# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument from copy import deepcopy from unittest.mock import MagicMock import pandas as pd import pytest from arrow import Arrow from freqtrade.configuration import TimeRange from freqtrade.data import history from freqtrade.data.history import get_timerange from freqtrade.enums import ExitType from freqtrade.optimize.backtesting import Backtesting from tests.conftest import EXMS, patch_exchange def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) -> None: default_conf['use_exit_signal'] = False default_conf['max_open_trades'] = 10 mocker.patch(f'{EXMS}.get_fee', fee) mocker.patch('freqtrade.optimize.backtesting.amount_to_contract_precision', lambda x, *args, **kwargs: round(x, 8)) mocker.patch(f"{EXMS}.get_min_pair_stake_amount", return_value=0.00001) mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=float('inf')) patch_exchange(mocker) default_conf.update({ "stake_amount": 100.0, "dry_run_wallet": 1000.0, "strategy": "StrategyTestV3" }) backtesting = Backtesting(default_conf) backtesting._set_strategy(backtesting.strategylist[0]) pair = 'UNITTEST/BTC' timerange = TimeRange('date', None, 1517227800, 0) data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'], timerange=timerange) backtesting.strategy.position_adjustment_enable = True processed = backtesting.strategy.advise_all_indicators(data) min_date, max_date = get_timerange(processed) result = backtesting.backtest( processed=deepcopy(processed), start_date=min_date, end_date=max_date, ) results = result['results'] assert not results.empty assert len(results) == 2 expected = pd.DataFrame( {'pair': [pair, pair], 'stake_amount': [500.0, 100.0], 'max_stake_amount': [500.0, 100], 'amount': [4806.87657523, 970.63960782], 'open_date': pd.to_datetime([Arrow(2018, 1, 29, 18, 40, 0).datetime, Arrow(2018, 1, 30, 3, 30, 0).datetime], utc=True ), 'close_date': pd.to_datetime([Arrow(2018, 1, 29, 22, 00, 0).datetime, Arrow(2018, 1, 30, 4, 10, 0).datetime], utc=True), 'open_rate': [0.10401764894444211, 0.10302485], 'close_rate': [0.10453904066847439, 0.103541], 'fee_open': [0.0025, 0.0025], 'fee_close': [0.0025, 0.0025], 'trade_duration': [200, 40], 'profit_ratio': [0.0, 0.0], 'profit_abs': [0.0, 0.0], 'exit_reason': [ExitType.ROI.value, ExitType.ROI.value], 'initial_stop_loss_abs': [0.0940005, 0.09272236], 'initial_stop_loss_ratio': [-0.1, -0.1], 'stop_loss_abs': [0.0940005, 0.09272236], 'stop_loss_ratio': [-0.1, -0.1], 'min_rate': [0.10370188, 0.10300000000000001], 'max_rate': [0.10481985, 0.1038888], 'is_open': [False, False], 'enter_tag': [None, None], 'leverage': [1.0, 1.0], 'is_short': [False, False], 'open_timestamp': [1517251200000, 1517283000000], 'close_timestamp': [1517265300000, 1517285400000], }) pd.testing.assert_frame_equal(results.drop(columns=['orders']), expected) data_pair = processed[pair] assert len(results.iloc[0]['orders']) == 6 assert len(results.iloc[1]['orders']) == 2 for _, t in results.iterrows(): ln = data_pair.loc[data_pair["date"] == t["open_date"]] # Check open trade rate alignes to open rate assert ln is not None # check close trade rate alignes to close rate or is between high and low ln = data_pair.loc[data_pair["date"] == t["close_date"]] assert (round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6) or round(ln.iloc[0]["low"], 6) < round( t["close_rate"], 6) < round(ln.iloc[0]["high"], 6)) @pytest.mark.parametrize('leverage', [ 1, 2 ]) def test_backtest_position_adjustment_detailed(default_conf, fee, mocker, leverage) -> None: default_conf['use_exit_signal'] = False mocker.patch(f'{EXMS}.get_fee', fee) mocker.patch(f"{EXMS}.get_min_pair_stake_amount", return_value=10) mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=float('inf')) mocker.patch(f"{EXMS}.get_max_leverage", return_value=10) patch_exchange(mocker) default_conf.update({ "stake_amount": 100.0, "dry_run_wallet": 1000.0, "strategy": "StrategyTestV3" }) backtesting = Backtesting(default_conf) backtesting._can_short = True backtesting._set_strategy(backtesting.strategylist[0]) pair = 'XRP/USDT' row = [ pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0), 2.1, # Open 2.2, # High 1.9, # Low 2.1, # Close 1, # enter_long 0, # exit_long 0, # enter_short 0, # exit_short '', # enter_tag '', # exit_tag ] backtesting.strategy.leverage = MagicMock(return_value=leverage) trade = backtesting._enter_trade(pair, row=row, direction='long') trade.orders[0].close_bt_order(row[0], trade) assert trade assert pytest.approx(trade.stake_amount) == 100.0 assert pytest.approx(trade.amount) == 47.61904762 * leverage assert len(trade.orders) == 1 backtesting.strategy.adjust_trade_position = MagicMock(return_value=None) trade = backtesting._get_adjust_trade_entry_for_candle(trade, row) assert trade assert pytest.approx(trade.stake_amount) == 100.0 assert pytest.approx(trade.amount) == 47.61904762 * leverage assert len(trade.orders) == 1 # Increase position by 100 backtesting.strategy.adjust_trade_position = MagicMock(return_value=100) trade = backtesting._get_adjust_trade_entry_for_candle(trade, row) assert trade assert pytest.approx(trade.stake_amount) == 200.0 assert pytest.approx(trade.amount) == 95.23809524 * leverage assert len(trade.orders) == 2 # Reduce by more than amount - no change to trade. backtesting.strategy.adjust_trade_position = MagicMock(return_value=-500) trade = backtesting._get_adjust_trade_entry_for_candle(trade, row) assert trade assert pytest.approx(trade.stake_amount) == 200.0 assert pytest.approx(trade.amount) == 95.23809524 * leverage assert len(trade.orders) == 2 assert trade.nr_of_successful_entries == 2 # Reduce position by 50 backtesting.strategy.adjust_trade_position = MagicMock(return_value=-100) trade = backtesting._get_adjust_trade_entry_for_candle(trade, row) assert trade assert pytest.approx(trade.stake_amount) == 100.0 assert pytest.approx(trade.amount) == 47.61904762 * leverage assert len(trade.orders) == 3 assert trade.nr_of_successful_entries == 2 assert trade.nr_of_successful_exits == 1 # Adjust below minimum backtesting.strategy.adjust_trade_position = MagicMock(return_value=-99) trade = backtesting._get_adjust_trade_entry_for_candle(trade, row) assert trade assert pytest.approx(trade.stake_amount) == 100.0 assert pytest.approx(trade.amount) == 47.61904762 * leverage assert len(trade.orders) == 3 assert trade.nr_of_successful_entries == 2 assert trade.nr_of_successful_exits == 1