96 lines
4.2 KiB
Python
96 lines
4.2 KiB
Python
|
# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
|
||
|
|
|
||
|
|
import random
|
||
|
|
from datetime import datetime, timedelta, timezone
|
||
|
|
from pathlib import Path
|
||
|
|
from unittest.mock import MagicMock, PropertyMock
|
||
|
|
import logging
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
import pandas as pd
|
||
|
|
import pytest
|
||
|
|
from arrow import Arrow
|
||
|
|
|
||
|
|
from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_backtesting
|
||
|
|
from freqtrade.configuration import TimeRange
|
||
|
|
from freqtrade.data import history
|
||
|
|
from freqtrade.data.btanalysis import BT_DATA_COLUMNS, evaluate_result_multi
|
||
|
|
from freqtrade.data.converter import clean_ohlcv_dataframe
|
||
|
|
from freqtrade.data.dataprovider import DataProvider
|
||
|
|
from freqtrade.data.history import get_timerange
|
||
|
|
from freqtrade.enums import RunMode, SellType
|
||
|
|
from freqtrade.exceptions import DependencyException, OperationalException
|
||
|
|
from freqtrade.optimize.backtesting import Backtesting
|
||
|
|
from freqtrade.persistence import LocalTrade
|
||
|
|
from freqtrade.resolvers import StrategyResolver
|
||
|
|
from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
|
||
|
|
patched_configuration_load_config_file)
|
||
|
|
|
||
|
|
def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) -> None:
|
||
|
|
default_conf['use_sell_signal'] = False
|
||
|
|
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
||
|
|
mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
|
||
|
|
patch_exchange(mocker)
|
||
|
|
default_conf.update({
|
||
|
|
"position_adjustment_enable": True,
|
||
|
|
"stake_amount": 100.0,
|
||
|
|
"dry_run_wallet": 1000.0,
|
||
|
|
"strategy": "StrategyTestPositionAdjust"
|
||
|
|
})
|
||
|
|
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)
|
||
|
|
processed = backtesting.strategy.advise_all_indicators(data)
|
||
|
|
min_date, max_date = get_timerange(processed)
|
||
|
|
result = backtesting.backtest(
|
||
|
|
processed=processed,
|
||
|
|
start_date=min_date,
|
||
|
|
end_date=max_date,
|
||
|
|
max_open_trades=10,
|
||
|
|
position_stacking=False,
|
||
|
|
)
|
||
|
|
results = result['results']
|
||
|
|
assert not results.empty
|
||
|
|
assert len(results) == 2
|
||
|
|
|
||
|
|
expected = pd.DataFrame(
|
||
|
|
{'pair': [pair, pair],
|
||
|
|
'stake_amount': [500.0, 100.0],
|
||
|
|
'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],
|
||
|
|
'sell_reason': [SellType.ROI.value, SellType.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],
|
||
|
|
'buy_tag': [None, None],
|
||
|
|
})
|
||
|
|
pd.testing.assert_frame_equal(results, expected)
|
||
|
|
data_pair = processed[pair]
|
||
|
|
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))
|