def main():
cerebro = bt.Cerebro()
hist_start_date = datetime.utcnow() - timedelta(minutes=10)
data_min = bt.feeds.CCXT(exchange='binance', symbol="BTC/USDT", name="btc_usdt_min", fromdate=hist_start_date,
timeframe=bt.TimeFrame.Minutes)
cerebro.adddata(data_min)
cerebro.addstrategy(TestStrategy)
cerebro.run()
def connect_broker():
apikey = 'siX-NO9IeVWstmn1zA2e904N'
secret = 'ieEjNwz9TDAzg_B2EVkpgzkchDeNmyy9_UNB03B567Gwh0A_'
cerebro = bt.Cerebro(quicknotify=True)
# Add the strategy
cerebro.addstrategy(TestStrategy)
# Create our store
config = {'apiKey': apikey, 'secret': secret, 'enableRateLimit': True}
# IMPORTANT NOTE - Kraken (and some other exchanges) will not return any values
# for get cash or value if You have never held any LTC coins in your account.
# So switch LTC to a coin you have funded previously if you get errors
store = CCXTStore(exchange='bitmex',
currency='BTC',
config=config,
retries=5,
debug=False,
testnet=True)
print("I am here")
print(store.exchange.urls)
broker = store.getbroker()
cerebro.setbroker(broker)
# Get our data
# Drop newest will prevent us from loading partial data from incomplete candles
hist_start_date = datetime.utcnow() - timedelta(minutes=50)
data = store.getdata(dataname='BTC/USD',
name="BTCUSD",
timeframe=bt.TimeFrame.Minutes,
fromdate=hist_start_date,
compression=1,
ohlcv_limit=50,
drop_newest=True) #, historical=True)
# Add the feed
cerebro.adddata(data)
# Run the strategy
cerebro.run()
self.sell(size=100)
#Variable for our starting cash
startcash = 10000
if __name__ == '__main__':
cerebro = bt.Cerebro()
hist_start_date = datetime.utcnow() - timedelta(minutes=1000)
data_min = bt.feeds.CCXT(exchange='binance',
symbol="BTC/USDT",
name="btc_usd_min",
fromdate=hist_start_date,
todate=datetime.utcnow(),
timeframe=bt.TimeFrame.Minutes)
cerebro.adddata(data_min)
cerebro.broker.setcash(startcash)
cerebro.addstrategy(firstStrategy)
cerebro.run()
# Get final portfolio Value
portvalue = cerebro.broker.getvalue()
pnl = portvalue - startcash
# Print out the final result
print('Final Portfolio Value: ${}'.format(portvalue))
print('P/L: ${}'.format(pnl))
# Finally plot the end results
cerebro.plot(style='candlestick')
# Create data feeds
data_ticks = bt.feeds.CCXT(exchange='geminy',
symbol='BTC/USD',
name="btc_usd_tick",
timeframe=bt.TimeFrame.Ticks,
compression=1,
config=config)
cerebro.adddata(data_ticks)
class TestStrategy(bt.Strategy):
def next(self):
print('*' * 5, 'NEXT:', bt.num2date(self.data.datetime[0]),
self.data._name, self.data.open[0], self.data.high[0],
self.data.low[0], self.data.close[0], self.data.volume[0],
bt.TimeFrame.getname(self.data._timeframe), len(self.data))
if __name__ == '__main__':
cerebro = bt.Cerebro()
hist_start_date = datetime.utcnow() - timedelta(minutes=10)
data_min = bt.feeds.CCXT(exchange='bitmex',
symbol="BTC/USD",
name="btc_usd_min",
fromdate=hist_start_date,
timeframe=bt.TimeFrame.Minutes)
cerebro.adddata(data_min)
cerebro.addstrategy(TestStrategy)
cerebro.run()
df = ts.pro_bar(ts_code=code,
adj='qfq',
start_date=start_time,
end_date=end_time)
df.index = pd.to_datetime(df.trade_date)
df.sort_index(ascending=True, inplace=True)
df['volume'] = df['vol']
df['openinterest'] = 0
df = df[['open', 'high', 'low', 'close', 'volume', 'openinterest']]
return df
if __name__ == '__main__':
cerebro = bt.Cerebro()
cerebro.addstrategy(TestStrategy, maperiod5=5, maperiod30=30)
cerebro.broker.setcash(100000.0)
cerebro.broker.setcommission(commission=0.0005)
# Add a FixedSize sizer according to the stake
cerebro.addsizer(bt.sizers.FixedSize)
data = bt.feeds.PandasData(dataname=get_data('688158.SH'))
cerebro.adddata(data)
# 添加分析对象
cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name="sharpe")
cerebro.addanalyzer(bt.analyzers.AnnualReturn, _name="AR")
cerebro.addanalyzer(bt.analyzers.DrawDown, _name="DD")
cerebro.addanalyzer(bt.analyzers.Returns, _name="RE")
# if order.isbuy():
# self.log('BUY EXECUTED, %.2f' % order.executed.price)
# elif order.issell():
# self.log('SELL EXECUTED, %.2f' % order.executed.price)
#
# self.bar_executed = len(self)
# elif order.status in [order.Canceled, order.Margin, order.Rejected]:
# self.log('Order Canceled/Margin/Rejected')
# # Write down: no pending order
# self.order = None
def next(self):
self.log(f"{self.close[0]}-{self.plFound[0]},{self.phFound[0]}")
if __name__ == '__main__':
cerebro = bt.Cerebro()
# hist_start_data=datetime.utcnow()-timedelta(days=365)
# data_min=bt.feeds.CCXT(exchange='bitmex',symbol="BTC/USD",name="btc_usd_min",fromdate=hist_start_data,todate=datetime.utcnow(),timeframe=bt.TimeFrame.Days)
# cerebro.adddata(data_min)
modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
datapath = os.path.join(modpath, '.\hist_data\BINANCE_BTCUSDT.csv')
data = bt.feeds.BacktraderCSVData(dataname=datapath,
timeframe=bt.TimeFrame.Minutes)
cerebro.adddata(data)
cerebro.addstrategy(TrbStrategy)
cerebro.broker.setcash(10000)
cerebro.broker.setcommission(commission=0.001)
cerebro.run()
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
df['openinterest'] = 0
df = df[['open', 'high', 'low', 'close', 'volume', 'openinterest']]
return df
if __name__ == "__main__":
cerebro = bt.Cerebro()
st_number = '688158.SH'
df = get_data(st_number)
data = bt.feeds.PandasData(dataname=df)
cerebro.adddata(data)
cerebro.addstrategy(SMACross)
cerebro.addsizer(bt.sizers.AllInSizerInt)
cerebro.broker.set_cash(100000)
cerebro.addanalyzer(bt.analyzers.AnnualReturn, _name="annual_returns")
cerebro.addanalyzer(bt.analyzers.DrawDown, _name="draw_down")
cerebro.addanalyzer(bt.analyzers.Transactions, _name="transactions")
results = cerebro.run()
# 打印Analyzer结果到日志
for result in results:
annual_returns = result.analyzers.annual_returns.get_analysis()
log.info("annual returns:")
for year, ret in annual_returns.items():