305 lines
9.3 KiB
Cython
305 lines
9.3 KiB
Cython
import sys, time, random, os
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# load strategy
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# from strategies.indicator import StrategyIndicator
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from backtesting import Backtest
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# load functions
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from indicator_util import get_indicators_values
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from signal_helper import *
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# Exchange API
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import pybithumb
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from itertools import combinations
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from datetime import datetime
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from trade.candle import CandlePatterns
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import warnings
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# from threading import Thread
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from time import sleep
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from strategy import StrategyCandlePattern
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from multiprocessing import Process, freeze_support
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from multiprocessing import Pool
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import multiprocessing
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import psutil
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warnings.filterwarnings(action='ignore')
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# set config
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start_time = time.time()
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cash = 1000
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commission = .005
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top_cash = 0
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top_profit = 25
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top_win_rate = 60
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best_pattern_arr = []
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# pivonachi
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profit_arr = [0] + pivo(100)
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loss_arr = [0] + pivo(10)
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# 시그널 보조 지표
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base_indicators = [
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{'RSI_DIV': 14},
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{'MFI_DIV': 14},
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{'CMO_DIV': 9},
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{'CCI_DIV': 20},
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{'WILLR_DIV': 28},
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{'RSI': 14},
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{'BBANDS': [20, 2]},
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{'BBANDS': [34, 2]},
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{'CCI': 14},
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{'AROON': 14},
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{'SAR': [0.00252, 0.22]},
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{'AROONOSC': 14},
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{'BOP': 14},
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{'CCI': 20},
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{'MFI': 14},
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{'MOM': 10},
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{'MOM': 14},
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{'ROC': 9},
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{'ROC': 14},
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{'WILLR': 14},
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]
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# 시그널 주도 지표(필터링될 지표)
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signal_indicators = [
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{'STOCH_DIV': [14, 3, 3]},
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{'STOCH_DIV': [14, 1, 1]},
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# {'STOCH_DIV': [20, 12, 12]},
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{'STOCHRSI_DIV': [14, 14, 3]},
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{'CMO_DIV': 14},
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{'CCI_DIV': 14},
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{'ADX_DIV': 14},
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{'BOP_DIV': 0},
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{'OBV_DIV': 0},
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{'MOM_DIV': 10},
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{'ROC_DIV': 14},
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{'ROC_DIV': 9},
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{'STOCH_DIV': [14, 3, 14]},
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{'STOCH_DIV': [14, 3, 5]},
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{'ADOSC_DIV': [3, 10]},
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{'ULTOSC_DIV': [7, 14, 28]},
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{'TRIX': [14, 9]},
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{'STOCH': [20, 12, 12]},
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{'STOCH': [14, 3, 14]},
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{'STOCH': [14, 3, 5]},
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{'DMI': 14},
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{'DI': 21},
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{'APO': [10, 20]},
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{'MACD': [12, 26, 9]},
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{'MACDFIX': 26},
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{'MACDFIX': 9},
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{'MACDFIX': 14},
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{'MACDFIX': 31},
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{'PPO': [12, 26, 9]},
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{'STOCHF': [14, 3]},
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{'STOCHRSI': [14, 14, 3]},
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{'ULTOSC': [7, 14, 28]},
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{'EMA': 30},
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{'EMA': 55},
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{'DEMA': 55},
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{'DEMA': 100},
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{'DEMA': 200},
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{'MA': 21},
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{'MA': 55},
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{'MA': 100},
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{'MAMA': [0.5, 0.05]},
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{'T3': [100, 10]},
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{'TRIMA': 30},
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{'TRIMA': 50},
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{'WMA': 30},
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{'WMA': 20},
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]
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# for test
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# base_indicators = [{'RSI': 14}, {'BBANDS': [34, 2]}, {'CCI': 20}, {'MFI': 14}, {'MOM': 14}]
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# signal_indicators = [{'STOCH_DIV': [14, 3, 3]}, {'ROC_DIV': 14}, {'STOCH_DIV': [14, 3, 5]}]
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# multi Treading - item
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def simulrating_by_item(item, data, all_indicators, idx, t_time):
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# def simulrating_by_item(data):
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global top_profit
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global top_win_rate
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global start_time
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global cash
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global commission
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for indicators in list(combinations(all_indicators, idx)):
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for profit in profit_arr:
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for loss in loss_arr:
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StrategyCandlePattern.use_indicators = list(indicators)
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StrategyCandlePattern.up_target = float(profit)
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StrategyCandlePattern.down_target = float(loss)
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bt = Backtest(data, StrategyCandlePattern, cash=cash, commission=commission)
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bt.run()
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# 수익 및 거래 수 제한
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if bt._results['Return [%]'] > top_profit and bt._results['# Trades'] > 5:
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print('-' * 60)
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print('시간봉 :', t_time)
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print('지표 조합 개수 :', idx)
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print('지표 :', StrategyCandlePattern.use_indicators)
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print("적용된 스탑프로핏 : %0.2f%%" % profit)
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print("적용된 스탑로스 : %0.2f%%" % loss)
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print("총 수익률 : %0.2f%%" % bt._results['Return [%]'])
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print("최종 금액 : %0.2f" % bt._results['Equity Final [$]'])
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print("거래 수 :", bt._results['# Trades'])
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print("파일명 :", str(item)+'_'+str(t_time)+'_'+str(idx)+'_'+str(time.time()))
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print('-' * 60)
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# bt.plot(filename=str(item)+'_'+str(t_time)+'_'+str(idx)+'_'+str(time.time()))
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top_profit = bt._results['Return [%]']
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best_pattern_arr.append({
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't_time': t_time,
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'indicators': indicators,
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'profit': profit,
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'loss': loss,
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'return': bt._results['Return [%]'],
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'trades': bt._results['# Trades'],
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})
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del bt
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e = int(time.time() - start_time)
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print('(완료) 조합 지표 개수 :', idx, t_time, '{:02d}:{:02d}:{:02d}'.format(e // 3600, (e % 3600 // 60), e % 60))
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print(datetime.now())
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# multi Treading - fackage
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def simulrating_by_item_fackage(item, data, t_time):
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global top_profit
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global top_win_rate
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global start_time
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global base_indicators
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global signal_indicators
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global cash
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global commission
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filtered_signal_indicators = []
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for indicator in signal_indicators:
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for profit in profit_arr:
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for loss in loss_arr:
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StrategyCandlePattern.use_indicators = [indicator]
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StrategyCandlePattern.up_target = float(profit)
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StrategyCandlePattern.down_target = float(loss)
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bt = Backtest(data, StrategyCandlePattern, cash=cash, commission=commission)
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bt.run()
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# 수익 및 거래 수 제한
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if bt._results['Return [%]'] > 15 and bt._results['# Trades'] > 5:
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if indicator not in filtered_signal_indicators:
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filtered_signal_indicators.append(indicator)
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if bt._results['Return [%]'] > top_profit:
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print('-' * 60)
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print('시간봉 :', t_time)
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print('지표 조합 개수 :', 1)
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print('지표 :', StrategyCandlePattern.use_indicators)
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print("적용된 스탑프로핏 : %0.2f%%" % profit)
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print("적용된 스탑로스 : %0.2f%%" % loss)
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print("총 수익률 : %0.2f%%" % bt._results['Return [%]'])
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print("최종 금액 : %0.2f" % bt._results['Equity Final [$]'])
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print("거래 수 :", bt._results['# Trades'])
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print('-' * 60)
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# bt.plot()
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top_profit = bt._results['Return [%]']
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best_pattern_arr.append({
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't_time': t_time,
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'indicators': [indicator],
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'profit': profit,
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'loss': loss,
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'return': bt._results['Return [%]'],
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'trades': bt._results['# Trades'],
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})
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del bt
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e = int(time.time() - start_time)
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print('시그널 지표 필터링 완료 :', '{:02d}:{:02d}:{:02d}'.format(e // 3600, (e % 3600 // 60), e % 60))
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print('지표 총합 :', len(filtered_signal_indicators) + len(base_indicators))
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print('필터 지표 리스트', filtered_signal_indicators)
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all_indicators = filtered_signal_indicators[::-1] + base_indicators
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joined = []
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for idx in range(2, 5):
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# simulrating_by_item(item, data, all_indicators, idx, t_time)
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# item_thread = Thread(target=simulrating_by_item, args=(item, data, all_indicators, idx, t_time,))
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# item_thread.start()
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# with multiprocessing.Pool(processes=psutil.cpu_count(logical=False)) as pool:
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# pool = Pool(processes=4)
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# func = simulrating_by_item(item, data, all_indicators, idx, t_time)
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# pool.map(func)
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_p = Process(target=simulrating_by_item, args=(item, data, all_indicators, idx, t_time,))
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# _p.daemon = True
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_p.start()
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joined.append(_p)
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for _p in joined:
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_p.join()
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del item, data, all_indicators, idx, t_time
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# multi Treading - time
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def simulrating_by_time(item, t_time):
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'''
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"day": "24H",
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"hour12": "12H",
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"hour6": "06H",
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"hour": "01H",
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"minute30": "30M",
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"minute10": "10M",
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"minute5": "05M",
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"minute3": "03M",
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'''
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df = pybithumb.get_ohlcv(item, t_time) # params : 종목, 시간
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# 최근 두달 데이터 = 실질
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if t_time == 'hour':
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df = df[-1600:]
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elif t_time == 'hour6':
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df = df[-266:] # 최근 두달 데이터 = 실질
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elif t_time == 'hour12':
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df = df[-133:] # 최근 두달 데이터 = 실질
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elif t_time == 'day':
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df = df[-85:] # 최근 두달 데이터 = 실질
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data_columns_init(df)
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data = df
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simulrating_by_item_fackage(item, data, t_time)
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def start_backtest():
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print('Started Simulating.')
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for t_time in ['hour', 'hour6', 'hour12']:
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simulrating_by_time('BTC', t_time)
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break
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# p = Process(target=simulrating_by_time, args=('BTC', t_time,))
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# p.start()
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# p.join() # sync
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# thread = Thread(target=simulrating_by_time, args=('BTC', t_time,))
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# thread.start()
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# thread.join() # 동기
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print('Ended Simulating.')
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if __name__ == '__main__':
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freeze_support()
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start_backtest()
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