freqtrade_origin/tests/optimize/test_backtesting_adjust_position.py

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# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
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from copy import deepcopy
from unittest.mock import MagicMock
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import pandas as pd
import pytest
from freqtrade.configuration import TimeRange
from freqtrade.data import history
from freqtrade.data.history import get_timerange
from freqtrade.enums import ExitType, TradingMode
from freqtrade.optimize.backtesting import Backtesting
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from freqtrade.util.datetime_helpers import dt_utc
from tests.conftest import EXMS, patch_exchange
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def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) -> None:
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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,
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"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(
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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],
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'open_date': pd.to_datetime([dt_utc(2018, 1, 29, 18, 40, 0),
dt_utc(2018, 1, 30, 3, 30, 0)], utc=True
),
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'close_date': pd.to_datetime([dt_utc(2018, 1, 29, 22, 00, 0),
dt_utc(2018, 1, 30, 4, 10, 0)], 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],
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'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],
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'enter_tag': [None, None],
'leverage': [1.0, 1.0],
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'is_short': [False, False],
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'open_timestamp': [1517251200000, 1517283000000],
'close_timestamp': [1517265300000, 1517285400000],
})
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pd.testing.assert_frame_equal(results.drop(columns=['orders']), expected)
data_pair = processed[pair]
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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))
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@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)
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patch_exchange(mocker)
default_conf.update({
"stake_amount": 100.0,
"dry_run_wallet": 1000.0,
"strategy": "StrategyTestV3",
})
backtesting = Backtesting(default_conf)
backtesting.trading_mode = TradingMode.FUTURES
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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
]
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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
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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
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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
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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
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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
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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
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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