66 lines
2.0 KiB
Python
66 lines
2.0 KiB
Python
import talib.abstract as ta
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import pandas as pd
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import numpy as np
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from freqtrade.strategy import IStrategy
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import logging
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logger = logging.getLogger(__name__)
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class SimpleRSIStrategyOptimized(IStrategy):
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INTERFACE_VERSION = 3
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can_short: bool = False
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stoploss = -0.05
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minimal_roi = {"0": 100} # 由止盈逻辑替代
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timeframe = '1d'
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# === 策略参数（可优化）===
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ema_short = 10
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ema_long = 20
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rsi_period = 6
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rsi_oversold = 20
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def populate_indicators(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
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# EMA
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dataframe['ema_short'] = ta.EMA(dataframe['close'], timeperiod=self.ema_short)
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dataframe['ema_long'] = ta.EMA(dataframe['close'], timeperiod=self.ema_long)
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# RSI
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dataframe['rsi'] = ta.RSI(dataframe['close'], timeperiod=self.rsi_period)
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# 辅助：昨日值（shift 1）
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dataframe['ema_short_prev'] = dataframe['ema_short'].shift(1)
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dataframe['rsi_prev'] = dataframe['rsi'].shift(1)
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return dataframe
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def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
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dataframe.loc[
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(
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# 趋势条件：EMA 短期 > 长期 且 短期 EMA 上升
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(dataframe['ema_short'] > dataframe['ema_long']) &
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(dataframe['ema_short'] > dataframe['ema_short_prev']) &
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# RSI 超卖后反弹
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(dataframe['rsi_prev'] <= self.rsi_oversold) &
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(dataframe['rsi'] > dataframe['rsi_prev'])
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),
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'enter_long',
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] = 1
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return dataframe
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def populate_exit_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
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dataframe.loc[
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(
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# 趋势破坏：EMA 死叉
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(dataframe['ema_short'] < dataframe['ema_long']) |
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# 或价格跌破长期 EMA（支撑失效）
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(dataframe['close'] < dataframe['ema_long'])
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),
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'exit_long',
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] = 1
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return dataframe |