def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair):
def _trend_alternate_hold(dataframe=None, metadata=None):
"""
Buy every xth candle - sell every other xth -2 (hold on to pairs a bit)
"""
if metadata['pair'] in ('ETH/BTC', 'LTC/BTC'):
multi = 20
else:
multi = 18
dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0)
dataframe['sell'] = np.where(
(dataframe.index + multi - 2) % multi == 0, 1, 0)
return dataframe
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
pairs = ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC', 'NXT/BTC']
data = history.load_data(datadir=None, ticker_interval='5m', pairs=pairs)
# Only use 500 lines to increase performance
data = trim_dictlist(data, -500)
# Remove data for one pair from the beginning of the data
data[pair] = data[pair][tres:].reset_index()
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
default_conf['ticker_interval'] = '5m'
backtesting = Backtesting(default_conf)
backtesting.advise_buy = _trend_alternate_hold # Override
backtesting.advise_sell = _trend_alternate_hold # Override
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(data_processed)
backtest_conf = {
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 3,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
results = backtesting.backtest(backtest_conf)
# Make sure we have parallel trades
assert len(evaluate_result_multi(results, '5min', 2)) > 0
# make sure we don't have trades with more than configured max_open_trades
assert len(evaluate_result_multi(results, '5min', 3)) == 0
backtest_conf = {
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 1,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
results = backtesting.backtest(backtest_conf)
assert len(evaluate_result_multi(results, '5min', 1)) == 0
def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir):
def _trend_alternate_hold(dataframe=None, metadata=None):
"""
Buy every xth candle - sell every other xth -2 (hold on to pairs a bit)
"""
if metadata['pair'] in ('ETH/BTC', 'LTC/BTC'):
multi = 20
else:
multi = 18
dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0)
dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0)
return dataframe
mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
pairs = ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC', 'NXT/BTC']
data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=pairs)
# Only use 500 lines to increase performance
data = trim_dictlist(data, -500)
# Remove data for one pair from the beginning of the data
if tres > 0:
data[pair] = data[pair][tres:].reset_index()
default_conf['timeframe'] = '5m'
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.strategy.advise_buy = _trend_alternate_hold # Override
backtesting.strategy.advise_sell = _trend_alternate_hold # Override
processed = backtesting.strategy.advise_all_indicators(data)
min_date, max_date = get_timerange(processed)
backtest_conf = {
'processed': processed,
'start_date': min_date,
'end_date': max_date,
'max_open_trades': 3,
'position_stacking': False,
}
results = backtesting.backtest(**backtest_conf)
# Make sure we have parallel trades
assert len(evaluate_result_multi(results['results'], '5m', 2)) > 0
# make sure we don't have trades with more than configured max_open_trades
assert len(evaluate_result_multi(results['results'], '5m', 3)) == 0
# Cached data correctly removed amounts
offset = 1 if tres == 0 else 0
removed_candles = len(data[pair]) - offset - backtesting.strategy.startup_candle_count
assert len(backtesting.dataprovider.get_analyzed_dataframe(pair, '5m')[0]) == removed_candles
assert len(backtesting.dataprovider.get_analyzed_dataframe(
'NXT/BTC', '5m')[0]) == len(data['NXT/BTC']) - 1 - backtesting.strategy.startup_candle_count
backtest_conf = {
'processed': processed,
'start_date': min_date,
'end_date': max_date,
'max_open_trades': 1,
'position_stacking': False,
}
results = backtesting.backtest(**backtest_conf)
assert len(evaluate_result_multi(results['results'], '5m', 1)) == 0
