From 9ddeec4525adbb25f0383abbdbb2c5b6053fd7b1 Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Thu, 17 Apr 2025 18:54:14 +0200 Subject: [PATCH] perf(qav3): fine tune prediction thresholds and stoploss distance MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit Signed-off-by: Jérôme Benoit --- .../user_data/freqaimodels/QuickAdapterRegressorV3.py | 4 ++-- quickadapter/user_data/strategies/QuickAdapterV3.py | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index 2bdf26c..c584bfb 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -44,7 +44,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): https://github.com/sponsors/robcaulk """ - version = "3.7.10" + version = "3.7.11" @cached_property def _optuna_config(self) -> dict: @@ -372,7 +372,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): def min_max_pred(self, pred_df: pd.DataFrame) -> tuple[float, float]: temperature = float( - self.freqai_info.get("prediction_thresholds_temperature", 150.0) + self.freqai_info.get("prediction_thresholds_temperature", 125.0) ) min_pred = smoothed_min( pred_df[EXTREMA_COLUMN], diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py index 350327f..b19bbce 100644 --- a/quickadapter/user_data/strategies/QuickAdapterV3.py +++ b/quickadapter/user_data/strategies/QuickAdapterV3.py @@ -58,7 +58,7 @@ class QuickAdapterV3(IStrategy): INTERFACE_VERSION = 3 def version(self) -> str: - return "3.3.7" + return "3.3.8" timeframe = "5m" @@ -377,7 +377,7 @@ class QuickAdapterV3(IStrategy): return self.get_label_natr_ratio(pair) * 0.025 def get_trailing_stoploss_natr_ratio(self, pair: str) -> float: - return self.get_label_natr_ratio(pair) * 0.5 + return self.get_label_natr_ratio(pair) * 0.75 def set_freqai_targets(self, dataframe: DataFrame, metadata: dict, **kwargs): pair = str(metadata.get("pair")) -- 2.43.0