def test_simple(self): cerebro = Cerebro() cerebro.addstrategy(TestStrategy) # 'apiKey' and 'secret' are skipped config = { 'enableRateLimit': True, 'nonce': lambda: str(int(time.time() * 1000)) } feed = CCXTFeed( exchange='binance', dataname='BNB/USDT', # valid values are: # ticks, microseconds, seconds, minutes, daily, weekly, monthly timeframe=TimeFrame.Minutes, fromdate=dt.datetime(2019, 1, 28, 3, 30), todate=dt.datetime(2019, 1, 28, 10, 00), compression=15, ohlcv_limit=2, # required to make calls to binance exchange work currency='BNB', config=config, retries=5, # drop_newest=True, # historical=False, debug=True, ) # Add the feed cerebro.adddata(feed) # Run the strategy cerebro.run()
def test_std_backtest(cerebro: bt.Cerebro): cerebro.addstrategy(bt.strategies.MA_CrossOver) cerebro.run() s = backtrader_plotting.schemes.Blackly() b = Bokeh(style='bar', scheme=s, output_mode=_output_mode) figs = cerebro.plot(b) assert len(figs) == 1 assert_num_tabs(figs, 3) assert_num_figures(figs, 4)
def test_backtest_2strats(cerebro: bt.Cerebro): cerebro.addstrategy(bt.strategies.MA_CrossOver) cerebro.addstrategy(ToggleStrategy) cerebro.run() b = Bokeh(style='bar', output_mode=_output_mode) figs = cerebro.plot(b) assert len(figs) == 2 assert_num_tabs(figs, 3, 3) assert_num_figures(figs, 4, 3)
def run(symbol, prices, strategy): # initialize the Cerebro engine cerebro = Cerebro() cerebro.broker.setcash(100000) # add OHLC data feed feed = bt.feeds.PandasData(dataname=prices) cerebro.adddata(feed) cerebro.addstrategy(strategy=strategy, ticker=symbol) cerebro.run()
def test_ordered_optimize(cerebro: bt.Cerebro): cerebro.optstrategy(bt.strategies.MA_CrossOver, slow=[20], fast=[5, 10, 20]) res = cerebro.run(optreturn=True) def df(optresults): a = [x.analyzers.tradeanalyzer.get_analysis() for x in optresults] return sum([x.pnl.gross.total if 'pnl' in x else 0 for x in a]) usercolumns = { 'Profit & Loss': df, } b = Bokeh(style='bar', output_mode=_output_mode) browser = OptBrowser(b, res, usercolumns=usercolumns, sortcolumn='Profit & Loss') model = browser.build_optresult_model() # browser.start() def count_children(obj): numo = 1 if hasattr(obj, "children"): numo = count_children(obj.children) if hasattr(obj, '__len__'): numo += len(obj) return numo num = count_children(model) assert num == 3
def test_optimize_no_optreturn(cerebro_no_optreturn: bt.Cerebro): cerebro_no_optreturn.optstrategy(bt.strategies.MA_CrossOver, slow=[5, 10, 20], fast=[5, 10, 20]) res = cerebro_no_optreturn.run() s = backtrader_plotting.schemes.Blackly() b = Bokeh(style='bar', output_mode=_output_mode, scheme=s) browser = OptBrowser(b, res) model = browser.build_optresult_model() #browser.start() def count_children(obj): numo = 1 if hasattr(obj, "children"): numo = count_children(obj.children) if hasattr(obj, '__len__'): numo += len(obj) return numo num = count_children(model) assert num == 3
def test_std_backtest_ind_on_line(cerebro: bt.Cerebro): '''In the past it crashed when creating indicators with specific lines case LineSeriesStub was not handled correctly''' class TestStrategy(bt.Strategy): def __init__(self): self._sma = bt.indicators.SMA(self.data.close) cerebro.addstrategy(TestStrategy) cerebro.run() s = backtrader_plotting.schemes.Blackly() b = Bokeh(style='bar', scheme=s, output_mode=_output_mode) figs = cerebro.plot(b) assert len(figs) == 1 assert_num_tabs(figs, 3) assert_num_figures(figs, 3)
def test_std_backtest_ind_subplot(cerebro: bt.Cerebro): cerebro.addstrategy(bt.strategies.MA_CrossOver) cerebro.run() plotconfig = { '#:i-0': { 'subplot': True, } } s = backtrader_plotting.schemes.Blackly() b = Bokeh(style='bar', scheme=s, output_mode=_output_mode, plotconfig=plotconfig) figs = cerebro.plot(b) assert_num_tabs(figs, 3) assert_num_figures(figs, 5)
def test_optimize_2strat(cerebro: bt.Cerebro): cerebro.optstrategy(bt.strategies.MA_CrossOver, slow=[5, 10, 20], fast=[5, 10, 20]) cerebro.optstrategy(ToggleStrategy, modbuy=[12, 15], modsell=[17, 19]) res = cerebro.run() b = Bokeh(style='bar', output_mode=_output_mode) browser = OptBrowser(b, res) with pytest.raises(RuntimeError): browser.build_optresult_model()
def run_bt_multiple(): cerebro = Cerebro() df = get_pickle('tiingo', 'SPY') data = PandasData(dataname=df) cerebro.adddata(data) cerebro.addanalyzer(Returns) cerebro.optstrategy(StrategyFetcher, idx=[0, 1]) results = cerebro.run() strats = [x[0] for x in results] for i, strat in enumerate(strats): rets = strat.analyzers.returns.get_analysis() print('Strategy {} Name {}:\n - analyzer: {}\n'.format( i, strat.__class__.__name__, rets))
def test_std_backtest_2datas(cerebro: bt.Cerebro): datapath = getdatadir('nvda-1999-2014.txt') data = bt.feeds.YahooFinanceCSVData( dataname=datapath, fromdate=datetime.datetime(1998, 1, 1), todate=datetime.datetime(2000, 12, 31), reverse=False, swapcloses=True, ) cerebro.adddata(data) cerebro.addstrategy(bt.strategies.MA_CrossOver) cerebro.run() s = backtrader_plotting.schemes.Blackly() b = Bokeh(style='bar', scheme=s, output_mode=_output_mode, merge_data_hovers=True) figs = cerebro.plot(b) assert len(figs) == 1 assert_num_tabs(figs, 3) assert_num_figures(figs, 5)
def backtesting(config): cerebro = Cerebro() cerebro.addstrategy(TestStrategy) cerebro.adddata(CCXTFeed(exchange='binance', dataname='BNB/USDT', timeframe=TimeFrame.Minutes, fromdate=datetime(2019, 1, 1, 0, 0), todate=datetime(2019, 1, 1, 0, 2), compression=1, ohlcv_limit=2, currency='BNB', config=config, retries=5)) finished_strategies = cerebro.run() return finished_strategies
def test_optimize(cerebro: bt.Cerebro): cerebro.optstrategy(bt.strategies.MA_CrossOver, slow=[5, 10, 20], fast=[5, 10, 20]) res = cerebro.run(optreturn=True) b = Bokeh(style='bar', output_mode=_output_mode) browser = OptBrowser(b, res) model = browser.build_optresult_model() # browser.start() def count_children(obj): numo = 1 if hasattr(obj, "children"): numo = count_children(obj.children) if hasattr(obj, '__len__'): numo += len(obj) return numo num = count_children(model) assert num == 3
import os, sys, argparse import pandas import backtrader from backtrader import Cerebro from strategies.BuyAndHold import BuyAndHold from strategies.GoldenCross import GoldenCross cerebro = backtrader.Cerebro() pricesData = pandas.read_csv('SPY.csv', index_col='Date', parse_dates=True) # initializing Cerebro cerebro = Cerebro() cerebro.broker.setcash(100000) feed = backtrader.feeds.PandasData(dataname=pricesData) # add data feed cerebro.adddata(feed) strategies = {"golden_cross": GoldenCross, "buy_hold": BuyAndHold} parser = argparse.ArgumentParser() # parse command line arguments parser.add_argument("strategy", help="Which strategy to run", type=str) args = parser.parse_args() if not args.strategy in strategies: print("Invalid strategy, must select one of {}".format(strategies.keys())) sys.exit() cerebro.addstrategy(strategy=strategies[args.strategy]) cerebro.run() cerebro.plot() # plot the chart
start_date = datetime.datetime(2020, 3, 26) # start_date = datetime.datetime(2016, 4, 1) end_date = datetime.datetime(2021, 1, 27) feed = bt.feeds.YahooFinanceData( dataname=sel_stock[0], # Do not pass values before this date fromdate=start_date, # Do not pass values after this date todate=end_date, reverse=False) cerebro.adddata(feed) print(f'Stock = {sel_stock[0]}, strategy = {strat}, start={start_date}') results = cerebro.run() if strat in ['bbands1', 'bbands2']: for i, strat_result in enumerate(results): if strat_result.params.BuyLast: buy_or_sell += "BUY " else: buy_or_sell += "SELL " print(buy_or_sell) # print(strat_result.params.LastTransaction) # print("strat_parameters - {}: {}".format(i, strat_result.params)) # cerebro.strategy.set_sma(opt_slow, opt_fast) # print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) # print('Final Cash Value: %.2f' % cerebro.broker.get_cash())
logging.basicConfig(level=getattr(logging, args.loglevel)) # Create a cerebro entity cerebro = Cerebro() # Set our desired cash start cerebro.broker.setcash(100000.0) # Set our sizer cerebro.addsizer(PercentSizer, percents=90) # Load the Kraken data pair = args.long + args.short datafeed = KrakenData(dataname=pair, timeframe=getattr(TimeFrame, args.timeframe), compression=args.compression, refresh_period=args.refresh, historical=args.historical, backfill_start=not args.no_backfill) cerebro.adddata(datafeed) # Add the strategies to run cerebro.addstrategy(TestStrategy) # Run the backtest result = cerebro.run() # Plot the result if args.plot: cerebro.plot()
from backtrader import Cerebro, TimeFrame from BackTraderQuik.QKStore import QKStore # Хранилище QUIK import Strategy as ts # Торговые системы if __name__ == '__main__': # Точка входа при запуске этого скрипта cerebro = Cerebro() # Инициируем "движок" BackTrader # Склейка фьючерсов (Rollover) symbols = ['SPBFUT.SiH9', 'SPBFUT.SiM9', 'SPBFUT.SiU9', 'SPBFUT.SiZ9', 'SPBFUT.SiH0', 'SPBFUT.SiM0', 'SPBFUT.SiU0', 'SPBFUT.SiZ0', 'SPBFUT.SiH1', 'SPBFUT.SiM1', 'SPBFUT.SiU1', 'SPBFUT.SiZ1'] # Тикеры для склейки store = QKStore() # Хранилище QUIK (QUIK на локальном компьютере) # store = QKStore(Host='<Ваш IP адрес>') # Хранилище QUIK (К QUIK на удаленном компьютере обращаемся по IP или названию) data = [store.getdata(dataname=symbol, timeframe=TimeFrame.Minutes, compression=5) for symbol in symbols] # Получаем по ним исторические данные cerebro.rolloverdata(name='Si', *data, checkdate=True, checkcondition=True) # Склеенный тикер cerebro.addstrategy(ts.PrintStatusAndBars) # Добавляем торговую систему cerebro.run() # Запуск торговой системы cerebro.plot() # Рисуем график. Требуется matplotlib версии 3.2.2 (pip install matplotlib==3.2.2)
"moving_avg": MovingAverage, "sar": Sar, "adx_macd": AdxMacd } #check against - golden_cross, buy_hold, macd, moving_avg, sar strategy = "sar" if strategy == "golden_cross_opt": cerebro.optstrategy( GoldenCross, fast=range(40, 60, 10), slow=range(160, 220, 20), #fast=range(10, 30, 10), slow=range(50, 90, 20), ) cerebro.run(maxcpus=1) GoldenCross.show_max() elif strategy == "macd_opt": strats = cerebro.optstrategy( MacdStrat, fast=range(8, 16, 1), slow=range(16, 32, 2), ) cerebro.run(maxcpus=1) best_fast, best_slow, best_roi = MacdStrat.show_max() print('Best params: fast={}, slow={}, roi={}'.format( best_fast, best_slow, best_roi)) """ elif strategy == "macd": cerebro.addstrategy(strategy=strategies[strategy],fast=15, slow=30) cerebro.run()