From: Jérôme Benoit <jerome.benoit@piment-noir.org>
Date: Fri, 28 Feb 2025 13:49:31 +0000 (+0100)
Subject: perf(qav3): fine tune long/short IQR signal for the gaussian window
X-Git-Url: https://git.piment-noir.org/?a=commitdiff_plain;h=1d026313062150f19b23405084453f0fd912392f;p=freqai-strategies.git

perf(qav3): fine tune long/short IQR signal for the gaussian window

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

diff --git a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
index d016e04..227b9af 100644
--- a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
@@ -507,10 +507,10 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
             fit_live_predictions_candles / (label_period_candles * 2)
         )
         min_pred = pred_df_sorted.iloc[-label_period_frequency:].quantile(
-            self.freqai_info.get("min_quantile", 0.75)
+            self.freqai_info.get("min_quantile", 0.67)
         )
         max_pred = pred_df_sorted.iloc[:label_period_frequency].quantile(
-            self.freqai_info.get("max_quantile", 0.75)
+            self.freqai_info.get("max_quantile", 0.67)
         )
         return min_pred[EXTREMA_COLUMN], max_pred[EXTREMA_COLUMN]
 
diff --git a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
index b0df554..f0860ca 100644
--- a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
@@ -508,10 +508,10 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
             fit_live_predictions_candles / (label_period_candles * 2)
         )
         min_pred = pred_df_sorted.iloc[-label_period_frequency:].quantile(
-            self.freqai_info.get("min_quantile", 0.75)
+            self.freqai_info.get("min_quantile", 0.67)
         )
         max_pred = pred_df_sorted.iloc[:label_period_frequency].quantile(
-            self.freqai_info.get("max_quantile", 0.75)
+            self.freqai_info.get("max_quantile", 0.67)
         )
         return min_pred[EXTREMA_COLUMN], max_pred[EXTREMA_COLUMN]