Merge pull request #127 from OtenMoten/master

Hyperopt and Strategy "Swing-High-To-Sky"

user_data/hyperopts/HO-SwingHighToSky.py

@@ -0,0 +1,124 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+
+import talib.abstract as ta
+from pandas import DataFrame
+from typing import Dict, Any, Callable, List
+from functools import reduce
+
+import numpy as np
+from skopt.space import Categorical, Dimension, Integer, Real
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+from freqtrade.optimize.hyperopt_interface import IHyperOpt
+
+__author__      = "Kevin Ossenbrück"
+__copyright__   = "Free For Use"
+__credits__     = ["Bloom Trading, Mohsen Hassan"]
+__license__     = "MIT"
+__version__     = "1.0"
+__maintainer__  = "Kevin Ossenbrück"
+__email__       = "kevin.ossenbrueck@pm.de"
+__status__      = "Live"
+
+cciTimeMin = 10
+cciTimeMax = 100
+cciValueMin = -400
+cciValueMax = 400
+cciTimeRange = range(cciTimeMin, cciTimeMax)
+
+class_name = 'HOSwingHighToSky'
+class HOSwingHighToSky(IHyperOpt):
+
+    @staticmethod
+    def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
+
+        macd = ta.MACD(dataframe)
+        dataframe['macd'] = macd['macd']
+        dataframe['macdsignal'] = macd['macdsignal']
+        
+        for cciTime in cciTimeRange:
+        
+            cciName = "cci-" + str(cciTime) 
+            dataframe[cciName] = ta.CCI(dataframe, timeperiod = cciTime)
+            
+        return dataframe
+
+    @staticmethod
+    def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
+   
+        def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
+        
+            conditions = []
+                
+            # TRIGGERS & GUARDS
+            if 'trigger' in params:
+            
+                for cciTime in cciTimeRange:
+                
+                    cciName = "cci-" + str(cciTime)
+            
+                    if params['trigger'] == cciName:
+                        conditions.append(dataframe[cciName] < params["buy-cci-value"])
+                        conditions.append(dataframe['macd'] > dataframe['macdsignal'])
+                        conditions.append(dataframe['volume'] > 0)
+                
+            if conditions:
+                dataframe.loc[reduce(lambda x, y: x & y, conditions), 'buy'] = 1
+
+            return dataframe
+
+        return populate_buy_trend
+
+    @staticmethod
+    def indicator_space() -> List[Dimension]:
+        
+        buyTriggerList = []
+        
+        for cciTime in cciTimeRange:
+        
+            cciName = "cci-" + str(cciTime)
+            buyTriggerList.append(cciName)
+        
+        return [
+            Integer(cciValueMin, cciValueMax, name='buy-cci-value'),
+            Categorical(buyTriggerList, name='trigger')
+        ]
+
+    @staticmethod
+    def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
+
+        def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
+           
+            conditions = []
+                 
+            # TRIGGERS & GUARDS
+            if 'sell-trigger' in params:
+            
+                for cciTime in cciTimeRange:
+                
+                    cciName = "cci-" + str(cciTime)
+            
+                    if params['sell-trigger'] == cciName:
+                        conditions.append(dataframe[cciName] > params["sell-cci-value"])
+                        conditions.append(dataframe['macd'] < dataframe['macdsignal'])
+                
+            if conditions:
+                dataframe.loc[reduce(lambda x, y: x & y, conditions), 'sell'] = 1
+
+            return dataframe
+
+        return populate_sell_trend
+
+    @staticmethod
+    def sell_indicator_space() -> List[Dimension]:
+       
+        sellTriggerList = []
+        
+        for cciTime in cciTimeRange:
+        
+            cciName = "cci-" + str(cciTime)
+            sellTriggerList.append(cciName)
+            
+        return [
+            Integer(cciValueMin, cciValueMax, name='sell-cci-value'),
+            Categorical(sellTriggerList, name='sell-trigger')
+        ]

user_data/strategies/Swing-High-To-Sky.py

@@ -0,0 +1,78 @@
+# --- Do not remove these libs ---
+from freqtrade.strategy.interface import IStrategy
+from typing import Dict, List
+from functools import reduce
+from pandas import DataFrame
+# --------------------------------
+
+import talib.abstract as ta
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+import numpy # noqa
+
+__author__      = "Kevin Ossenbrück"
+__copyright__   = "Free For Use"
+__credits__     = ["Bloom Trading, Mohsen Hassan"]
+__license__     = "MIT"
+__version__     = "1.0"
+__maintainer__  = "Kevin Ossenbrück"
+__email__       = "kevin.ossenbrueck@pm.de"
+__status__      = "Live"
+
+class_name = 'SwingHighToSky'
+class SwingHighToSky(IStrategy):
+
+    # Disable ROI
+    # Could be replaced with new ROI from hyperopt.
+    minimal_roi = {
+         "0":  100
+    }
+
+    stoploss = -0.30
+  
+    ### Do extra hyperopt for trailing seperat. Use "--spaces default" and then "--spaces trailing".
+    ### See here for more information: https://www.freqtrade.io/en/latest/hyperopt
+    trailing_stop = True
+    trailing_stop_positive = 0.08
+    trailing_stop_positive_offset = 0.10
+    trailing_only_offset_is_reached = True
+
+    ticker_interval = '30m'
+
+    def informative_pairs(self):
+        return []
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        
+        macd = ta.MACD(dataframe)
+        dataframe['macd'] = macd['macd']
+        dataframe['macdsignal'] = macd['macdsignal']
+        
+        ### Add timeperiod from hyperopt (replace xx with value):
+        ### "xx" must be replaced even before the first hyperopt is run,
+        ### else "xx" would be a syntax error because it must be a Integer value.
+        dataframe['cci-buy'] = ta.CCI(dataframe, timeperiod=xx)
+        dataframe['cci-sell'] = ta.CCI(dataframe, timeperiod=xx)
+
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        
+        dataframe.loc[
+            (
+                (dataframe['macd'] > dataframe['macdsignal']) &
+                (dataframe['cci-buy'] <= -100.0) # Replace with value from hyperopt.
+            ),
+            'buy'] = 1
+
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        
+        dataframe.loc[
+            ( 
+                (dataframe['macd'] < dataframe['macdsignal']) & 
+                (dataframe['cci-sell'] >= 200.0) # Replace with value from hyperopt.
+            ),
+            'sell'] = 1
+            
+        return dataframe