first commit

BinHV45.py

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+# --- Do not remove these libs ---
+from freqtrade.strategy import IStrategy
+from freqtrade.strategy import IntParameter
+from pandas import DataFrame
+import numpy as np
+# --------------------------------
+
+import talib.abstract as ta
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+
+
+def bollinger_bands(stock_price, window_size, num_of_std):
+    rolling_mean = stock_price.rolling(window=window_size).mean()
+    rolling_std = stock_price.rolling(window=window_size).std()
+    lower_band = rolling_mean - (rolling_std * num_of_std)
+
+    return rolling_mean, lower_band
+
+
+class BinHV45(IStrategy):
+    INTERFACE_VERSION = 2
+
+    minimal_roi = {
+        "0": 0.0125
+    }
+
+    stoploss = -0.05
+    timeframe = '1m'
+
+    buy_bbdelta = IntParameter(low=1, high=15, default=30, space='buy', optimize=True)
+    buy_closedelta = IntParameter(low=15, high=20, default=30, space='buy', optimize=True)
+    buy_tail = IntParameter(low=20, high=30, default=30, space='buy', optimize=True)
+
+    # Hyperopt parameters
+    buy_params = {
+        "buy_bbdelta": 7,
+        "buy_closedelta": 17,
+        "buy_tail": 25,
+    }
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        bollinger = qtpylib.bollinger_bands(dataframe['close'], window=40, stds=2)
+
+        dataframe['upper'] = bollinger['upper']
+        dataframe['mid'] = bollinger['mid']
+        dataframe['lower'] = bollinger['lower']
+        dataframe['bbdelta'] = (dataframe['mid'] - dataframe['lower']).abs()
+        dataframe['pricedelta'] = (dataframe['open'] - dataframe['close']).abs()
+        dataframe['closedelta'] = (dataframe['close'] - dataframe['close'].shift()).abs()
+        dataframe['tail'] = (dataframe['close'] - dataframe['low']).abs()
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe.loc[
+            (
+                dataframe['lower'].shift().gt(0) &
+                dataframe['bbdelta'].gt(dataframe['close'] * self.buy_bbdelta.value / 1000) &
+                dataframe['closedelta'].gt(dataframe['close'] * self.buy_closedelta.value / 1000) &
+                dataframe['tail'].lt(dataframe['bbdelta'] * self.buy_tail.value / 1000) &
+                dataframe['close'].lt(dataframe['lower'].shift()) &
+                dataframe['close'].le(dataframe['close'].shift())
+            ),
+            'buy'] = 1
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        no sell signal
+        """
+        dataframe.loc[:, 'sell'] = 0
+        return dataframe