Merge pull request #5002 from freqtrade/track_rejected_trades

Track rejected trades

freqtrade/optimize/backtesting.py

@@ -177,6 +177,7 @@ class Backtesting:
         Trade.use_db = False
         PairLocks.reset_locks()
         Trade.reset_trades()
+        self.rejected_trades = 0
         self.dataprovider.clear_cache()
 
     def _get_ohlcv_as_lists(self, processed: Dict[str, DataFrame]) -> Dict[str, Tuple]:
@@ -336,6 +337,14 @@ class Backtesting:
                     trades.append(trade1)
         return trades
 
+    def trade_slot_available(self, max_open_trades: int, open_trade_count: int) -> bool:
+        # Always allow trades when max_open_trades is enabled.
+        if max_open_trades <= 0 or open_trade_count < max_open_trades:
+            return True
+        # Rejected trade
+        self.rejected_trades += 1
+        return False
+
     def backtest(self, processed: Dict,
                  start_date: datetime, end_date: datetime,
                  max_open_trades: int = 0, position_stacking: bool = False,
@@ -397,11 +406,14 @@ class Backtesting:
                 # without positionstacking, we can only have one open trade per pair.
                 # max_open_trades must be respected
                 # don't open on the last row
-                if ((position_stacking or len(open_trades[pair]) == 0)
-                        and (max_open_trades <= 0 or open_trade_count_start < max_open_trades)
-                        and tmp != end_date
-                        and row[BUY_IDX] == 1 and row[SELL_IDX] != 1
-                        and not PairLocks.is_pair_locked(pair, row[DATE_IDX])):
+                if (
+                    (position_stacking or len(open_trades[pair]) == 0)
+                    and self.trade_slot_available(max_open_trades, open_trade_count_start)
+                    and tmp != end_date
+                    and row[BUY_IDX] == 1
+                    and row[SELL_IDX] != 1
+                    and not PairLocks.is_pair_locked(pair, row[DATE_IDX])
+                ):
                     trade = self._enter_trade(pair, row)
                     if trade:
                         # TODO: hacky workaround to avoid opening > max_open_trades
@@ -439,6 +451,7 @@ class Backtesting:
             'results': results,
             'config': self.strategy.config,
             'locks': PairLocks.get_all_locks(),
+            'rejected_signals': self.rejected_trades,
             'final_balance': self.wallets.get_total(self.strategy.config['stake_currency']),
         }
 

freqtrade/optimize/optimize_reports.py

@@ -355,6 +355,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
         'starting_balance': starting_balance,
         'dry_run_wallet': starting_balance,
         'final_balance': content['final_balance'],
+        'rejected_signals': content['rejected_signals'],
         'max_open_trades': max_open_trades,
         'max_open_trades_setting': (config['max_open_trades']
                                     if config['max_open_trades'] != float('inf') else -1),
@@ -561,7 +562,6 @@ def text_table_add_metrics(strat_results: Dict) -> str:
                                                    strat_results['stake_currency'])),
             ('Total trade volume', round_coin_value(strat_results['total_volume'],
                                                     strat_results['stake_currency'])),
-
             ('', ''),  # Empty line to improve readability
             ('Best Pair', f"{strat_results['best_pair']['key']} "
                           f"{round(strat_results['best_pair']['profit_sum_pct'], 2)}%"),
@@ -580,6 +580,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
             ('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
             ('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
             ('Zero Duration Trades', zero_duration_trades),
+            ('Rejected Buy signals', strat_results.get('rejected_signals', 'N/A')),
             ('', ''),  # Empty line to improve readability
 
             ('Min balance', round_coin_value(strat_results['csum_min'],