first commit

Scalp.py

@@ -0,0 +1,75 @@
+# --- 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
+
+
+class Scalp(IStrategy):
+    """
+        this strategy is based around the idea of generating a lot of potentatils buys and make tiny profits on each trade
+
+        we recommend to have at least 60 parallel trades at any time to cover non avoidable losses.
+
+        Recommended is to only sell based on ROI for this strategy
+    """
+
+    # Minimal ROI designed for the strategy.
+    # This attribute will be overridden if the config file contains "minimal_roi"
+    minimal_roi = {
+        "0": 0.01
+    }
+    # Optimal stoploss designed for the strategy
+    # This attribute will be overridden if the config file contains "stoploss"
+    # should not be below 3% loss
+
+    stoploss = -0.04
+    # Optimal timeframe for the strategy
+    # the shorter the better
+    timeframe = '1m'
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe['ema_high'] = ta.EMA(dataframe, timeperiod=5, price='high')
+        dataframe['ema_close'] = ta.EMA(dataframe, timeperiod=5, price='close')
+        dataframe['ema_low'] = ta.EMA(dataframe, timeperiod=5, price='low')
+        stoch_fast = ta.STOCHF(dataframe, 5, 3, 0, 3, 0)
+        dataframe['fastd'] = stoch_fast['fastd']
+        dataframe['fastk'] = stoch_fast['fastk']
+        dataframe['adx'] = ta.ADX(dataframe)
+
+        # required for graphing
+        bollinger = qtpylib.bollinger_bands(dataframe['close'], window=20, stds=2)
+        dataframe['bb_lowerband'] = bollinger['lower']
+        dataframe['bb_upperband'] = bollinger['upper']
+        dataframe['bb_middleband'] = bollinger['mid']
+
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe.loc[
+            (
+                (dataframe['open'] < dataframe['ema_low']) &
+                (dataframe['adx'] > 30) &
+                (
+                    (dataframe['fastk'] < 30) &
+                    (dataframe['fastd'] < 30) &
+                    (qtpylib.crossed_above(dataframe['fastk'], dataframe['fastd']))
+                )
+            ),
+            'buy'] = 1
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe.loc[
+            (
+                (dataframe['open'] >= dataframe['ema_high'])
+            ) |
+            (
+                (qtpylib.crossed_above(dataframe['fastk'], 70)) |
+                (qtpylib.crossed_above(dataframe['fastd'], 70))
+            ),
+            'sell'] = 1
+        return dataframe