diff --git a/user_data/strategies/berlinguyinca/ADXMomentum.py b/user_data/strategies/berlinguyinca/ADXMomentum.py
index 5a382fe..f47bef9 100644
--- a/user_data/strategies/berlinguyinca/ADXMomentum.py
+++ b/user_data/strategies/berlinguyinca/ADXMomentum.py
@@ -31,7 +31,7 @@ class ADXMomentum(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '1h'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
         dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=25)
         dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=25)
@@ -40,7 +40,7 @@ class ADXMomentum(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (dataframe['adx'] > 25) &
@@ -52,7 +52,7 @@ class ADXMomentum(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (dataframe['adx'] > 25) &
diff --git a/user_data/strategies/berlinguyinca/ASDTSRockwellTrading.py b/user_data/strategies/berlinguyinca/ASDTSRockwellTrading.py
index d13c35c..b970443 100644
--- a/user_data/strategies/berlinguyinca/ASDTSRockwellTrading.py
+++ b/user_data/strategies/berlinguyinca/ASDTSRockwellTrading.py
@@ -47,7 +47,7 @@ class ASDTSRockwellTrading(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
         macd = ta.MACD(dataframe)
         dataframe['macd'] = macd['macd']
@@ -56,7 +56,7 @@ class ASDTSRockwellTrading(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -71,7 +71,7 @@ class ASDTSRockwellTrading(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/AdxSmas.py b/user_data/strategies/berlinguyinca/AdxSmas.py
index eb1d936..4faf842 100644
--- a/user_data/strategies/berlinguyinca/AdxSmas.py
+++ b/user_data/strategies/berlinguyinca/AdxSmas.py
@@ -32,14 +32,14 @@ class AdxSmas(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '1h'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
         dataframe['short'] = ta.SMA(dataframe, timeperiod=3)
         dataframe['long'] = ta.SMA(dataframe, timeperiod=6)
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (dataframe['adx'] > 25) &
@@ -49,7 +49,7 @@ class AdxSmas(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (dataframe['adx'] < 25) &
diff --git a/user_data/strategies/berlinguyinca/AverageStrategy.py b/user_data/strategies/berlinguyinca/AverageStrategy.py
index 8f249d1..3a32e90 100644
--- a/user_data/strategies/berlinguyinca/AverageStrategy.py
+++ b/user_data/strategies/berlinguyinca/AverageStrategy.py
@@ -31,7 +31,7 @@ class AverageStrategy(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '4h'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         macd = ta.MACD(dataframe)
 
         dataframe['maShort'] = ta.EMA(dataframe, timeperiod=8)
@@ -39,7 +39,7 @@ class AverageStrategy(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -53,7 +53,7 @@ class AverageStrategy(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/AwesomeMacd.py b/user_data/strategies/berlinguyinca/AwesomeMacd.py
index e701244..5942665 100644
--- a/user_data/strategies/berlinguyinca/AwesomeMacd.py
+++ b/user_data/strategies/berlinguyinca/AwesomeMacd.py
@@ -32,7 +32,7 @@ class AwesomeMacd(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '1h'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
         dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
 
@@ -43,7 +43,7 @@ class AwesomeMacd(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (dataframe['macd'] > 0) &
@@ -54,7 +54,7 @@ class AwesomeMacd(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (dataframe['macd'] < 0) &
diff --git a/user_data/strategies/berlinguyinca/BbandRsi.py b/user_data/strategies/berlinguyinca/BbandRsi.py
index 4d84329..797b6e3 100644
--- a/user_data/strategies/berlinguyinca/BbandRsi.py
+++ b/user_data/strategies/berlinguyinca/BbandRsi.py
@@ -32,7 +32,7 @@ class BbandRsi(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '1h'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
 
         # Bollinger bands
@@ -43,7 +43,7 @@ class BbandRsi(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (dataframe['rsi'] < 30) &
@@ -53,7 +53,7 @@ class BbandRsi(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (dataframe['rsi'] > 70)
diff --git a/user_data/strategies/berlinguyinca/BinHV27.py b/user_data/strategies/berlinguyinca/BinHV27.py
index acf110d..49b51cb 100644
--- a/user_data/strategies/berlinguyinca/BinHV27.py
+++ b/user_data/strategies/berlinguyinca/BinHV27.py
@@ -28,7 +28,7 @@ class BinHV27(IStrategy):
     }
     stoploss = -0.50
     ticker_interval = '5m'
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['rsi'] = numpy.nan_to_num(ta.RSI(dataframe, timeperiod=5))
         rsiframe = DataFrame(dataframe['rsi']).rename(columns={'rsi': 'close'})
         dataframe['emarsi'] = numpy.nan_to_num(ta.EMA(rsiframe, timeperiod=5))
@@ -52,7 +52,7 @@ class BinHV27(IStrategy):
         dataframe['delta'] = dataframe['fastsma'] - dataframe['fastsma'].shift()
         dataframe['slowingdown'] = dataframe['delta'].lt(dataframe['delta'].shift())
         return dataframe
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             dataframe['slowsma'].gt(0) &
             dataframe['close'].lt(dataframe['highsma']) &
@@ -89,7 +89,7 @@ class BinHV27(IStrategy):
             ),
             'buy'] = 1
         return dataframe
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         buyframe = dataframe[dataframe['buy'] == 1].tail(1)
         if len(buyframe) == 0:
           dataframe.loc[[False], 'sell'] = 0
diff --git a/user_data/strategies/berlinguyinca/BinHV45.py b/user_data/strategies/berlinguyinca/BinHV45.py
index 24d7350..a39d9ed 100644
--- a/user_data/strategies/berlinguyinca/BinHV45.py
+++ b/user_data/strategies/berlinguyinca/BinHV45.py
@@ -25,7 +25,7 @@ class BinHV45(IStrategy):
     stoploss = -0.05
     ticker_interval = '1m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         mid, lower = bollinger_bands(dataframe['close'], window_size=40, num_of_std=2)
         dataframe['mid'] = np.nan_to_num(mid)
         dataframe['lower'] = np.nan_to_num(lower)
@@ -35,7 +35,7 @@ class BinHV45(IStrategy):
         dataframe['tail'] = (dataframe['close'] - dataframe['low']).abs()
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 dataframe['lower'].shift().gt(0) &
@@ -48,7 +48,7 @@ class BinHV45(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         no sell signal
         """
diff --git a/user_data/strategies/berlinguyinca/CCIStrategy.py b/user_data/strategies/berlinguyinca/CCIStrategy.py
index 0ea39da..d0b91ae 100644
--- a/user_data/strategies/berlinguyinca/CCIStrategy.py
+++ b/user_data/strategies/berlinguyinca/CCIStrategy.py
@@ -23,7 +23,7 @@ class CCIStrategy(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '1m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe = self.resample(dataframe, self.ticker_interval, 5)
 
         dataframe['cci_one'] = ta.CCI(dataframe, timeperiod=170)
@@ -41,7 +41,7 @@ class CCIStrategy(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -63,7 +63,7 @@ class CCIStrategy(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/CMCWinner.py b/user_data/strategies/berlinguyinca/CMCWinner.py
index c1480d2..7f00a47 100644
--- a/user_data/strategies/berlinguyinca/CMCWinner.py
+++ b/user_data/strategies/berlinguyinca/CMCWinner.py
@@ -43,7 +43,7 @@ class CMCWinner(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '15m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Adds several different TA indicators to the given DataFrame
 
@@ -63,7 +63,7 @@ class CMCWinner(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -79,7 +79,7 @@ class CMCWinner(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/ClucMay72018.py b/user_data/strategies/berlinguyinca/ClucMay72018.py
index 414ddf1..c5aebc6 100644
--- a/user_data/strategies/berlinguyinca/ClucMay72018.py
+++ b/user_data/strategies/berlinguyinca/ClucMay72018.py
@@ -39,7 +39,7 @@ class ClucMay72018(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['rsi'] = ta.RSI(dataframe, timeperiod=5)
         rsiframe = DataFrame(dataframe['rsi']).rename(columns={'rsi': 'close'})
         dataframe['emarsi'] = ta.EMA(rsiframe, timeperiod=5)
@@ -53,7 +53,7 @@ class ClucMay72018(IStrategy):
         dataframe['ema100'] = ta.EMA(dataframe, timeperiod=50)
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -69,7 +69,7 @@ class ClucMay72018(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/CofiBitStrategy.py b/user_data/strategies/berlinguyinca/CofiBitStrategy.py
index 8303170..fb76064 100644
--- a/user_data/strategies/berlinguyinca/CofiBitStrategy.py
+++ b/user_data/strategies/berlinguyinca/CofiBitStrategy.py
@@ -29,7 +29,7 @@ class CofiBitStrategy(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         stoch_fast = ta.STOCHF(dataframe, 5.0, 3.0, 0.0, 3.0, 0.0)
         dataframe['fastd'] = stoch_fast['fastd']
         dataframe['fastk'] = stoch_fast['fastk']
@@ -40,7 +40,7 @@ class CofiBitStrategy(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -59,7 +59,7 @@ class CofiBitStrategy(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/CombinedBinHAndCluc.py b/user_data/strategies/berlinguyinca/CombinedBinHAndCluc.py
index a17af8f..b0868b5 100644
--- a/user_data/strategies/berlinguyinca/CombinedBinHAndCluc.py
+++ b/user_data/strategies/berlinguyinca/CombinedBinHAndCluc.py
@@ -26,7 +26,7 @@ class CombinedBinHAndCluc(IStrategy):
     stoploss = -0.15
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         mid, lower = bollinger_bands(dataframe['close'], window_size=40, num_of_std=2)
         dataframe['mid'] = np.nan_to_num(mid)
         dataframe['lower'] = np.nan_to_num(lower)
@@ -47,7 +47,7 @@ class CombinedBinHAndCluc(IStrategy):
         dataframe['ema100'] = ta.EMA(dataframe, timeperiod=50)
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     dataframe['lower'].shift().gt(0) &
@@ -67,7 +67,7 @@ class CombinedBinHAndCluc(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         """
         dataframe.loc[
diff --git a/user_data/strategies/berlinguyinca/DoesNothingStrategy.py b/user_data/strategies/berlinguyinca/DoesNothingStrategy.py
index 33621fc..0f2481a 100644
--- a/user_data/strategies/berlinguyinca/DoesNothingStrategy.py
+++ b/user_data/strategies/berlinguyinca/DoesNothingStrategy.py
@@ -26,17 +26,17 @@ class DoesNothingStrategy(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
             ),
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
             ),
diff --git a/user_data/strategies/berlinguyinca/EMASkipPump.py b/user_data/strategies/berlinguyinca/EMASkipPump.py
index ee35672..c7f849d 100644
--- a/user_data/strategies/berlinguyinca/EMASkipPump.py
+++ b/user_data/strategies/berlinguyinca/EMASkipPump.py
@@ -33,7 +33,7 @@ class EMASkipPump(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """ Adds several different TA indicators to the given DataFrame
         """
 
@@ -59,7 +59,7 @@ class EMASkipPump(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
         dataframe.loc[
             (dataframe['volume'] < (dataframe['volume'].rolling(window=30).mean().shift(1) * 20)) &
@@ -72,7 +72,7 @@ class EMASkipPump(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
         dataframe.loc[
             (dataframe['close'] > dataframe['ema_{}'.format(self.EMA_SHORT_TERM)]) &
diff --git a/user_data/strategies/berlinguyinca/Freqtrade_backtest_validation_freqtrade1.py b/user_data/strategies/berlinguyinca/Freqtrade_backtest_validation_freqtrade1.py
index 3396703..7e530fe 100644
--- a/user_data/strategies/berlinguyinca/Freqtrade_backtest_validation_freqtrade1.py
+++ b/user_data/strategies/berlinguyinca/Freqtrade_backtest_validation_freqtrade1.py
@@ -26,13 +26,13 @@ class Freqtrade_backtest_validation_freqtrade1(IStrategy):
     stoploss = -09.90
     ticker_interval = '1h'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         # SMA - Simple Moving Average
         dataframe['fastMA'] = ta.SMA(dataframe, timeperiod=14)
         dataframe['slowMA'] = ta.SMA(dataframe, timeperiod=28)
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 (dataframe['fastMA'] > dataframe['slowMA'])
@@ -41,7 +41,7 @@ class Freqtrade_backtest_validation_freqtrade1(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 (dataframe['fastMA'] < dataframe['slowMA'])
diff --git a/user_data/strategies/berlinguyinca/Low_BB.py b/user_data/strategies/berlinguyinca/Low_BB.py
index a79421d..0511580 100644
--- a/user_data/strategies/berlinguyinca/Low_BB.py
+++ b/user_data/strategies/berlinguyinca/Low_BB.py
@@ -45,7 +45,7 @@ class Low_BB(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '1m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         ##################################################################################
         # buy and sell indicators
 
@@ -79,7 +79,7 @@ class Low_BB(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -96,7 +96,7 @@ class Low_BB(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/MACDStrategy.py b/user_data/strategies/berlinguyinca/MACDStrategy.py
index a12e6a4..94cc068 100644
--- a/user_data/strategies/berlinguyinca/MACDStrategy.py
+++ b/user_data/strategies/berlinguyinca/MACDStrategy.py
@@ -42,7 +42,7 @@ class MACDStrategy(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
         macd = ta.MACD(dataframe)
         dataframe['macd'] = macd['macd']
@@ -52,7 +52,7 @@ class MACDStrategy(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -67,7 +67,7 @@ class MACDStrategy(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/MACDStrategy_crossed.py b/user_data/strategies/berlinguyinca/MACDStrategy_crossed.py
index f9ef472..2806aa8 100644
--- a/user_data/strategies/berlinguyinca/MACDStrategy_crossed.py
+++ b/user_data/strategies/berlinguyinca/MACDStrategy_crossed.py
@@ -36,7 +36,7 @@ class MACDStrategy_crossed(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
         macd = ta.MACD(dataframe)
         dataframe['macd'] = macd['macd']
@@ -46,7 +46,7 @@ class MACDStrategy_crossed(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -61,7 +61,7 @@ class MACDStrategy_crossed(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/MultiRSI.py b/user_data/strategies/berlinguyinca/MultiRSI.py
index 105940a..3645464 100644
--- a/user_data/strategies/berlinguyinca/MultiRSI.py
+++ b/user_data/strategies/berlinguyinca/MultiRSI.py
@@ -26,7 +26,7 @@ class MultiRSI(IStrategy):
     def get_ticker_indicator(self):
         return int(self.ticker_interval[:-1])
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         from technical.util import resample_to_interval
         from technical.util import resampled_merge
 
@@ -51,7 +51,7 @@ class MultiRSI(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 # must be bearish
@@ -61,7 +61,7 @@ class MultiRSI(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 (dataframe['rsi'] > dataframe['resample_{}_rsi'.format(self.get_ticker_indicator()*2)]) &
diff --git a/user_data/strategies/berlinguyinca/Quickie.py b/user_data/strategies/berlinguyinca/Quickie.py
index e9253eb..281ee25 100644
--- a/user_data/strategies/berlinguyinca/Quickie.py
+++ b/user_data/strategies/berlinguyinca/Quickie.py
@@ -34,7 +34,7 @@ class Quickie(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         macd = ta.MACD(dataframe)
         dataframe['macd'] = macd['macd']
         dataframe['macdsignal'] = macd['macdsignal']
@@ -54,7 +54,7 @@ class Quickie(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (dataframe['adx'] > 30) &
@@ -66,7 +66,7 @@ class Quickie(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (dataframe['adx'] > 70) &
diff --git a/user_data/strategies/berlinguyinca/ReinforcedAverageStrategy.py b/user_data/strategies/berlinguyinca/ReinforcedAverageStrategy.py
index cc36ff5..b637f31 100644
--- a/user_data/strategies/berlinguyinca/ReinforcedAverageStrategy.py
+++ b/user_data/strategies/berlinguyinca/ReinforcedAverageStrategy.py
@@ -31,7 +31,7 @@ class ReinforcedAverageStrategy(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '4h'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
         dataframe['maShort'] = ta.EMA(dataframe, timeperiod=8)
         dataframe['maMedium'] = ta.EMA(dataframe, timeperiod=21)
@@ -43,7 +43,7 @@ class ReinforcedAverageStrategy(IStrategy):
         dataframe['bb_middleband'] = bollinger['mid']
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -60,7 +60,7 @@ class ReinforcedAverageStrategy(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/ReinforcedQuickie.py b/user_data/strategies/berlinguyinca/ReinforcedQuickie.py
index f622acf..a77b8fd 100644
--- a/user_data/strategies/berlinguyinca/ReinforcedQuickie.py
+++ b/user_data/strategies/berlinguyinca/ReinforcedQuickie.py
@@ -47,7 +47,7 @@ class ReinforcedQuickie(IStrategy):
     EMA_MEDIUM_TERM = 12
     EMA_LONG_TERM = 21
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe = self.resample(dataframe, self.ticker_interval, self.resample_factor)
 
         ##################################################################################
@@ -93,7 +93,7 @@ class ReinforcedQuickie(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -138,7 +138,7 @@ class ReinforcedQuickie(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
diff --git a/user_data/strategies/berlinguyinca/ReinforcedSmoothScalp.py b/user_data/strategies/berlinguyinca/ReinforcedSmoothScalp.py
index b540edb..d82576b 100644
--- a/user_data/strategies/berlinguyinca/ReinforcedSmoothScalp.py
+++ b/user_data/strategies/berlinguyinca/ReinforcedSmoothScalp.py
@@ -39,7 +39,7 @@ class ReinforcedSmoothScalp(IStrategy):
     # resample factor to establish our general trend. Basically don't buy if a trend is not given
     resample_factor = 5
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe = self.resample(dataframe, self.ticker_interval, self.resample_factor)
 
         dataframe['ema_high'] = ta.EMA(dataframe, timeperiod=5, price='high')
@@ -61,7 +61,7 @@ class ReinforcedSmoothScalp(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 (
@@ -84,7 +84,7 @@ class ReinforcedSmoothScalp(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (
diff --git a/user_data/strategies/berlinguyinca/Scalp.py b/user_data/strategies/berlinguyinca/Scalp.py
index 0d05607..a7aaf66 100644
--- a/user_data/strategies/berlinguyinca/Scalp.py
+++ b/user_data/strategies/berlinguyinca/Scalp.py
@@ -39,7 +39,7 @@ class Scalp(IStrategy):
     # the shorter the better
     ticker_interval = '1m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    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')
@@ -56,7 +56,7 @@ class Scalp(IStrategy):
 
 
         return dataframe
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 (dataframe['open'] < dataframe['ema_low']) &
@@ -69,7 +69,7 @@ class Scalp(IStrategy):
             ),
             'buy'] = 1
         return dataframe
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 (dataframe['open'] >= dataframe['ema_high'])
diff --git a/user_data/strategies/berlinguyinca/Simple.py b/user_data/strategies/berlinguyinca/Simple.py
index fd51dd6..f6437bb 100644
--- a/user_data/strategies/berlinguyinca/Simple.py
+++ b/user_data/strategies/berlinguyinca/Simple.py
@@ -34,7 +34,7 @@ class Simple(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         # MACD
         macd = ta.MACD(dataframe)
         dataframe['macd'] = macd['macd']
@@ -52,7 +52,7 @@ class Simple(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 (
@@ -65,7 +65,7 @@ class Simple(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         # different strategy used for sell points, due to be able to duplicate it to 100%
         dataframe.loc[
             (
diff --git a/user_data/strategies/berlinguyinca/SmoothOperator.py b/user_data/strategies/berlinguyinca/SmoothOperator.py
index 1c57886..558e983 100644
--- a/user_data/strategies/berlinguyinca/SmoothOperator.py
+++ b/user_data/strategies/berlinguyinca/SmoothOperator.py
@@ -41,7 +41,7 @@ class SmoothOperator(IStrategy):
     # resample factor to establish our general trend. Basically don't buy if a trend is not given
     resample_factor = 12
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         # resampled dataframe to establish if we are in an uptrend, downtrend or sideways trend
         dataframe = StrategyHelper.resample(dataframe, self.ticker_interval, self.resample_factor)
 
@@ -108,7 +108,7 @@ class SmoothOperator(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
 
@@ -178,7 +178,7 @@ class SmoothOperator(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         # different strategy used for sell points, due to be able to duplicate it to 100%
         dataframe.loc[
             (
diff --git a/user_data/strategies/berlinguyinca/SmoothScalp.py b/user_data/strategies/berlinguyinca/SmoothScalp.py
index aa99d41..2c09aa6 100644
--- a/user_data/strategies/berlinguyinca/SmoothScalp.py
+++ b/user_data/strategies/berlinguyinca/SmoothScalp.py
@@ -36,7 +36,7 @@ class SmoothScalp(IStrategy):
     # the shorter the better
     ticker_interval = '1m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    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')
@@ -62,7 +62,7 @@ class SmoothScalp(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 (
@@ -81,7 +81,7 @@ class SmoothScalp(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                     (
diff --git a/user_data/strategies/berlinguyinca/TechnicalExampleStrategy.py b/user_data/strategies/berlinguyinca/TechnicalExampleStrategy.py
index 6eb0c49..d0ef82e 100644
--- a/user_data/strategies/berlinguyinca/TechnicalExampleStrategy.py
+++ b/user_data/strategies/berlinguyinca/TechnicalExampleStrategy.py
@@ -14,12 +14,12 @@ class TechnicalExampleStrategy(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = '5m'
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['cmf'] = cmf(dataframe, 21)
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe.loc[
             (
                 (
@@ -30,7 +30,7 @@ class TechnicalExampleStrategy(IStrategy):
             'buy'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         # different strategy used for sell points, due to be able to duplicate it to 100%
         dataframe.loc[
             (