106 lines
3.4 KiB
Python
106 lines
3.4 KiB
Python
#!/usr/bin/env python3
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"""
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Hyperopt 配置示例，用于优化新的趋势判定参数
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使用方法:
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1. 将此文件保存为 hyperopt_trend_params.py
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2. 运行: freqtrade hyperopt --config config.json --strategy freqaiprimer --hyperopt hyperopt_trend_params
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"""
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from freqtrade.optimize.hyperopt_interface import IHyperOpt
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from typing import Dict, Any
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import logging
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logger = logging.getLogger(__name__)
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class TrendParamsHyperopt(IHyperOpt):
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"""
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优化趋势判定参数的 Hyperopt 类
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"""
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@staticmethod
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def generate_roi_table(params: Dict) -> Dict[int, float]:
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"""生成ROI表格"""
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return {
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0: params['roi_p1'] + params['roi_p2'] + params['roi_p3'],
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params['roi_t3']: params['roi_p1'] + params['roi_p2'],
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params['roi_t3'] + params['roi_t2']: params['roi_p1'],
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params['roi_t3'] + params['roi_t2'] + params['roi_t1']: 0,
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}
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@staticmethod
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def roi_space():
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"""ROI参数空间"""
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return {
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'roi_p1': [0.01, 0.08],
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'roi_p2': [0.01, 0.08],
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'roi_p3': [0.01, 0.08],
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'roi_t1': [10, 120],
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'roi_t2': [10, 60],
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'roi_t3': [10, 60],
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}
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@staticmethod
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def stoploss_space():
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"""止损参数空间"""
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return {
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'stoploss': [-0.5, -0.05],
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}
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@staticmethod
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def trailing_space():
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"""追踪止损参数空间"""
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return {
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'trailing_stop': [True, False],
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'trailing_stop_positive': [0.005, 0.05],
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'trailing_stop_positive_offset_p1': [0.005, 0.05],
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'trailing_only_offset_is_reached': [True, False],
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}
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def buy_params_space(self):
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"""买入参数空间，包含新的趋势判定阈值"""
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return {
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# 原有参数
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'buy_threshold': [-0.05, -0.001],
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'volume_z_score_min': [0.1, 2.0],
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'rsi_max': [20, 60],
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# 新的趋势判定阈值
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'trend_final_bullish_threshold': [50, 90], # 上涨趋势阈值
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'trend_final_bearish_threshold': [10, 50], # 下跌趋势阈值
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}
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def sell_params_space(self):
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"""卖出参数空间"""
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return {
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'sell_threshold': [0.001, 0.08],
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'rsi_min': [60, 90],
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'stochrsi_max': [60, 95],
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}
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def generate_estimator(self, dimensions: list, **kwargs) -> Any:
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"""生成优化器"""
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from skopt import Optimizer
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from skopt.space import Real, Integer
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# 定义参数空间
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space = [
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Real(-0.5, -0.05, name='stoploss'),
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Real(0.001, 0.08, name='sell_threshold'),
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Real(-0.05, -0.001, name='buy_threshold'),
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Real(0.1, 2.0, name='volume_z_score_min'),
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Integer(20, 60, name='rsi_max'),
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Integer(60, 90, name='rsi_min'),
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Integer(60, 95, name='stochrsi_max'),
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Integer(50, 90, name='trend_final_bullish_threshold'),
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Integer(10, 50, name='trend_final_bearish_threshold'),
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]
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return Optimizer(space, base_estimator='ET', acq_func='EI', n_initial_points=10)
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# 使用示例配置
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if __name__ == "__main__":
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print("趋势参数优化配置已加载")
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print("支持的优化参数:")
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print("- trend_final_bullish_threshold: 50-90")
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print("- trend_final_bearish_threshold: 10-50") |