Allow "detailed" backtesting timeframe to look into the candle

freqtrade/commands/arguments.py

@@ -22,7 +22,7 @@ ARGS_COMMON_OPTIMIZE = ["timeframe", "timerange", "dataformat_ohlcv",
                         "max_open_trades", "stake_amount", "fee", "pairs"]
 
 ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_positions",
-                                        "enable_protections", "dry_run_wallet",
+                                        "enable_protections", "dry_run_wallet", "detail_timeframe",
                                         "strategy_list", "export", "exportfilename"]
 
 ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",

freqtrade/commands/cli_options.py

@@ -135,6 +135,10 @@ AVAILABLE_CLI_OPTIONS = {
         help='Override the value of the `stake_amount` configuration setting.',
     ),
     # Backtesting
+    "detail_timeframe": Arg(
+        '--timeframe-detail',
+        help='Specify detail timeframe for backtesting (`1m`, `5m`, `30m`, `1h`, `1d`).',
+    ),
     "position_stacking": Arg(
         '--eps', '--enable-position-stacking',
         help='Allow buying the same pair multiple times (position stacking).',

freqtrade/configuration/configuration.py

@@ -242,6 +242,9 @@ class Configuration:
             except ValueError:
                 pass
 
+        self._args_to_config(config, argname='detail_timeframe',
+                             logstring='Parameter --detail-timeframe detected, '
+                             'using {} for intra-candle backtesting')
         self._args_to_config(config, argname='stake_amount',
                              logstring='Parameter --stake-amount detected, '
                              'overriding stake_amount to: {} ...')

freqtrade/optimize/backtesting.py

@@ -86,6 +86,16 @@ class Backtesting:
                                        "configuration or as cli argument `--timeframe 5m`")
         self.timeframe = str(self.config.get('timeframe'))
         self.timeframe_min = timeframe_to_minutes(self.timeframe)
+        # Load detail timeframe if specified
+        self.timeframe_detail = str(self.config.get('detail_timeframe', ''))
+        if self.timeframe_detail:
+            self.timeframe_detail_min = timeframe_to_minutes(self.timeframe_detail)
+            if self.timeframe_min <= self.timeframe_detail_min:
+                raise OperationalException(
+                    "Detail timeframe must be smaller than strategy timeframe.")
+
+        else:
+            self.timeframe_detail_min = 0
 
         self.pairlists = PairListManager(self.exchange, self.config)
         if 'VolumePairList' in self.pairlists.name_list:
@@ -158,7 +168,7 @@ class Backtesting:
                 conf['protections'] = strategy.protections
             self.protections = ProtectionManager(self.config, strategy.protections)
 
-    def load_bt_data(self) -> Tuple[Dict[str, DataFrame], TimeRange]:
+    def load_bt_data(self) -> Tuple[Dict[str, DataFrame], TimeRange, Dict[str, DataFrame]]:
         """
         Loads backtest data and returns the data combined with the timerange
         as tuple.
@@ -174,6 +184,18 @@ class Backtesting:
             fail_without_data=True,
             data_format=self.config.get('dataformat_ohlcv', 'json'),
         )
+        if self.timeframe_detail:
+            detail_data = history.load_data(
+                datadir=self.config['datadir'],
+                pairs=self.pairlists.whitelist,
+                timeframe=self.timeframe_detail,
+                timerange=self.timerange,
+                startup_candles=0,
+                fail_without_data=True,
+                data_format=self.config.get('dataformat_ohlcv', 'json'),
+            )
+        else:
+            detail_data = None
 
         min_date, max_date = history.get_timerange(data)
 
@@ -186,7 +208,7 @@ class Backtesting:
                                                  self.required_startup, min_date)
 
         self.progress.set_new_value(1)
-        return data, self.timerange
+        return data, self.timerange, detail_data
 
     def prepare_backtest(self, enable_protections):
         """
@@ -318,7 +340,8 @@ class Backtesting:
         else:
             return sell_row[OPEN_IDX]
 
-    def _get_sell_trade_entry(self, trade: LocalTrade, sell_row: Tuple) -> Optional[LocalTrade]:
+    def _get_sell_trade_entry_for_candle(self, trade: LocalTrade,
+                                         sell_row: Tuple) -> Optional[LocalTrade]:
         sell_candle_time = sell_row[DATE_IDX].to_pydatetime()
         sell = self.strategy.should_sell(trade, sell_row[OPEN_IDX],  # type: ignore
                                          sell_candle_time, sell_row[BUY_IDX],
@@ -346,6 +369,29 @@ class Backtesting:
 
         return None
 
+    def _get_sell_trade_entry(self, trade: LocalTrade, sell_row: Tuple) -> Optional[LocalTrade]:
+        if self.timeframe_detail:
+            sell_candle_time = sell_row[DATE_IDX].to_pydatetime()
+            sell_candle_end = sell_candle_time + timedelta(minutes=self.timeframe_min)
+
+            detail_data = self.detail_data[trade.pair]
+            detail_data = detail_data.loc[
+                (detail_data['date'] >= sell_candle_time) &
+                (detail_data['date'] < sell_candle_end)
+             ]
+            detail_data['buy'] = sell_row[BUY_IDX]
+            detail_data['sell'] = sell_row[SELL_IDX]
+            headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high']
+            for det_row in detail_data[headers].values.tolist():
+                res = self._get_sell_trade_entry_for_candle(trade, det_row)
+                if res:
+                    return res
+
+            return None
+
+        else:
+            return self._get_sell_trade_entry_for_candle(trade, sell_row)
+
     def _enter_trade(self, pair: str, row: List) -> Optional[LocalTrade]:
         try:
             stake_amount = self.wallets.get_trade_stake_amount(pair, None)
@@ -591,7 +637,7 @@ class Backtesting:
         """
         data: Dict[str, Any] = {}
 
-        data, timerange = self.load_bt_data()
+        data, timerange, self.detail_data = self.load_bt_data()
         logger.info("Dataload complete. Calculating indicators")
 
         for strat in self.strategylist: