diff --git a/user_data/hyperopts/MACDStrategy_hyperopt.py b/user_data/hyperopts/MACDStrategy_hyperopt.py
deleted file mode 100644
index 036836f..0000000
--- a/user_data/hyperopts/MACDStrategy_hyperopt.py
+++ /dev/null
@@ -1,100 +0,0 @@
-# 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
-
-# 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
-
-class_name = 'MACDStrategy_hyperopt'
-
-
-# This class is a sample. Feel free to customize it.
-class MACDStrategy_hyperopt(IHyperOpt):
-    """
-    This is an Example hyperopt to inspire you. - corresponding to MACDStrategy in this repository.
-
-    To run this, best use the following command (adjust to your environment if needed):
-    ```
-    freqtrade hyperopt --strategy MACDStrategy --hyperopt MACDStrategy_hyperopt --spaces buy sell
-    ```
-    The idea is to optimize only the CCI value.
-    - Buy side: CCI between -700 and 0
-    - Sell side: CCI between 0 and 700
-
-    More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md
-     """
-
-    @staticmethod
-    def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
-
-        macd = ta.MACD(dataframe)
-        dataframe['macd'] = macd['macd']
-        dataframe['macdsignal'] = macd['macdsignal']
-        dataframe['macdhist'] = macd['macdhist']
-        dataframe['cci'] = ta.CCI(dataframe)
-
-        return dataframe
-
-    @staticmethod
-    def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
-        """
-        Define the buy strategy parameters to be used by hyperopt
-        """
-        def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
-            """
-            Buy strategy Hyperopt will build and use
-            """
-            dataframe.loc[
-                (
-                    (dataframe['macd'] > dataframe['macdsignal']) &
-                    (dataframe['cci'] <= params['buy-cci-value']) &
-                    (dataframe['volume'] > 0)  # Make sure Volume is not 0
-                ),
-                'buy'] = 1
-
-            return dataframe
-
-        return populate_buy_trend
-
-    @staticmethod
-    def indicator_space() -> List[Dimension]:
-        """
-        Define your Hyperopt space for searching strategy parameters
-        """
-        return [
-            Integer(-700, 0, name='buy-cci-value'),
-        ]
-
-    @staticmethod
-    def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
-        """
-        Define the sell strategy parameters to be used by hyperopt
-        """
-        def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
-            """
-            Sell strategy Hyperopt will build and use
-            """
-            dataframe.loc[
-                (
-                    (dataframe['macd'] < dataframe['macdsignal']) &
-                    (dataframe['cci'] >= params['sell-cci-value'])
-                ),
-                'sell'] = 1
-
-            return dataframe
-
-        return populate_sell_trend
-
-    @staticmethod
-    def sell_indicator_space() -> List[Dimension]:
-        """
-        Define your Hyperopt space for searching sell strategy parameters
-        """
-        return [
-            Integer(0, 700, name='sell-cci-value'),
-        ]
diff --git a/user_data/strategies/berlinguyinca/MACDStrategy.py b/user_data/strategies/berlinguyinca/MACDStrategy.py
index c2ec4ee..a30ffa4 100644
--- a/user_data/strategies/berlinguyinca/MACDStrategy.py
+++ b/user_data/strategies/berlinguyinca/MACDStrategy.py
@@ -1,8 +1,7 @@
 
 # --- Do not remove these libs ---
-from freqtrade.strategy.interface import IStrategy
-from typing import Dict, List
-from functools import reduce
+from freqtrade.strategy import IStrategy
+from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter
 from pandas import DataFrame
 # --------------------------------
 
@@ -11,7 +10,6 @@ import talib.abstract as ta
 
 class MACDStrategy(IStrategy):
     """
-
     author@: Gert Wohlgemuth
 
     idea:
@@ -24,7 +22,14 @@ class MACDStrategy(IStrategy):
             MACD below MACD signal
             and CCI > 100
 
+    freqtrade hyperopt --strategy MACDStrategy --hyperopt-loss <someLossFunction> --spaces buy sell
+
+    The idea is to optimize only the CCI value.
+    - Buy side: CCI between -700 and 0
+    - Sell side: CCI between 0 and 700
+
     """
+    INTERFACE_VERSION = 2
 
     # Minimal ROI designed for the strategy.
     # This attribute will be overridden if the config file contains "minimal_roi"
@@ -42,6 +47,19 @@ class MACDStrategy(IStrategy):
     # Optimal timeframe for the strategy
     timeframe = '5m'
 
+    buy_cci = IntParameter(low=-700, high=0, default=-50, space='buy', optimize=True)
+    sell_cci = IntParameter(low=0, high=700, default=100, space='sell', optimize=True)
+
+    # Buy hyperspace params:
+    buy_params = {
+        "buy_cci": -48,
+    }
+
+    # Sell hyperspace params:
+    sell_params = {
+        "sell_cci": 687,
+    }
+
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
         macd = ta.MACD(dataframe)
@@ -61,7 +79,8 @@ class MACDStrategy(IStrategy):
         dataframe.loc[
             (
                 (dataframe['macd'] > dataframe['macdsignal']) &
-                (dataframe['cci'] <= -50.0)
+                (dataframe['cci'] <= self.buy_cci.value) &
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
             ),
             'buy'] = 1
 
@@ -76,7 +95,8 @@ class MACDStrategy(IStrategy):
         dataframe.loc[
             (
                 (dataframe['macd'] < dataframe['macdsignal']) &
-                (dataframe['cci'] >= 100.0)
+                (dataframe['cci'] >= self.sell_cci.value) &
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
             ),
             'sell'] = 1