diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py
index 67b285c218b1acf00e0185a4db7590e40d8fab54..39542b9426ae89a3c34c586e3761930715abd565 100644 (file)
--- a/quickadapter/user_data/strategies/QuickAdapterV3.py
+++ b/quickadapter/user_data/strategies/QuickAdapterV3.py
@@ -1117,8 +1117,8 @@ class QuickAdapterV3(IStrategy):
         side: str,
         order: Literal["entry", "exit"],
         rate: float,
-        min_natr_ratio_percent: float = 0.0095,
-        max_natr_ratio_percent: float = 0.095,
+        min_natr_ratio_percent: float = 0.009,
+        max_natr_ratio_percent: float = 0.09,
         lookback_period: int = 1,
         decay_ratio: float = 0.5,
     ) -> bool: