diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 578b7b18d..d02691886 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -73,7 +73,6 @@ class Backtesting(object):
         :return: pretty printed table with tabulate as str
         """
         stake_currency = self.config.get('stake_currency')
-        ticker_interval = self.ticker_interval
 
         floatfmt = ('s', 'd', '.2f', '.8f', '.1f')
         tabular_data = []
@@ -86,7 +85,7 @@ class Backtesting(object):
                 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])
             ])
@@ -97,7 +96,7 @@ class Backtesting(object):
             len(results.index),
             results.profit_percent.mean() * 100.0,
             results.profit_BTC.sum(),
-            results.duration.mean() * ticker_interval,
+            result.duration.mean(),
             len(results[results.profit_BTC > 0]),
             len(results[results.profit_BTC < 0])
         ])
@@ -108,27 +107,27 @@ class Backtesting(object):
         max_open_trades = args.get('max_open_trades', 0)
         trade = Trade(
             open_rate=row.close,
-            open_date=row.date,
+            open_date=row.Index,
             stake_amount=stake_amount,
             amount=stake_amount / row.open,
             fee=exchange.get_fee()
         )
 
         # calculate win/lose forwards from buy point
-        sell_subset = ticker[ticker.date > row.date][['close', 'date', 'sell']]
+        sell_subset = ticker[ticker.index > row.Index][['close', 'sell']]
         for row2 in sell_subset.itertuples(index=True):
             if max_open_trades > 0:
                 # Increase trade_count_lock for every iteration
-                trade_count_lock[row2.date] = trade_count_lock.get(row2.date, 0) + 1
+                trade_count_lock[row2.Index] = trade_count_lock.get(row2.Index, 0) + 1
 
             # Buy is on is in the buy_subset there is a row that matches the date
             # of the sell event
-            buy_signal = not buy_subset[buy_subset.date == row2.date].empty
+            buy_signal = (buy_subset.index == row2.Index).any()
             if(
                     self.analyze.should_sell(
                         trade=trade,
                         rate=row2.close,
-                        date=row2.date,
+                        date=row2.Index,
                         buy=buy_signal,
                         sell=row2.sell
                     )
@@ -139,9 +138,9 @@ class Backtesting(object):
                         pair,
                         trade.calc_profit_percent(rate=row2.close),
                         trade.calc_profit(rate=row2.close),
-                        row2.Index - row.Index
+                        (row2.Index - row.Index).seconds // 60
                     ),\
-                    row2.date
+                    row2.Index
         return None
 
     def backtest(self, args) -> DataFrame:
@@ -174,22 +173,24 @@ class Backtesting(object):
             ticker = self.populate_sell_trend(
                 self.populate_buy_trend(pair_data)
             )
+            if 'date' in ticker:
+                ticker.set_index('date', inplace=True)
             # for each buy point
             lock_pair_until = None
-            headers = ['buy', 'open', 'close', 'date', 'sell']
+            headers = ['buy', 'open', 'close', 'sell']
             buy_subset = ticker[(ticker.buy == 1) & (ticker.sell == 0)][headers]
             for row in buy_subset.itertuples(index=True):
                 if realistic:
-                    if lock_pair_until is not None and row.date <= lock_pair_until:
+                    if lock_pair_until is not None and row.Index <= lock_pair_until:
                         continue
                 if max_open_trades > 0:
                     # Check if max_open_trades has already been reached for the given date
-                    if not trade_count_lock.get(row.date, 0) < max_open_trades:
+                    if not trade_count_lock.get(row.Index, 0) < max_open_trades:
                         continue
 
                 if max_open_trades > 0:
                     # Increase lock
-                    trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1
+                    trade_count_lock[row.Index] = trade_count_lock.get(row.Index, 0) + 1
 
                 ret = self._get_sell_trade_entry(
                     pair=pair,
@@ -209,8 +210,8 @@ class Backtesting(object):
                         # record a tuple of pair, current_profit_percent,
                         # entry-date, duration
                         records.append((pair, trade_entry[1],
-                                        row.date.strftime('%s'),
-                                        row2.date.strftime('%s'),
+                                        row.Index.strftime('%s'),
+                                        row2.Index.strftime('%s'),
                                         row.Index, trade_entry[3]))
         # For now export inside backtest(), maybe change so that backtest()
         # returns a tuple like: (dataframe, records, logs, etc)
diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py
index cf68c19f8..3408a63c3 100644
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -440,7 +440,7 @@ class Hyperopt(Backtesting):
 
         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 > self.max_accepted_trade_duration:
             print('.', end='')
diff --git a/freqtrade/tests/optimize/test_backtesting.py b/freqtrade/tests/optimize/test_backtesting.py
index f6968d370..06133be82 100644
--- a/freqtrade/tests/optimize/test_backtesting.py
+++ b/freqtrade/tests/optimize/test_backtesting.py
@@ -312,9 +312,9 @@ def test_generate_text_table():
         '-------  -----------  --------------  '
         '------------------  --------------  --------  ------\n'
         'BTC_ETH            2           15.00          '
-        '0.60000000           100.0         2       0\n'
+        '0.60000000            20.0         2       0\n'
         'TOTAL              2           15.00          '
-        '0.60000000           100.0         2       0'
+        '0.60000000            20.0         2       0'
     )
 
     assert backtesting._generate_text_table(data={'BTC_ETH': {}}, results=results) == result_str