From e94da7ca41c817ac96373232f9da3448c235a330 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 15 Oct 2018 22:02:23 +0200 Subject: [PATCH] inverse backtest logic to loop over time - not pairs (more realistic) --- freqtrade/optimize/backtesting.py | 40 +++++++++++++++++++++++++------ 1 file changed, 33 insertions(+), 7 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 6fcde64fa..212c675fd 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -66,6 +66,7 @@ class Backtesting(object): if self.config.get('strategy_list', None): # Force one interval self.ticker_interval = str(self.config.get('ticker_interval')) + self.ticker_interval_mins = constants.TICKER_INTERVAL_MINUTES[self.ticker_interval] for strat in list(self.config['strategy_list']): stratconf = deepcopy(self.config) stratconf['strategy'] = strat @@ -86,6 +87,8 @@ class Backtesting(object): """ self.strategy = strategy self.ticker_interval = self.config.get('ticker_interval') + self.ticker_interval_mins = constants.TICKER_INTERVAL_MINUTES[self.ticker_interval] + self.tickerdata_to_dataframe = strategy.tickerdata_to_dataframe self.advise_buy = strategy.advise_buy self.advise_sell = strategy.advise_sell @@ -280,8 +283,13 @@ class Backtesting(object): processed = args['processed'] max_open_trades = args.get('max_open_trades', 0) position_stacking = args.get('position_stacking', False) + start_date = args.get('start_date') + end_date = args.get('end_date') trades = [] trade_count_lock: Dict = {} + ticker: Dict = {} + pairs = [] + # Create ticker dict for pair, pair_data in processed.items(): pair_data['buy'], pair_data['sell'] = 0, 0 # cleanup from previous run @@ -296,15 +304,29 @@ class Backtesting(object): # Convert from Pandas to list for performance reasons # (Looping Pandas is slow.) - ticker = [x for x in ticker_data.itertuples()] + ticker[pair] = [x for x in ticker_data.itertuples()] + pairs.append(pair) + + lock_pair_until: Dict = {} + tmp = start_date + timedelta(minutes=self.ticker_interval_mins) + index = 0 + # Loop timerange and test per pair + while tmp < end_date: + # print(f"time: {tmp}") + for i, pair in enumerate(ticker): + try: + row = ticker[pair][index] + except IndexError: + # missing Data for one pair ... + # TODO:howto handle this + # logger.warning(f"i: {index} - {tmp} did not exist for {pair}") + continue - lock_pair_until = None - for index, row in enumerate(ticker): if row.buy == 0 or row.sell == 1: continue # skip rows where no buy signal or that would immediately sell off if not position_stacking: - if lock_pair_until is not None and row.date <= lock_pair_until: + if pair in lock_pair_until and row.date <= lock_pair_until[pair]: continue if max_open_trades > 0: # Check if max_open_trades has already been reached for the given date @@ -313,17 +335,19 @@ class Backtesting(object): trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1 - trade_entry = self._get_sell_trade_entry(pair, row, ticker[index + 1:], + trade_entry = self._get_sell_trade_entry(pair, row, ticker[pair][index + 1:], trade_count_lock, args) if trade_entry: - lock_pair_until = trade_entry.close_time + lock_pair_until[pair] = trade_entry.close_time trades.append(trade_entry) else: # Set lock_pair_until to end of testing period if trade could not be closed # This happens only if the buy-signal was with the last candle - lock_pair_until = ticker_data.iloc[-1].date + lock_pair_until[pair] = end_date + tmp += timedelta(minutes=self.ticker_interval_mins) + index += 1 return DataFrame.from_records(trades, columns=BacktestResult._fields) def start(self) -> None: @@ -390,6 +414,8 @@ class Backtesting(object): 'processed': preprocessed, 'max_open_trades': max_open_trades, 'position_stacking': self.config.get('position_stacking', False), + 'start_date': min_date, + 'end_date': max_date, } )