Merge branch 'develop' into feat/short

freqtrade/optimize/backtesting.py

@@ -46,6 +46,7 @@ ELONG_IDX = 6  # Exit long
 SHORT_IDX = 7
 ESHORT_IDX = 8  # Exit short
 ENTER_TAG_IDX = 9
+EXIT_TAG_IDX = 10
 
 
 class Backtesting:
@@ -257,7 +258,7 @@ class Backtesting:
         # Every change to this headers list must evaluate further usages of the resulting tuple
         # and eventually change the constants for indexes at the top
         headers = ['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
-                   'enter_short', 'exit_short', 'enter_tag']
+                   'enter_short', 'exit_short', 'enter_tag', 'exit_tag']
         data: Dict = {}
         self.progress.init_step(BacktestState.CONVERT, len(processed))
 
@@ -283,7 +284,7 @@ class Backtesting:
                 if col in df_analyzed.columns:
                     df_analyzed.loc[:, col] = df_analyzed.loc[:, col].shift(1)
                 else:
-                    df_analyzed.loc[:, col] = 0 if col != 'enter_tag' else None
+                    df_analyzed.loc[:, col] = 0 if col not in ('enter_tag', 'exit_tag') else None
 
             # Update dataprovider cache
             self.dataprovider._set_cached_df(pair, self.timeframe, df_analyzed)
@@ -326,7 +327,9 @@ class Backtesting:
                     # Worst case: price ticks tiny bit above open and dives down.
                     stop_rate = sell_row[OPEN_IDX] * (1 - abs(trade.stop_loss_pct))
                     assert stop_rate < sell_row[HIGH_IDX]
-                return stop_rate
+                # Limit lower-end to candle low to avoid sells below the low.
+                # This still remains "worst case" - but "worst realistic case".
+                return max(sell_row[LOW_IDX], stop_rate)
 
             # Set close_rate to stoploss
             return trade.stop_loss
@@ -375,6 +378,16 @@ class Backtesting:
         if sell.sell_flag:
             trade.close_date = sell_candle_time
             trade.sell_reason = sell.sell_reason
+
+            # Checks and adds an exit tag, after checking that the length of the
+            # sell_row has the length for an exit tag column
+            if(
+                len(sell_row) > EXIT_TAG_IDX
+                and sell_row[EXIT_TAG_IDX] is not None
+                and len(sell_row[EXIT_TAG_IDX]) > 0
+            ):
+                trade.sell_reason = sell_row[EXIT_TAG_IDX]
+
             trade_dur = int((trade.close_date_utc - trade.open_date_utc).total_seconds() // 60)
             closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)