From: Jérôme Benoit Date: Wed, 30 Jul 2025 10:06:58 +0000 (+0200) Subject: perf(qav3): fine tune defaults after trade entry logic change X-Git-Url: https://git.piment-noir.org/?a=commitdiff_plain;h=cd896b1a4f38940097978ef09d388ba208082476;p=freqai-strategies.git perf(qav3): fine tune defaults after trade entry logic change Signed-off-by: Jérôme Benoit --- diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index a0a843f..13cdb5f 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -51,7 +51,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): https://github.com/sponsors/robcaulk """ - version = "3.7.103" + version = "3.7.104" @cached_property def _optuna_config(self) -> dict[str, Any]: @@ -528,7 +528,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): ) pred_extrema = pred_df.get(EXTREMA_COLUMN).iloc[-thresholds_candles:] thresholds_smoothing = str( - self.freqai_info.get("prediction_thresholds_smoothing", "exp_weighted_mean") + self.freqai_info.get("prediction_thresholds_smoothing", "mean") ) thresholds_smoothing_methods = { "exp_weighted_mean", @@ -542,7 +542,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): } if thresholds_smoothing == "exp_weighted_mean": thresholds_alpha = float( - self.freqai_info.get("prediction_thresholds_alpha", 75.0) + self.freqai_info.get("prediction_thresholds_alpha", 100.0) ) return QuickAdapterRegressorV3.exp_weighted_mean_min_max( pred_extrema, thresholds_alpha @@ -639,22 +639,22 @@ class QuickAdapterRegressorV3(BaseRegressionModel): "cityblock", "correlation", "cosine", - "dice", + # "dice", "euclidean", - "hamming", - "jaccard", + # "hamming", + # "jaccard", "jensenshannon", - "kulczynski1", + # "kulczynski1", "mahalanobis", - "matching", + # "matching", "minkowski", - "rogerstanimoto", - "russellrao", + # "rogerstanimoto", + # "russellrao", "seuclidean", - "sokalmichener", - "sokalsneath", + # "sokalmichener", + # "sokalsneath", "sqeuclidean", - "yule", + # "yule", "hellinger", "shellinger", "geometric_mean", @@ -721,22 +721,22 @@ class QuickAdapterRegressorV3(BaseRegressionModel): "cityblock", "correlation", "cosine", - "dice", + # "dice", "euclidean", - "hamming", - "jaccard", + # "hamming", + # "jaccard", "jensenshannon", - "kulczynski1", # deprecated since version 1.15.0 + # "kulczynski1", # deprecated since version 1.15.0 "mahalanobis", - "matching", + # "matching", "minkowski", - "rogerstanimoto", - "russellrao", + # "rogerstanimoto", + # "russellrao", "seuclidean", - "sokalmichener", # deprecated since version 1.15.0 - "sokalsneath", + # "sokalmichener", # deprecated since version 1.15.0 + # "sokalsneath", "sqeuclidean", - "yule", + # "yule", }: cdist_kwargs = {"w": np_weights} if metric in { diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py index 36c7154..00bb8a3 100644 --- a/quickadapter/user_data/strategies/QuickAdapterV3.py +++ b/quickadapter/user_data/strategies/QuickAdapterV3.py @@ -65,7 +65,7 @@ class QuickAdapterV3(IStrategy): INTERFACE_VERSION = 3 def version(self) -> str: - return "3.3.111" + return "3.3.112" timeframe = "5m" @@ -94,9 +94,10 @@ class QuickAdapterV3(IStrategy): # {stage: (natr_ratio_percent, stake_percent)} partial_exit_stages: dict[int, tuple[float, float]] = { - 0: (0.4, 0.35), - 1: (0.7, 0.75), - 2: (0.9, 0.5), + 0: (0.4167, 0.4167), + 1: (0.6667, 0.25), + 2: (0.8333, 0.1667), + 3: (0.9167, 0.0833), } timeframe_minutes = timeframe_to_minutes(timeframe)