Update buy to entry in backtesting
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3637549a5e
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@ -332,11 +332,11 @@ class Backtesting:
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self.dataprovider._set_cached_df(
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pair, self.timeframe, df_analyzed, self.config['candle_type_def'])
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# Create a copy of the dataframe before shifting, that way the buy signal/tag
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# Create a copy of the dataframe before shifting, that way the entry signal/tag
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# remains on the correct candle for callbacks.
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df_analyzed = df_analyzed.copy()
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# To avoid using data from future, we use buy/sell signals shifted
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# To avoid using data from future, we use entry/exit signals shifted
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# from the previous candle
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for col in headers[5:]:
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tag_col = col in ('enter_tag', 'exit_tag')
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@ -649,7 +649,7 @@ class Backtesting:
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proposed_rate=propose_rate, entry_tag=entry_tag,
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side=direction,
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) # default value is the open rate
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# We can't place orders higher than current high (otherwise it'd be a stop limit buy)
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# We can't place orders higher than current high (otherwise it'd be a stop limit entry)
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# which freqtrade does not support in live.
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if direction == "short":
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propose_rate = max(propose_rate, row[LOW_IDX])
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@ -813,7 +813,7 @@ class Backtesting:
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if len(open_trades[pair]) > 0:
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for trade in open_trades[pair]:
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if trade.open_order_id and trade.nr_of_successful_entries == 0:
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# Ignore trade if buy-order did not fill yet
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# Ignore trade if entry-order did not fill yet
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continue
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sell_row = data[pair][-1]
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@ -869,7 +869,7 @@ class Backtesting:
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# Remove trade due to entry timeout expiration.
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return True
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else:
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# Close additional buy order
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# Close additional entry order
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del trade.orders[trade.orders.index(order)]
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if order.side == trade.exit_side:
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self.timedout_exit_orders += 1
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@ -882,7 +882,7 @@ class Backtesting:
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self, data: Dict, pair: str, row_index: int, current_time: datetime) -> Optional[Tuple]:
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try:
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# Row is treated as "current incomplete candle".
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# Buy / sell signals are shifted by 1 to compensate for this.
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# entry / exit signals are shifted by 1 to compensate for this.
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row = data[pair][row_index]
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except IndexError:
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# missing Data for one pair at the end.
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@ -947,14 +947,14 @@ class Backtesting:
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self.dataprovider._set_dataframe_max_index(row_index)
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for t in list(open_trades[pair]):
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# 1. Cancel expired buy/sell orders.
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# 1. Cancel expired entry/exit orders.
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if self.check_order_cancel(t, current_time):
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# Close trade due to buy timeout expiration.
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# Close trade due to entry timeout expiration.
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open_trade_count -= 1
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open_trades[pair].remove(t)
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self.wallets.update()
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# 2. Process buys.
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# 2. Process entries.
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# without positionstacking, we can only have one open trade per pair.
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# max_open_trades must be respected
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# don't open on the last row
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@ -970,7 +970,7 @@ class Backtesting:
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if trade:
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# TODO: hacky workaround to avoid opening > max_open_trades
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# This emulates previous behavior - not sure if this is correct
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# Prevents buying if the trade-slot was freed in this candle
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# Prevents entering if the trade-slot was freed in this candle
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open_trade_count_start += 1
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open_trade_count += 1
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# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
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@ -1052,7 +1052,7 @@ class Backtesting:
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"No data left after adjusting for startup candles.")
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# Use preprocessed_tmp for date generation (the trimmed dataframe).
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# Backtesting will re-trim the dataframes after buy/sell signal generation.
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# Backtesting will re-trim the dataframes after entry/exit signal generation.
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min_date, max_date = history.get_timerange(preprocessed_tmp)
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logger.info(f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
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f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
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