# 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