591 lines
22 KiB
Python
591 lines
22 KiB
Python
# pragma pylint: disable=missing-docstring, C0103, C0330
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# pragma pylint: disable=protected-access, too-many-lines, invalid-name, too-many-arguments
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import logging
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import math
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from unittest.mock import MagicMock
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import arrow
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import numpy as np
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import pytest
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from pandas import DataFrame, to_datetime
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from freqtrade.data.converter import ohlcv_to_dataframe
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from freqtrade.edge import Edge, PairInfo
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from freqtrade.enums import ExitType
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from freqtrade.exceptions import OperationalException
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from tests.conftest import get_patched_freqtradebot, log_has
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from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
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_get_frame_time_from_offset)
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# Cases to be tested:
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# 1) Open trade should be removed from the end
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# 2) Two complete trades within dataframe (with sell hit for all)
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# 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss
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# 4) Entered, sl 3%, candle drops 4%, recovers to 1% => Trade closed, 3% loss
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# 5) Stoploss and sell are hit. should sell on stoploss
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####################################################################
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tests_start_time = arrow.get(2018, 10, 3)
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timeframe_in_minute = 60
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# Helpers for this test file
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def _validate_ohlc(buy_ohlc_sell_matrice):
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for index, ohlc in enumerate(buy_ohlc_sell_matrice):
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# if not high < open < low or not high < close < low
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if not ohlc[3] >= ohlc[2] >= ohlc[4] or not ohlc[3] >= ohlc[5] >= ohlc[4]:
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raise Exception('Line ' + str(index + 1) + ' of ohlc has invalid values!')
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return True
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def _build_dataframe(buy_ohlc_sell_matrice):
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_validate_ohlc(buy_ohlc_sell_matrice)
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data = []
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for ohlc in buy_ohlc_sell_matrice:
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d = {
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'date': tests_start_time.shift(
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minutes=(
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ohlc[0] *
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timeframe_in_minute)).int_timestamp *
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1000,
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'buy': ohlc[1],
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'open': ohlc[2],
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'high': ohlc[3],
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'low': ohlc[4],
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'close': ohlc[5],
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'sell': ohlc[6]}
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data.append(d)
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frame = DataFrame(data)
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frame['date'] = to_datetime(frame['date'],
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unit='ms',
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utc=True,
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infer_datetime_format=True)
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return frame
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def _time_on_candle(number):
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return np.datetime64(tests_start_time.shift(
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minutes=(number * timeframe_in_minute)).int_timestamp * 1000, 'ms')
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# End helper functions
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# Open trade should be removed from the end
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tc0 = BTContainer(data=[
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# D O H L C V B S
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[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
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[1, 5000, 5025, 4975, 4987, 6172, 0, 1]], # enter trade (signal on last candle)
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stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
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trades=[]
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)
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# Two complete trades within dataframe(with sell hit for all)
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tc1 = BTContainer(data=[
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# D O H L C V B S
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[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
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[1, 5000, 5025, 4975, 4987, 6172, 0, 1], # enter trade (signal on last candle)
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[2, 5000, 5025, 4975, 4987, 6172, 0, 0], # exit at open
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[3, 5000, 5025, 4975, 4987, 6172, 1, 0], # no action
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[4, 5000, 5025, 4975, 4987, 6172, 0, 0], # should enter the trade
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[5, 5000, 5025, 4975, 4987, 6172, 0, 1], # no action
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[6, 5000, 5025, 4975, 4987, 6172, 0, 0], # should sell
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],
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stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
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trades=[BTrade(sell_reason=ExitType.SELL_SIGNAL, open_tick=1, close_tick=2),
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BTrade(sell_reason=ExitType.SELL_SIGNAL, open_tick=4, close_tick=6)]
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)
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# 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss
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tc2 = BTContainer(data=[
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# D O H L C V B S
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[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
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[1, 5000, 5025, 4600, 4987, 6172, 0, 0], # enter trade, stoploss hit
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[2, 5000, 5025, 4975, 4987, 6172, 0, 0],
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],
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stop_loss=-0.01, roi={"0": float('inf')}, profit_perc=-0.01,
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trades=[BTrade(sell_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)]
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)
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# 4) Entered, sl 3 %, candle drops 4%, recovers to 1 % = > Trade closed, 3 % loss
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tc3 = BTContainer(data=[
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# D O H L C V B S
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[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
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[1, 5000, 5025, 4800, 4987, 6172, 0, 0], # enter trade, stoploss hit
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[2, 5000, 5025, 4975, 4987, 6172, 0, 0],
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],
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stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
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trades=[BTrade(sell_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)]
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)
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# 5) Stoploss and sell are hit. should sell on stoploss
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tc4 = BTContainer(data=[
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# D O H L C V B S
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[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
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[1, 5000, 5025, 4800, 4987, 6172, 0, 1], # enter trade, stoploss hit, sell signal
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[2, 5000, 5025, 4975, 4987, 6172, 0, 0],
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],
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stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
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trades=[BTrade(sell_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)]
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)
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TESTS = [
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tc0,
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tc1,
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tc2,
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tc3,
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tc4
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]
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@pytest.mark.parametrize("data", TESTS)
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def test_edge_results(edge_conf, mocker, caplog, data) -> None:
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"""
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run functional tests
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"""
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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frame = _build_backtest_dataframe(data.data)
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caplog.set_level(logging.DEBUG)
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edge.fee = 0
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trades = edge._find_trades_for_stoploss_range(frame, 'TEST/BTC', [data.stop_loss])
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results = edge._fill_calculable_fields(DataFrame(trades)) if trades else DataFrame()
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assert len(trades) == len(data.trades)
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if not results.empty:
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assert round(results["profit_ratio"].sum(), 3) == round(data.profit_perc, 3)
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for c, trade in enumerate(data.trades):
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res = results.iloc[c]
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assert res.exit_type == trade.sell_reason
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assert res.open_date == _get_frame_time_from_offset(trade.open_tick).replace(tzinfo=None)
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assert res.close_date == _get_frame_time_from_offset(trade.close_tick).replace(tzinfo=None)
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def test_adjust(mocker, edge_conf):
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
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return_value={
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'E/F': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
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'C/D': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
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'N/O': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60)
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}
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))
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pairs = ['A/B', 'C/D', 'E/F', 'G/H']
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assert(edge.adjust(pairs) == ['E/F', 'C/D'])
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def test_stoploss(mocker, edge_conf):
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
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return_value={
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'E/F': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
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'C/D': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
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'N/O': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60)
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}
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))
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assert edge.stoploss('E/F') == -0.01
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def test_nonexisting_stoploss(mocker, edge_conf):
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
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return_value={
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'E/F': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
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}
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))
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assert edge.stoploss('N/O') == -0.1
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def test_edge_stake_amount(mocker, edge_conf):
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
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return_value={
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'E/F': PairInfo(-0.02, 0.66, 3.71, 0.50, 1.71, 10, 60),
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}
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))
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assert edge._capital_ratio == 0.5
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assert edge.stake_amount('E/F', free_capital=100, total_capital=100,
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capital_in_trade=25) == 31.25
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assert edge.stake_amount('E/F', free_capital=20, total_capital=100,
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capital_in_trade=25) == 20
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assert edge.stake_amount('E/F', free_capital=0, total_capital=100,
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capital_in_trade=25) == 0
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# Test with increased allowed_risk
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# Result should be no more than allowed capital
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edge._allowed_risk = 0.4
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edge._capital_ratio = 0.5
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assert edge.stake_amount('E/F', free_capital=100, total_capital=100,
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capital_in_trade=25) == 62.5
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assert edge.stake_amount('E/F', free_capital=100, total_capital=100,
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capital_in_trade=0) == 50
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edge._capital_ratio = 1
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# Full capital is available
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assert edge.stake_amount('E/F', free_capital=100, total_capital=100,
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capital_in_trade=0) == 100
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# Full capital is available
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assert edge.stake_amount('E/F', free_capital=0, total_capital=100,
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capital_in_trade=0) == 0
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def test_nonexisting_stake_amount(mocker, edge_conf):
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
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return_value={
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'E/F': PairInfo(-0.11, 0.66, 3.71, 0.50, 1.71, 10, 60),
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}
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))
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# should use strategy stoploss
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assert edge.stake_amount('N/O', 1, 2, 1) == 0.15
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def test_edge_heartbeat_calculate(mocker, edge_conf):
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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heartbeat = edge_conf['edge']['process_throttle_secs']
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# should not recalculate if heartbeat not reached
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edge._last_updated = arrow.utcnow().int_timestamp - heartbeat + 1
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assert edge.calculate(edge_conf['exchange']['pair_whitelist']) is False
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def mocked_load_data(datadir, pairs=[], timeframe='0m',
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timerange=None, *args, **kwargs):
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hz = 0.1
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base = 0.001
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NEOBTC = [
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[
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tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
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math.sin(x * hz) / 1000 + base,
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math.sin(x * hz) / 1000 + base + 0.0001,
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math.sin(x * hz) / 1000 + base - 0.0001,
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math.sin(x * hz) / 1000 + base,
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123.45
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] for x in range(0, 500)]
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hz = 0.2
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base = 0.002
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LTCBTC = [
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[
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tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
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math.sin(x * hz) / 1000 + base,
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math.sin(x * hz) / 1000 + base + 0.0001,
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math.sin(x * hz) / 1000 + base - 0.0001,
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math.sin(x * hz) / 1000 + base,
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123.45
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] for x in range(0, 500)]
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pairdata = {'NEO/BTC': ohlcv_to_dataframe(NEOBTC, '1h', pair="NEO/BTC",
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fill_missing=True),
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'LTC/BTC': ohlcv_to_dataframe(LTCBTC, '1h', pair="LTC/BTC",
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fill_missing=True)}
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return pairdata
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def test_edge_process_downloaded_data(mocker, edge_conf):
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
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mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
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mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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assert edge.calculate(edge_conf['exchange']['pair_whitelist'])
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assert len(edge._cached_pairs) == 2
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assert edge._last_updated <= arrow.utcnow().int_timestamp + 2
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def test_edge_process_no_data(mocker, edge_conf, caplog):
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
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mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
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mocker.patch('freqtrade.edge.edge_positioning.load_data', MagicMock(return_value={}))
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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assert not edge.calculate(edge_conf['exchange']['pair_whitelist'])
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assert len(edge._cached_pairs) == 0
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assert log_has("No data found. Edge is stopped ...", caplog)
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assert edge._last_updated == 0
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def test_edge_process_no_trades(mocker, edge_conf, caplog):
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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mocker.patch('freqtrade.exchange.Exchange.get_fee', return_value=0.001)
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mocker.patch('freqtrade.edge.edge_positioning.refresh_data', )
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mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
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# Return empty
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mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', return_value=[])
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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assert not edge.calculate(edge_conf['exchange']['pair_whitelist'])
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assert len(edge._cached_pairs) == 0
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assert log_has("No trades found.", caplog)
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def test_edge_process_no_pairs(mocker, edge_conf, caplog):
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edge_conf['exchange']['pair_whitelist'] = []
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mocker.patch('freqtrade.freqtradebot.validate_config_consistency')
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', return_value=0.001)
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mocker.patch('freqtrade.edge.edge_positioning.refresh_data')
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mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
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# Return empty
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mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', return_value=[])
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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assert fee_mock.call_count == 0
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assert edge.fee is None
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assert not edge.calculate(['XRP/USDT'])
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assert fee_mock.call_count == 1
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assert edge.fee == 0.001
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def test_edge_init_error(mocker, edge_conf,):
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edge_conf['stake_amount'] = 0.5
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mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
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with pytest.raises(OperationalException, match='Edge works only with unlimited stake amount'):
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get_patched_freqtradebot(mocker, edge_conf)
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@pytest.mark.parametrize("fee,risk_reward_ratio,expectancy", [
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(0.0005, 306.5384615384, 101.5128205128),
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(0.001, 152.6923076923, 50.2307692308),
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])
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def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectancy):
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edge_conf['edge']['min_trade_number'] = 2
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freqtrade = get_patched_freqtradebot(mocker, edge_conf)
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def get_fee(*args, **kwargs):
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return fee
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freqtrade.exchange.get_fee = get_fee
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edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
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trades = [
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{'pair': 'TEST/BTC',
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'stoploss': -0.9,
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'profit_percent': '',
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'profit_abs': '',
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'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
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'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
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'trade_duration': '',
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'open_rate': 17,
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'close_rate': 17,
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'exit_type': 'sell_signal'},
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{'pair': 'TEST/BTC',
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'stoploss': -0.9,
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'profit_percent': '',
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'profit_abs': '',
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'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
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'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
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'trade_duration': '',
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'open_rate': 20,
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'close_rate': 20,
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'exit_type': 'sell_signal'},
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{'pair': 'TEST/BTC',
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'stoploss': -0.9,
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'profit_percent': '',
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'profit_abs': '',
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'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
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'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
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'trade_duration': '',
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'open_rate': 26,
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'close_rate': 34,
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'exit_type': 'sell_signal'}
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]
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trades_df = DataFrame(trades)
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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')
|