freqtrade_origin/tests/edge/test_edge.py

# pragma pylint: disable=missing-docstring, C0103, C0330
# pragma pylint: disable=protected-access, too-many-lines, invalid-name, too-many-arguments

import logging
import math
from unittest.mock import MagicMock

import arrow
import numpy as np
import pytest
from pandas import DataFrame, to_datetime

from freqtrade.data.converter import ohlcv_to_dataframe
from freqtrade.edge import Edge, PairInfo
from freqtrade.enums import ExitType
from freqtrade.exceptions import OperationalException
from tests.conftest import get_patched_freqtradebot, log_has
from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
                            _get_frame_time_from_offset)


# Cases to be tested:
# 1) Open trade should be removed from the end
# 2) Two complete trades within dataframe (with sell hit for all)
# 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss
# 4) Entered, sl 3%, candle drops 4%, recovers to 1% => Trade closed, 3% loss
# 5) Stoploss and sell are hit. should sell on stoploss
####################################################################

tests_start_time = arrow.get(2018, 10, 3)
timeframe_in_minute = 60

# Helpers for this test file


def _validate_ohlc(buy_ohlc_sell_matrice):
    for index, ohlc in enumerate(buy_ohlc_sell_matrice):
        # if not high < open < low or not high < close < low
        if not ohlc[3] >= ohlc[2] >= ohlc[4] or not ohlc[3] >= ohlc[5] >= ohlc[4]:
            raise Exception('Line ' + str(index + 1) + ' of ohlc has invalid values!')
    return True


def _build_dataframe(buy_ohlc_sell_matrice):
    _validate_ohlc(buy_ohlc_sell_matrice)
    data = []
    for ohlc in buy_ohlc_sell_matrice:
        d = {
            'date': tests_start_time.shift(
                minutes=(
                    ohlc[0] *
                    timeframe_in_minute)).int_timestamp *
            1000,
            'buy': ohlc[1],
            'open': ohlc[2],
            'high': ohlc[3],
            'low': ohlc[4],
            'close': ohlc[5],
            'sell': ohlc[6]}
        data.append(d)

    frame = DataFrame(data)
    frame['date'] = to_datetime(frame['date'],
                                unit='ms',
                                utc=True,
                                infer_datetime_format=True)

    return frame


def _time_on_candle(number):
    return np.datetime64(tests_start_time.shift(
        minutes=(number * timeframe_in_minute)).int_timestamp * 1000, 'ms')


# End helper functions
# Open trade should be removed from the end
tc0 = BTContainer(data=[
    # D  O     H     L     C     V    B  S
    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
    [1, 5000, 5025, 4975, 4987, 6172, 0, 1]],  # enter trade (signal on last candle)
    stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
    trades=[]
)

# Two complete trades within dataframe(with sell hit for all)
tc1 = BTContainer(data=[
    # D  O     H     L     C     V    B  S
    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
    [1, 5000, 5025, 4975, 4987, 6172, 0, 1],  # enter trade (signal on last candle)
    [2, 5000, 5025, 4975, 4987, 6172, 0, 0],  # exit at open
    [3, 5000, 5025, 4975, 4987, 6172, 1, 0],  # no action
    [4, 5000, 5025, 4975, 4987, 6172, 0, 0],  # should enter the trade
    [5, 5000, 5025, 4975, 4987, 6172, 0, 1],  # no action
    [6, 5000, 5025, 4975, 4987, 6172, 0, 0],  # should sell
],
    stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
    trades=[BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=2),
            BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=4, close_tick=6)]
)

# 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss
tc2 = BTContainer(data=[
    # D  O     H     L     C     V    B  S
    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
    [1, 5000, 5025, 4600, 4987, 6172, 0, 0],  # enter trade, stoploss hit
    [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
],
    stop_loss=-0.01, roi={"0": float('inf')}, profit_perc=-0.01,
    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)]
)

# 4) Entered, sl 3 %, candle drops 4%, recovers to 1 % = > Trade closed, 3 % loss
tc3 = BTContainer(data=[
    # D  O     H     L     C     V    B  S
    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
    [1, 5000, 5025, 4800, 4987, 6172, 0, 0],  # enter trade, stoploss hit
    [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
],
    stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)]
)

# 5) Stoploss and sell are hit. should sell on stoploss
tc4 = BTContainer(data=[
    # D  O     H     L     C     V    B  S
    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
    [1, 5000, 5025, 4800, 4987, 6172, 0, 1],  # enter trade, stoploss hit, sell signal
    [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
],
    stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)]
)

TESTS = [
    tc0,
    tc1,
    tc2,
    tc3,
    tc4
]


@pytest.mark.parametrize("data", TESTS)
def test_edge_results(edge_conf, mocker, caplog, data) -> None:
    """
    run functional tests
    """
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
    frame = _build_backtest_dataframe(data.data)
    caplog.set_level(logging.DEBUG)
    edge.fee = 0

    trades = edge._find_trades_for_stoploss_range(frame, 'TEST/BTC', [data.stop_loss])
    results = edge._fill_calculable_fields(DataFrame(trades)) if trades else DataFrame()

    assert len(trades) == len(data.trades)

    if not results.empty:
        assert round(results["profit_ratio"].sum(), 3) == round(data.profit_perc, 3)

    for c, trade in enumerate(data.trades):
        res = results.iloc[c]
        assert res.exit_type == trade.exit_reason
        assert res.open_date == _get_frame_time_from_offset(trade.open_tick).replace(tzinfo=None)
        assert res.close_date == _get_frame_time_from_offset(trade.close_tick).replace(tzinfo=None)


def test_adjust(mocker, edge_conf):
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
    mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
        return_value={
            'E/F': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
            'C/D': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
            'N/O': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60)
        }
    ))

    pairs = ['A/B', 'C/D', 'E/F', 'G/H']
    assert(edge.adjust(pairs) == ['E/F', 'C/D'])


def test_stoploss(mocker, edge_conf):
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
    mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
        return_value={
            'E/F': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
            'C/D': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
            'N/O': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60)
        }
    ))

    assert edge.stoploss('E/F') == -0.01


def test_nonexisting_stoploss(mocker, edge_conf):
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
    mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
        return_value={
            'E/F': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
        }
    ))

    assert edge.stoploss('N/O') == -0.1


def test_edge_stake_amount(mocker, edge_conf):
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
    mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
        return_value={
            'E/F': PairInfo(-0.02, 0.66, 3.71, 0.50, 1.71, 10, 60),
        }
    ))
    assert edge._capital_ratio == 0.5
    assert edge.stake_amount('E/F', free_capital=100, total_capital=100,
                             capital_in_trade=25) == 31.25

    assert edge.stake_amount('E/F', free_capital=20, total_capital=100,
                             capital_in_trade=25) == 20

    assert edge.stake_amount('E/F', free_capital=0, total_capital=100,
                             capital_in_trade=25) == 0

    # Test with increased allowed_risk
    # Result should be no more than allowed capital
    edge._allowed_risk = 0.4
    edge._capital_ratio = 0.5
    assert edge.stake_amount('E/F', free_capital=100, total_capital=100,
                             capital_in_trade=25) == 62.5

    assert edge.stake_amount('E/F', free_capital=100, total_capital=100,
                             capital_in_trade=0) == 50

    edge._capital_ratio = 1
    # Full capital is available
    assert edge.stake_amount('E/F', free_capital=100, total_capital=100,
                             capital_in_trade=0) == 100
    # Full capital is available
    assert edge.stake_amount('E/F', free_capital=0, total_capital=100,
                             capital_in_trade=0) == 0


def test_nonexisting_stake_amount(mocker, edge_conf):
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
    mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
        return_value={
            'E/F': PairInfo(-0.11, 0.66, 3.71, 0.50, 1.71, 10, 60),
        }
    ))
    # should use strategy stoploss
    assert edge.stake_amount('N/O', 1, 2, 1) == 0.15


def test_edge_heartbeat_calculate(mocker, edge_conf):
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
    heartbeat = edge_conf['edge']['process_throttle_secs']

    # should not recalculate if heartbeat not reached
    edge._last_updated = arrow.utcnow().int_timestamp - heartbeat + 1

    assert edge.calculate(edge_conf['exchange']['pair_whitelist']) is False


def mocked_load_data(datadir, pairs=[], timeframe='0m',
                     timerange=None, *args, **kwargs):
    hz = 0.1
    base = 0.001

    NEOBTC = [
        [
            tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
            math.sin(x * hz) / 1000 + base,
            math.sin(x * hz) / 1000 + base + 0.0001,
            math.sin(x * hz) / 1000 + base - 0.0001,
            math.sin(x * hz) / 1000 + base,
            123.45
        ] for x in range(0, 500)]

    hz = 0.2
    base = 0.002
    LTCBTC = [
        [
            tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
            math.sin(x * hz) / 1000 + base,
            math.sin(x * hz) / 1000 + base + 0.0001,
            math.sin(x * hz) / 1000 + base - 0.0001,
            math.sin(x * hz) / 1000 + base,
            123.45
        ] for x in range(0, 500)]

    pairdata = {'NEO/BTC': ohlcv_to_dataframe(NEOBTC, '1h', pair="NEO/BTC",
                                              fill_missing=True),
                'LTC/BTC': ohlcv_to_dataframe(LTCBTC, '1h', pair="LTC/BTC",
                                              fill_missing=True)}
    return pairdata


def test_edge_process_downloaded_data(mocker, edge_conf):
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
    mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
    mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)

    assert edge.calculate(edge_conf['exchange']['pair_whitelist'])
    assert len(edge._cached_pairs) == 2
    assert edge._last_updated <= arrow.utcnow().int_timestamp + 2


def test_edge_process_no_data(mocker, edge_conf, caplog):
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
    mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
    mocker.patch('freqtrade.edge.edge_positioning.load_data', MagicMock(return_value={}))
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)

    assert not edge.calculate(edge_conf['exchange']['pair_whitelist'])
    assert len(edge._cached_pairs) == 0
    assert log_has("No data found. Edge is stopped ...", caplog)
    assert edge._last_updated == 0


def test_edge_process_no_trades(mocker, edge_conf, caplog):
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    mocker.patch('freqtrade.exchange.Exchange.get_fee', return_value=0.001)
    mocker.patch('freqtrade.edge.edge_positioning.refresh_data', )
    mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
    # Return empty
    mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', return_value=[])
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)

    assert not edge.calculate(edge_conf['exchange']['pair_whitelist'])
    assert len(edge._cached_pairs) == 0
    assert log_has("No trades found.", caplog)


def test_edge_process_no_pairs(mocker, edge_conf, caplog):
    edge_conf['exchange']['pair_whitelist'] = []
    mocker.patch('freqtrade.freqtradebot.validate_config_consistency')

    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
    fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', return_value=0.001)
    mocker.patch('freqtrade.edge.edge_positioning.refresh_data')
    mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
    # Return empty
    mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', return_value=[])
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
    assert fee_mock.call_count == 0
    assert edge.fee is None

    assert not edge.calculate(['XRP/USDT'])
    assert fee_mock.call_count == 1
    assert edge.fee == 0.001


def test_edge_init_error(mocker, edge_conf,):
    edge_conf['stake_amount'] = 0.5
    mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
    with pytest.raises(OperationalException,  match='Edge works only with unlimited stake amount'):
        get_patched_freqtradebot(mocker, edge_conf)


@pytest.mark.parametrize("fee,risk_reward_ratio,expectancy", [
    (0.0005, 306.5384615384, 101.5128205128),
    (0.001, 152.6923076923, 50.2307692308),
])
def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectancy):
    edge_conf['edge']['min_trade_number'] = 2
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)

    def get_fee(*args, **kwargs):
        return fee

    freqtrade.exchange.get_fee = get_fee
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)

    trades = [
        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
         'trade_duration': '',
         'open_rate': 17,
         'close_rate': 17,
         'exit_type': 'exit_signal'},

        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
         'trade_duration': '',
         'open_rate': 20,
         'close_rate': 20,
         'exit_type': 'exit_signal'},

        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
         'trade_duration': '',
         'open_rate': 26,
         'close_rate': 34,
         'exit_type': 'exit_signal'}
    ]

    trades_df = DataFrame(trades)
    trades_df = edge._fill_calculable_fields(trades_df)
    final = edge._process_expectancy(trades_df)
    assert len(final) == 1

    assert 'TEST/BTC' in final
    assert final['TEST/BTC'].stoploss == -0.9
    assert round(final['TEST/BTC'].winrate, 10) == 0.3333333333
    assert round(final['TEST/BTC'].risk_reward_ratio, 10) == risk_reward_ratio
    assert round(final['TEST/BTC'].required_risk_reward, 10) == 2.0
    assert round(final['TEST/BTC'].expectancy, 10) == expectancy

    # Pop last item so no trade is profitable
    trades.pop()
    trades_df = DataFrame(trades)
    trades_df = edge._fill_calculable_fields(trades_df)
    final = edge._process_expectancy(trades_df)
    assert len(final) == 0
    assert isinstance(final, dict)


def test_process_expectancy_remove_pumps(mocker, edge_conf, fee,):
    edge_conf['edge']['min_trade_number'] = 2
    edge_conf['edge']['remove_pumps'] = True
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)

    freqtrade.exchange.get_fee = fee
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)

    trades = [
        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
         'open_index': 1,
         'close_index': 1,
         'trade_duration': '',
         'open_rate': 17,
         'close_rate': 15,
         'exit_type': 'sell_signal'},

        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
         'open_index': 4,
         'close_index': 4,
         'trade_duration': '',
         'open_rate': 20,
         'close_rate': 10,
         'exit_type': 'sell_signal'},
        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
         'open_index': 4,
         'close_index': 4,
         'trade_duration': '',
         'open_rate': 20,
         'close_rate': 10,
         'exit_type': 'sell_signal'},
        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
         'open_index': 4,
         'close_index': 4,
         'trade_duration': '',
         'open_rate': 20,
         'close_rate': 10,
         'exit_type': 'sell_signal'},
        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
         'open_index': 4,
         'close_index': 4,
         'trade_duration': '',
         'open_rate': 20,
         'close_rate': 10,
         'exit_type': 'sell_signal'},

        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
         'open_index': 6,
         'close_index': 7,
         'trade_duration': '',
         'open_rate': 26,
         'close_rate': 134,
         'exit_type': 'sell_signal'}
    ]

    trades_df = DataFrame(trades)
    trades_df = edge._fill_calculable_fields(trades_df)
    final = edge._process_expectancy(trades_df)

    assert 'TEST/BTC' in final
    assert final['TEST/BTC'].stoploss == -0.9
    assert final['TEST/BTC'].nb_trades == len(trades_df) - 1
    assert round(final['TEST/BTC'].winrate, 10) == 0.0


def test_process_expectancy_only_wins(mocker, edge_conf, fee,):
    edge_conf['edge']['min_trade_number'] = 2
    freqtrade = get_patched_freqtradebot(mocker, edge_conf)

    freqtrade.exchange.get_fee = fee
    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)

    trades = [
        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
         'open_index': 1,
         'close_index': 1,
         'trade_duration': '',
         'open_rate': 15,
         'close_rate': 17,
         'exit_type': 'sell_signal'},
        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
         'open_index': 4,
         'close_index': 4,
         'trade_duration': '',
         'open_rate': 10,
         'close_rate': 20,
         'exit_type': 'sell_signal'},
        {'pair': 'TEST/BTC',
         'stoploss': -0.9,
         'profit_percent': '',
         'profit_abs': '',
         'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
         'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
         'open_index': 6,
         'close_index': 7,
         'trade_duration': '',
         'open_rate': 26,
         'close_rate': 134,
         'exit_type': 'sell_signal'}
    ]

    trades_df = DataFrame(trades)
    trades_df = edge._fill_calculable_fields(trades_df)
    final = edge._process_expectancy(trades_df)

    assert 'TEST/BTC' in final
    assert final['TEST/BTC'].stoploss == -0.9
    assert final['TEST/BTC'].nb_trades == len(trades_df)
    assert round(final['TEST/BTC'].winrate, 10) == 1.0
    assert round(final['TEST/BTC'].risk_reward_ratio, 10) == float('inf')
    assert round(final['TEST/BTC'].expectancy, 10) == float('inf')