init

user_data/strategies/cci_multi_tf_strategy.py

@@ -0,0 +1,134 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+# flake8: noqa: F401
+# isort: skip_file
+# --- Do not remove these imports ---
+import numpy as np
+import pandas as pd
+from datetime import datetime, timedelta, timezone
+from pandas import DataFrame
+from typing import Optional, Union
+from freqtrade.strategy import (
+    IStrategy,
+    Trade,
+    Order,
+    PairLocks,
+    informative,  # @informative decorator
+    # Hyperopt Parameters
+    BooleanParameter,
+    CategoricalParameter,
+    DecimalParameter,
+    IntParameter,
+    RealParameter,
+    # timeframe helpers
+    timeframe_to_minutes,
+    timeframe_to_next_date,
+    timeframe_to_prev_date,
+    # Strategy helper functions
+    merge_informative_pair,
+    stoploss_from_absolute,
+    stoploss_from_open,
+)
+import logging  
+  
+logger = logging.getLogger(__name__) 
+# --------------------------------
+# Add your lib to import here
+import talib.abstract as ta
+from technical import qtpylib
+
+
+class CCIMultiTimeframeSpotStrategy(IStrategy):
+    # 策略参数
+    INTERFACE_VERSION = 3
+
+    minimal_roi = {"0": 100}
+    stoploss = -1
+    trailing_stop = False
+    timeframe = '4h'
+
+    use_exit_signal = True
+    exit_profit_only = False
+    ignore_roi_if_entry_signal = False
+
+    def TD(self, dataframe:DataFrame):
+        close = dataframe['close'].to_list()
+        td = [0,0,0,0]
+        up = 0
+        down = 0
+        for i in range(4, len(close)):
+            if close[i] > close[i-4]:
+                up += 1
+                down = 0
+                td.append(up)
+            else:
+                down -= 1
+                up = 0
+                td.append(down)
+        return td
+
+    @informative('1d')  
+    def populate_indicators_1d(self, dataframe: DataFrame, metadata: dict) -> DataFrame:  
+        dataframe['cci'] = ta.CCI(dataframe, timeperiod=26)  
+        dataframe["adx"] = ta.ADX(dataframe)
+        macd = ta.MACD(dataframe, fastperiod=12, slowperiod=26, signalperiod=9,)
+        dataframe["macd"] = macd["macd"]
+        dataframe["macdsignal"] = macd["macdsignal"]
+        dataframe["macdhist"] = macd["macdhist"]
+        logger.info(dataframe.tail())
+        return dataframe
+    
+    @informative('1w')  
+    def populate_indicators_1w(self, dataframe: DataFrame, metadata: dict) -> DataFrame:  
+        dataframe['cci'] = ta.CCI(dataframe, timeperiod=26)  
+        logger.info(dataframe.tail())
+        return dataframe
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # 计算4h CCI
+        dataframe['cci_4h'] = ta.CCI(dataframe, timeperiod=26)
+        dataframe['sma12_4h'] = ta.SMA(dataframe, timeperiod=12)
+        dataframe['sma26_4h'] = ta.SMA(dataframe, timeperiod=26)
+        dataframe["adx_4h"] = ta.ADX(dataframe)
+        
+        macd = ta.MACD(dataframe, fastperiod=12, slowperiod=26, signalperiod=9,)
+        dataframe["macd_4h"] = macd["macd"]
+        dataframe["macdsignal_4h"] = macd["macdsignal"]
+        dataframe["macdhist_4h"] = macd["macdhist"]
+
+        dataframe['cci_hist_4h'] = ta.CCI(dataframe['macdhist_1d'], dataframe['macdhist_1d'], dataframe['macdhist_1d'], timeperiod=26)
+
+        # dataframe['adx_hist_4h'] = ta.ADX(dataframe['macdhist_4h'])
+        dataframe['TD'] = self.TD(dataframe)
+        
+        logger.info(dataframe.tail())
+        return dataframe
+
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # 入场：1d与4h CCI < -100，且4h CCI上升（当前 > 前一根）
+        dataframe.loc[
+            (
+                (dataframe['cci_4h'] < -100) &
+                (dataframe['cci_1d'] < -100) &
+                (dataframe['cci_4h'] > dataframe['cci_4h'].shift(1)) &
+                # (dataframe['macdhist_1d'] < dataframe['macdhist_1d'].shift(1)) &
+                (dataframe['volume'] > 0)
+            ),
+            'enter_long',
+        ] = 1
+
+        return dataframe
+
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # 离场：1d与4h CCI > 100，且4h CCI下降（当前 < 前一根）
+        dataframe.loc[
+            (
+                (dataframe['cci_4h'] > 100) &
+                (dataframe['cci_1d'] > 100) &
+                (dataframe['cci_4h'] < dataframe['cci_4h'].shift(1)) &
+                # (dataframe['macdhist_1d'] > dataframe['macdhist_1d'].shift(1)) &
+                (dataframe['volume'] > 0)
+            ),
+            'exit_long',
+        ] = 1
+
+        return dataframe
+