diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index d6d016aba..d13708b90 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -33,7 +33,7 @@ def get_timeframe(data: Dict[str, DataFrame]) -> Tuple[arrow.Arrow, arrow.Arrow]
 
 
 def generate_text_table(
-        data: Dict[str, Dict], results: DataFrame, stake_currency, ticker_interval) -> str:
+        data: Dict[str, Dict], results: DataFrame, stake_currency) -> str:
     """
     Generates and returns a text table for the given backtest data and the results dataframe
     :return: pretty printed table with tabulate as str
@@ -49,7 +49,7 @@ def generate_text_table(
             len(result.index),
             result.profit_percent.mean() * 100.0,
             result.profit_BTC.sum(),
-            result.duration.mean() * ticker_interval,
+            result.duration.mean(),
             len(result[result.profit_BTC > 0]),
             len(result[result.profit_BTC < 0])
         ])
@@ -60,7 +60,7 @@ def generate_text_table(
         len(results.index),
         results.profit_percent.mean() * 100.0,
         results.profit_BTC.sum(),
-        results.duration.mean() * ticker_interval,
+        results.duration.mean(),
         len(results[results.profit_BTC > 0]),
         len(results[results.profit_BTC < 0])
     ])
@@ -91,7 +91,7 @@ def get_sell_trade_entry(pair, row, buy_subset, ticker, trade_count_lock, args):
             return row2, (pair,
                           trade.calc_profit_percent(rate=row2.close),
                           trade.calc_profit(rate=row2.close),
-                          row2.Index - row.Index
+                          (row2.date - row.date).seconds // 60
                           ), row2.date
     return None
 
@@ -231,5 +231,5 @@ def start(args):
                         })
     logger.info(
         '\n==================================== BACKTESTING REPORT ====================================\n%s',  # noqa
-        generate_text_table(data, results, config['stake_currency'], strategy.ticker_interval)
+        generate_text_table(data, results, config['stake_currency'])
     )
diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py
index 8b89e1985..12c061b4f 100644
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -406,7 +406,7 @@ def optimizer(params):
 
     total_profit = results.profit_percent.sum()
     trade_count = len(results.index)
-    trade_duration = results.duration.mean() * 5
+    trade_duration = results.duration.mean()
 
     if trade_count == 0 or trade_duration > MAX_ACCEPTED_TRADE_DURATION:
         print('.', end='')
diff --git a/freqtrade/tests/optimize/test_backtesting.py b/freqtrade/tests/optimize/test_backtesting.py
index 0dd4f777a..bf060e374 100644
--- a/freqtrade/tests/optimize/test_backtesting.py
+++ b/freqtrade/tests/optimize/test_backtesting.py
@@ -29,12 +29,12 @@ def test_generate_text_table():
             'loss': [0, 0]
         }
     )
-    print(generate_text_table({'BTC_ETH': {}}, results, 'BTC', 5))
-    assert generate_text_table({'BTC_ETH': {}}, results, 'BTC', 5) == (
+    print(generate_text_table({'BTC_ETH': {}}, results, 'BTC'))
+    assert generate_text_table({'BTC_ETH': {}}, results, 'BTC') == (
         'pair       buy count    avg profit %    total profit BTC    avg duration    profit    loss\n'  # noqa
         '-------  -----------  --------------  ------------------  --------------  --------  ------\n'  # noqa
-        'BTC_ETH            2           15.00          0.60000000           100.0         2       0\n'  # noqa
-        'TOTAL              2           15.00          0.60000000           100.0         2       0')  # noqa
+        'BTC_ETH            2           15.00          0.60000000            20.0         2       0\n'  # noqa
+        'TOTAL              2           15.00          0.60000000            20.0         2       0')  # noqa
 
 
 def test_get_timeframe(default_strategy):