mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-11-10 18:23:55 +00:00
136 lines
4.9 KiB
Python
136 lines
4.9 KiB
Python
# pragma pylint: disable=missing-docstring
|
|
import logging
|
|
import os
|
|
from functools import reduce
|
|
from math import exp
|
|
from operator import itemgetter
|
|
|
|
import pytest
|
|
from hyperopt import fmin, tpe, hp, Trials, STATUS_OK
|
|
from pandas import DataFrame
|
|
|
|
from freqtrade.tests.test_backtesting import backtest, format_results
|
|
from freqtrade.vendor.qtpylib.indicators import crossed_above
|
|
|
|
logging.disable(logging.DEBUG) # disable debug logs that slow backtesting a lot
|
|
|
|
# set TARGET_TRADES to suit your number concurrent trades so its realistic to 20days of data
|
|
TARGET_TRADES = 1200
|
|
|
|
|
|
def buy_strategy_generator(params):
|
|
print(params)
|
|
|
|
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
|
|
conditions = []
|
|
# GUARDS AND TRENDS
|
|
if params['uptrend_long_ema']['enabled']:
|
|
conditions.append(dataframe['ema50'] > dataframe['ema100'])
|
|
if params['mfi']['enabled']:
|
|
conditions.append(dataframe['mfi'] < params['mfi']['value'])
|
|
if params['fastd']['enabled']:
|
|
conditions.append(dataframe['fastd'] < params['fastd']['value'])
|
|
if params['adx']['enabled']:
|
|
conditions.append(dataframe['adx'] > params['adx']['value'])
|
|
if params['cci']['enabled']:
|
|
conditions.append(dataframe['cci'] < params['cci']['value'])
|
|
if params['rsi']['enabled']:
|
|
conditions.append(dataframe['rsi'] < params['rsi']['value'])
|
|
if params['over_sar']['enabled']:
|
|
conditions.append(dataframe['close'] > dataframe['sar'])
|
|
if params['uptrend_sma']['enabled']:
|
|
prevsma = dataframe['sma'].shift(1)
|
|
conditions.append(dataframe['sma'] > prevsma)
|
|
|
|
prev_fastd = dataframe['fastd'].shift(1)
|
|
# TRIGGERS
|
|
triggers = {
|
|
'lower_bb': dataframe['tema'] <= dataframe['blower'],
|
|
'faststoch10': (dataframe['fastd'] >= 10) & (prev_fastd < 10),
|
|
'ao_cross_zero': (crossed_above(dataframe['ao'], 0.0)),
|
|
'ema5_cross_ema10': (crossed_above(dataframe['ema5'], dataframe['ema10'])),
|
|
'macd_cross_signal': (crossed_above(dataframe['macd'], dataframe['macdsignal'])),
|
|
}
|
|
conditions.append(triggers.get(params['trigger']['type']))
|
|
|
|
dataframe.loc[
|
|
reduce(lambda x, y: x & y, conditions),
|
|
'buy'] = 1
|
|
dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
|
|
|
|
return dataframe
|
|
return populate_buy_trend
|
|
|
|
|
|
@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
|
|
def test_hyperopt(conf, pairs, mocker):
|
|
mocked_buy_trend = mocker.patch('freqtrade.analyze.populate_buy_trend')
|
|
|
|
def optimizer(params):
|
|
mocked_buy_trend.side_effect = buy_strategy_generator(params)
|
|
|
|
results = backtest(conf, pairs, mocker)
|
|
|
|
result = format_results(results)
|
|
print(result)
|
|
|
|
total_profit = results.profit.sum() * 1000
|
|
trade_count = len(results.index)
|
|
|
|
trade_loss = 1 - 0.8 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5)
|
|
profit_loss = exp(-total_profit**3 / 10**11)
|
|
|
|
return {
|
|
'loss': trade_loss + profit_loss,
|
|
'status': STATUS_OK,
|
|
'result': result
|
|
}
|
|
|
|
space = {
|
|
'mfi': hp.choice('mfi', [
|
|
{'enabled': False},
|
|
{'enabled': True, 'value': hp.uniform('mfi-value', 5, 15)}
|
|
]),
|
|
'fastd': hp.choice('fastd', [
|
|
{'enabled': False},
|
|
{'enabled': True, 'value': hp.uniform('fastd-value', 5, 40)}
|
|
]),
|
|
'adx': hp.choice('adx', [
|
|
{'enabled': False},
|
|
{'enabled': True, 'value': hp.uniform('adx-value', 10, 30)}
|
|
]),
|
|
'cci': hp.choice('cci', [
|
|
{'enabled': False},
|
|
{'enabled': True, 'value': hp.uniform('cci-value', -150, -100)}
|
|
]),
|
|
'rsi': hp.choice('rsi', [
|
|
{'enabled': False},
|
|
{'enabled': True, 'value': hp.uniform('rsi-value', 20, 30)}
|
|
]),
|
|
'uptrend_long_ema': hp.choice('uptrend_long_ema', [
|
|
{'enabled': False},
|
|
{'enabled': True}
|
|
]),
|
|
'over_sar': hp.choice('over_sar', [
|
|
{'enabled': False},
|
|
{'enabled': True}
|
|
]),
|
|
'uptrend_sma': hp.choice('uptrend_sma', [
|
|
{'enabled': False},
|
|
{'enabled': True}
|
|
]),
|
|
'trigger': hp.choice('trigger', [
|
|
{'type': 'lower_bb'},
|
|
{'type': 'faststoch10'},
|
|
{'type': 'ao_cross_zero'},
|
|
{'type': 'ema5_cross_ema10'},
|
|
{'type': 'macd_cross_signal'},
|
|
]),
|
|
}
|
|
trials = Trials()
|
|
best = fmin(fn=optimizer, space=space, algo=tpe.suggest, max_evals=4, trials=trials)
|
|
print('\n\n\n\n====================== HYPEROPT BACKTESTING REPORT ================================')
|
|
print('Best parameters {}'.format(best))
|
|
newlist = sorted(trials.results, key=itemgetter('loss'))
|
|
print('Result: {}'.format(newlist[0]['result']))
|