135 lines
4.4 KiB
Python
135 lines
4.4 KiB
Python
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
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# flake8: noqa: F401
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# isort: skip_file
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# --- Do not remove these imports ---
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import numpy as np
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import pandas as pd
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from datetime import datetime, timedelta, timezone
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from pandas import DataFrame
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from typing import Optional, Union
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from freqtrade.strategy import (
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IStrategy,
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Trade,
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Order,
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PairLocks,
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informative, # @informative decorator
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# Hyperopt Parameters
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BooleanParameter,
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CategoricalParameter,
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DecimalParameter,
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IntParameter,
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RealParameter,
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# timeframe helpers
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timeframe_to_minutes,
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timeframe_to_next_date,
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timeframe_to_prev_date,
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# Strategy helper functions
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merge_informative_pair,
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stoploss_from_absolute,
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stoploss_from_open,
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)
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import logging
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logger = logging.getLogger(__name__)
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# --------------------------------
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# Add your lib to import here
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import talib.abstract as ta
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from technical import qtpylib
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class CCIMultiTimeframeSpotStrategy(IStrategy):
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# 策略参数
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INTERFACE_VERSION = 3
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minimal_roi = {"0": 100}
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stoploss = -1
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trailing_stop = False
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timeframe = '4h'
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use_exit_signal = True
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exit_profit_only = False
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ignore_roi_if_entry_signal = False
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def TD(self, dataframe:DataFrame):
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close = dataframe['close'].to_list()
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td = [0,0,0,0]
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up = 0
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down = 0
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for i in range(4, len(close)):
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if close[i] > close[i-4]:
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up += 1
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down = 0
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td.append(up)
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else:
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down -= 1
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up = 0
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td.append(down)
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return td
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@informative('1d')
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def populate_indicators_1d(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe['cci'] = ta.CCI(dataframe, timeperiod=26)
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dataframe["adx"] = ta.ADX(dataframe)
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macd = ta.MACD(dataframe, fastperiod=12, slowperiod=26, signalperiod=9,)
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dataframe["macd"] = macd["macd"]
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dataframe["macdsignal"] = macd["macdsignal"]
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dataframe["macdhist"] = macd["macdhist"]
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logger.info(dataframe.tail())
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return dataframe
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@informative('1w')
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def populate_indicators_1w(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe['cci'] = ta.CCI(dataframe, timeperiod=26)
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logger.info(dataframe.tail())
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return dataframe
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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# 计算4h CCI
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dataframe['cci_4h'] = ta.CCI(dataframe, timeperiod=26)
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dataframe['sma12_4h'] = ta.SMA(dataframe, timeperiod=12)
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dataframe['sma26_4h'] = ta.SMA(dataframe, timeperiod=26)
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dataframe["adx_4h"] = ta.ADX(dataframe)
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macd = ta.MACD(dataframe, fastperiod=12, slowperiod=26, signalperiod=9,)
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dataframe["macd_4h"] = macd["macd"]
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dataframe["macdsignal_4h"] = macd["macdsignal"]
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dataframe["macdhist_4h"] = macd["macdhist"]
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dataframe['cci_hist_4h'] = ta.CCI(dataframe['macdhist_1d'], dataframe['macdhist_1d'], dataframe['macdhist_1d'], timeperiod=26)
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# dataframe['adx_hist_4h'] = ta.ADX(dataframe['macdhist_4h'])
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dataframe['TD'] = self.TD(dataframe)
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logger.info(dataframe.tail())
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return dataframe
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def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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# 入场：1d与4h CCI < -100，且4h CCI上升（当前 > 前一根）
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dataframe.loc[
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(
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(dataframe['cci_4h'] < -100) &
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(dataframe['cci_1d'] < -100) &
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(dataframe['cci_4h'] > dataframe['cci_4h'].shift(1)) &
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# (dataframe['macdhist_1d'] < dataframe['macdhist_1d'].shift(1)) &
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(dataframe['volume'] > 0)
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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: DataFrame, metadata: dict) -> DataFrame:
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# 离场：1d与4h CCI > 100，且4h CCI下降（当前 < 前一根）
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dataframe.loc[
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(
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(dataframe['cci_4h'] > 100) &
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(dataframe['cci_1d'] > 100) &
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(dataframe['cci_4h'] < dataframe['cci_4h'].shift(1)) &
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# (dataframe['macdhist_1d'] > dataframe['macdhist_1d'].shift(1)) &
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(dataframe['volume'] > 0)
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),
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'exit_long',
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] = 1
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return dataframe
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