diff --git a/freqtrade/analyze.py b/freqtrade/analyze.py
index dcf66b0a2..a4703d0f2 100644
--- a/freqtrade/analyze.py
+++ b/freqtrade/analyze.py
@@ -65,7 +65,7 @@ class Analyze(object):
         frame.drop(frame.tail(1).index, inplace=True)  # eliminate partial candle
         return frame
 
-    def populate_indicators(self, dataframe: DataFrame, pair: str = None) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Adds several different TA indicators to the given DataFrame
 
@@ -75,7 +75,7 @@ class Analyze(object):
         """
         return self.strategy.advise_indicators(dataframe=dataframe, pair=pair)
 
-    def populate_buy_trend(self, dataframe: DataFrame, pair: str = None) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -83,7 +83,7 @@ class Analyze(object):
         """
         return self.strategy.advise_buy(dataframe=dataframe, pair=pair)
 
-    def populate_sell_trend(self, dataframe: DataFrame, pair: str = None) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
@@ -215,5 +215,5 @@ class Analyze(object):
         """
         Creates a dataframe and populates indicators for given ticker data
         """
-        return {pair: self.populate_indicators(self.parse_ticker_dataframe(pair_data))
+        return {pair: self.populate_indicators(self.parse_ticker_dataframe(pair_data), pair)
                 for pair, pair_data in tickerdata.items()}
diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 713f23ecc..c5d0649c9 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -162,7 +162,7 @@ class Backtesting(object):
             pair_data['buy'], pair_data['sell'] = 0, 0  # cleanup from previous run
 
             ticker_data = self.populate_sell_trend(
-                self.populate_buy_trend(pair_data))[headers].copy()
+                self.populate_buy_trend(pair_data, pair), pair)[headers].copy()
 
             # to avoid using data from future, we buy/sell with signal from previous candle
             ticker_data.loc[:, 'buy'] = ticker_data['buy'].shift(1)
diff --git a/freqtrade/tests/optimize/test_backtesting.py b/freqtrade/tests/optimize/test_backtesting.py
index e1876d15b..585223f59 100644
--- a/freqtrade/tests/optimize/test_backtesting.py
+++ b/freqtrade/tests/optimize/test_backtesting.py
@@ -142,7 +142,7 @@ def _trend(signals, buy_value, sell_value):
     return signals
 
 
-def _trend_alternate(dataframe=None):
+def _trend_alternate(dataframe=None, pair=None):
     signals = dataframe
     low = signals['low']
     n = len(low)
@@ -534,7 +534,7 @@ def test_backtest_ticks(default_conf, fee, mocker):
 
 def test_backtest_clash_buy_sell(mocker, default_conf):
     # Override the default buy trend function in our default_strategy
-    def fun(dataframe=None):
+    def fun(dataframe=None, pair=None):
         buy_value = 1
         sell_value = 1
         return _trend(dataframe, buy_value, sell_value)
@@ -550,7 +550,7 @@ def test_backtest_clash_buy_sell(mocker, default_conf):
 
 def test_backtest_only_sell(mocker, default_conf):
     # Override the default buy trend function in our default_strategy
-    def fun(dataframe=None):
+    def fun(dataframe=None, pair=None):
         buy_value = 0
         sell_value = 1
         return _trend(dataframe, buy_value, sell_value)
diff --git a/freqtrade/tests/test_analyze.py b/freqtrade/tests/test_analyze.py
index e8d0816aa..86555fea7 100644
--- a/freqtrade/tests/test_analyze.py
+++ b/freqtrade/tests/test_analyze.py
@@ -56,13 +56,15 @@ def test_dataframe_correct_columns(result):
 
 def test_populates_buy_trend(result):
     # Load the default strategy for the unit test, because this logic is done in main.py
-    dataframe = _ANALYZE.populate_buy_trend(_ANALYZE.populate_indicators(result))
+    dataframe = _ANALYZE.populate_buy_trend(
+        _ANALYZE.populate_indicators(result, 'UNITTEST/BTC'), 'UNITTEST/BTC')
     assert 'buy' in dataframe.columns
 
 
 def test_populates_sell_trend(result):
     # Load the default strategy for the unit test, because this logic is done in main.py
-    dataframe = _ANALYZE.populate_sell_trend(_ANALYZE.populate_indicators(result))
+    dataframe = _ANALYZE.populate_sell_trend(
+        _ANALYZE.populate_indicators(result, 'UNITTEST/BTC'), 'UNITTEST/BTC')
     assert 'sell' in dataframe.columns