From: Jérôme Benoit Date: Sun, 25 May 2025 09:40:58 +0000 (+0200) Subject: perf(qav3): recalibrate pivot labeling momentum interval under low volatility X-Git-Url: https://git.piment-noir.org/?a=commitdiff_plain;h=2de1d3b7ce3ce8d86a1204f92f2e37f69abff127;p=freqai-strategies.git perf(qav3): recalibrate pivot labeling momentum interval under low volatility Signed-off-by: Jérôme Benoit --- diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index 90045ad..37ad091 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -45,7 +45,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): https://github.com/sponsors/robcaulk """ - version = "3.7.63" + version = "3.7.64" @cached_property def _optuna_config(self) -> dict: @@ -963,8 +963,8 @@ def zigzag( def calculate_min_slope_strength( pos: int, - min_strength: float = 0.8, - max_strength: float = 1.6, + min_strength: float = 0.5, + max_strength: float = 1.5, ) -> float: volatility_quantile = calculate_volatility_quantile(pos) if np.isnan(volatility_quantile): diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py index 3d1bfaf..ab31045 100644 --- a/quickadapter/user_data/strategies/QuickAdapterV3.py +++ b/quickadapter/user_data/strategies/QuickAdapterV3.py @@ -60,7 +60,7 @@ class QuickAdapterV3(IStrategy): INTERFACE_VERSION = 3 def version(self) -> str: - return "3.3.65" + return "3.3.66" timeframe = "5m" diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py index a4a1a8e..b7a6f7f 100644 --- a/quickadapter/user_data/strategies/Utils.py +++ b/quickadapter/user_data/strategies/Utils.py @@ -441,8 +441,8 @@ def zigzag( def calculate_min_slope_strength( pos: int, - min_strength: float = 0.8, - max_strength: float = 1.6, + min_strength: float = 0.5, + max_strength: float = 1.5, ) -> float: volatility_quantile = calculate_volatility_quantile(pos) if np.isnan(volatility_quantile):