diff --git a/freqtrade/optimize/default_hyperopt.py b/freqtrade/optimize/default_hyperopt.py
index 1c93fcc5d..aa3056fc0 100644
--- a/freqtrade/optimize/default_hyperopt.py
+++ b/freqtrade/optimize/default_hyperopt.py
@@ -1,9 +1,7 @@
 # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
 
 from functools import reduce
-from math import exp
 from typing import Any, Callable, Dict, List
-from datetime import datetime
 
 import talib.abstract as ta
 from pandas import DataFrame
@@ -33,21 +31,6 @@ class DefaultHyperOpts(IHyperOpt):
     You can override it with your own hyperopt
     """
 
-    @staticmethod
-    def hyperopt_loss_custom(results: DataFrame, trade_count: int,
-                             min_date: datetime, max_date: datetime, *args, **kwargs) -> float:
-        """
-        Objective function, returns smaller number for more optimal results
-        """
-        total_profit = results.profit_percent.sum()
-        trade_duration = results.trade_duration.mean()
-
-        trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8)
-        profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)
-        duration_loss = 0.4 * min(trade_duration / MAX_ACCEPTED_TRADE_DURATION, 1)
-        result = trade_loss + profit_loss + duration_loss
-        return result
-
     @staticmethod
     def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['adx'] = ta.ADX(dataframe)
diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py
index bf5b70e14..e041554dc 100644
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -80,11 +80,11 @@ class Hyperopt(Backtesting):
               hasattr(self.custom_hyperopt, 'hyperopt_loss_custom')):
             self.calculate_loss = self.custom_hyperopt.hyperopt_loss_custom  # type: ignore
 
-        # Implement fallback to avoid odd crashes when custom-hyperopt fails to load.
-        if not hasattr(self.custom_hyperopt, 'hyperopt_loss_custom'):
-            logger.warning("Could not load hyperopt configuration. "
-                           "Falling back to legacy configuration.")
-            raise OperationalException("Could not load hyperopt loss function.")
+            # Implement fallback to avoid odd crashes when custom-hyperopt fails to load.
+            if not hasattr(self.custom_hyperopt, 'hyperopt_loss_custom'):
+                logger.warning("Could not load hyperopt configuration. "
+                               "Falling back to legacy configuration.")
+                raise OperationalException("Could not load hyperopt loss function.")
 
         # Populate functions here (hasattr is slow so should not be run during "regular" operations)
         if hasattr(self.custom_hyperopt, 'populate_buy_trend'):