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()
