diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index e87af5aad..491e5c573 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -41,7 +41,7 @@ def generate_text_table(
     floatfmt = ('s', 'd', '.2f', '.8f', '.1f')
     tabular_data = []
     headers = ['pair', 'buy count', 'avg profit %',
-               'total profit ' + stake_currency, 'avg duration']
+               'total profit ' + stake_currency, 'avg duration', 'profit','loss']
     for pair in data:
         result = results[results.currency == pair]
         tabular_data.append([
@@ -50,6 +50,8 @@ def generate_text_table(
             result.profit_percent.mean() * 100.0,
             result.profit_BTC.sum(),
             result.duration.mean() * ticker_interval,
+            result.profit.sum(),
+            result.loss.sum()
         ])
 
     # Append Total
@@ -59,12 +61,15 @@ def generate_text_table(
         results.profit_percent.mean() * 100.0,
         results.profit_BTC.sum(),
         results.duration.mean() * ticker_interval,
+        results.profit.sum(),
+        results.loss.sum(),
+        
     ])
     return tabulate(tabular_data, headers=headers, floatfmt=floatfmt)
 
 
 def backtest(stake_amount: float, processed: Dict[str, DataFrame],
-             max_open_trades: int = 0, realistic: bool = True, sell_profit_only: bool = False, stoploss: int = -1.00) -> DataFrame:
+             max_open_trades: int = 0, realistic: bool = True, sell_profit_only: bool = False, stoploss: int = -1.00, use_sell_signal: bool = False) -> DataFrame:
     """
     Implements backtesting functionality
     :param stake_amount: btc amount to use for each trade
@@ -113,7 +118,7 @@ def backtest(stake_amount: float, processed: Dict[str, DataFrame],
                 current_profit_percent = trade.calc_profit_percent(rate=row2.close)
                 if (sell_profit_only and current_profit_percent < 0) :
                     continue
-                if min_roi_reached(trade, row2.close, row2.date) or row2.sell == 1 or current_profit_percent < stoploss:
+                if min_roi_reached(trade, row2.close, row2.date) or (row2.sell == 1 and use_sell_signal) or current_profit_percent <= stoploss:
                     current_profit_btc = trade.calc_profit(rate=row2.close)
                     lock_pair_until = row2.Index
 
@@ -122,11 +127,13 @@ def backtest(stake_amount: float, processed: Dict[str, DataFrame],
                             pair,
                             current_profit_percent,
                             current_profit_btc,
-                            row2.Index - row.Index
+                            row2.Index - row.Index,  
+                            current_profit_btc > 0,
+                            current_profit_btc < 0
                         )
                     )
                     break
-    labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
+    labels = ['currency', 'profit_percent', 'profit_BTC', 'duration', 'profit','loss']
     return DataFrame.from_records(trades, columns=labels)
 
 
@@ -174,7 +181,7 @@ def start(args):
 
     # Execute backtest and print results
     results = backtest(
-        config['stake_amount'], preprocessed, max_open_trades, args.realistic_simulation, config.get('experimental',{}).get('sell_profit_only', False), config.get('stoploss')
+        config['stake_amount'], preprocessed, max_open_trades, args.realistic_simulation, config.get('experimental',{}).get('sell_profit_only', False), config.get('stoploss'), config.get('experimental',{}).get('use_sell_signal',False)
     )
     logger.info(
         '\n====================== BACKTESTING REPORT ================================\n%s',