diff --git a/user_data/strategies/Heracles.py b/user_data/strategies/Heracles.py
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+# Heracles Strategy: Strongest Son of GodStra
+# ( With just 1 Genome! its a bacteria :D )
+# Author: @Mablue (Masoud Azizi)
+# github: https://github.com/mablue/
+# IMPORTANT:Add to your pairlists inside config.json (Under StaticPairList):
+#   {
+#       "method": "AgeFilter",
+#       "min_days_listed": 100
+#   },
+# IMPORTANT: INSTALL TA BEFOUR RUN(pip install ta)
+# ######################################################################
+# Optimal config settings:
+# "max_open_trades": 100,
+# "stake_amount": "unlimited",
+
+# --- Do not remove these libs ---
+import logging
+
+from numpy.lib import math
+from freqtrade.strategy.interface import IStrategy
+from pandas import DataFrame
+# --------------------------------
+
+# Add your lib to import here
+# import talib.abstract as ta
+import pandas as pd
+import ta
+from ta.utils import dropna
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+from functools import reduce
+import numpy as np
+
+
+class Heracles(IStrategy):
+    # 65/600:   2275 trades. 1438/7/830 W/D/L.
+    # Avg profit   3.10%. Median profit   3.06%.
+    # Total profit  113171 USDT ( 7062 Σ%).
+    # Avg duration 345 min. Objective: -23.0
+
+    # Buy hyperspace params:
+    buy_params = {
+        'buy-cross-0': 'volatility_kcw',
+        'buy-indicator-0': 'volatility_dcp',
+        'buy-oper-0': '<',
+    }
+
+    # Sell hyperspace params:
+    sell_params = {
+        'sell-cross-0': 'trend_macd_signal',
+        'sell-indicator-0': 'trend_ema_fast',
+        'sell-oper-0': '=',
+    }
+
+    # ROI table:
+    minimal_roi = {
+        "0": 0.32836,
+        "1629": 0.17896,
+        "6302": 0.05372,
+        "10744": 0
+    }
+
+    # Stoploss:
+    stoploss = -0.04655
+
+    # Trailing stop:
+    trailing_stop = True
+    trailing_stop_positive = 0.02444
+    trailing_stop_positive_offset = 0.04406
+    trailing_only_offset_is_reached = True
+
+    # Buy hypers
+    timeframe = '12h'
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # Add all ta features
+        dataframe = dropna(dataframe)
+
+        dataframe['volatility_kcw'] = ta.volatility.keltner_channel_wband(
+            dataframe['high'],
+            dataframe['low'],
+            dataframe['close'],
+            window=20,
+            window_atr=10,
+            fillna=False,
+            original_version=True
+        )
+        dataframe['volatility_dcp'] = ta.volatility.donchian_channel_pband(
+            dataframe['high'],
+            dataframe['low'],
+            dataframe['close'],
+            window=10,
+            offset=0,
+            fillna=False
+        )
+        dataframe['trend_macd_signal'] = ta.trend.macd_signal(
+            dataframe['close'],
+            window_slow=26,
+            window_fast=12,
+            window_sign=9,
+            fillna=False
+        )
+
+        dataframe['trend_ema_fast'] = ta.trend.EMAIndicator(
+            close=dataframe['close'], window=12, fillna=False
+        ).ema_indicator()
+
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+
+        IND = self.buy_params['buy-indicator-0']
+        CRS = self.buy_params['buy-cross-0']
+        DFIND = dataframe[IND]
+        DFCRS = dataframe[CRS]
+
+        dataframe.loc[
+            (DFIND < DFCRS),
+            'buy'] = 1
+
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        IND = self.sell_params['sell-indicator-0']
+        CRS = self.sell_params['sell-cross-0']
+
+        DFIND = dataframe[IND]
+        DFCRS = dataframe[CRS]
+
+        dataframe.loc[
+            (qtpylib.crossed_below(DFIND, DFCRS)),
+            'sell'] = 1
+
+        return dataframe