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()
def connect_broker():
config = {
'urls': {
'api': 'https://api.sandbox.gemini.com'
},
'apiKey': 'XXXXX',
'secret': 'XXXXX',
'nonce': lambda: str(int(time.time() * 1000))
}
broker = bt.brokers.CCXTBroker(exchange='gemini',
currency='USD',
config=config)
cerebro.setbroker(broker)
# 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)
def connect_broker():
path = '/home/rick/PycharmProjects/Btc/huobittrade/binance.txt'
f = open(path, 'r')
all = f.readlines()
f.close()
apikey = all[0].strip()
skey = all[1].strip()
config = {'urls': {'api': 'https://api.binance.com/wapi/v3'},
'apiKey': apikey,
'secret': skey,
'nonce': lambda: str(int(time.time() * 1000))
}
broker = bt.brokers.CCXTBroker(exchange='binance',
currency='USD', config=config)
cerebro.setbroker(broker)
# Create data feeds
data_ticks = bt.feeds.CCXT(exchange='binance', symbol='BTC/USDT',
name="btc_usdt_tick",
timeframe=bt.TimeFrame.Ticks,
compression=1, config=config)
cerebro.adddata(data_ticks)
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')
#cerebro.addsizer(bt.sizers.FixedSize, stake=1)
#cerebro.addanalyzer(btanalyzers.AnnualReturn, _name='annual')
# Set the commission
cerebro.broker.setcommission(leverage=1, mult=lv_mult, commission=0.01)
tframes = dict(daily=bt.TimeFrame.Days,
weekly=bt.TimeFrame.Weeks,
monthly=bt.TimeFrame.Months)
data = None
data = bt.feeds.PandasData(dataname=p0,
fromdate=starttime,
todate=val,
timeframe=bt.TimeFrame.Minutes,
compression=knum)
# Add the Data Feed to Cerebro
cerebro.adddata(data)
cerebro.resampledata(data, timeframe=tframes["daily"], compression=1)
# Set our desired cash start
cerebro.broker.setcash(lv_cash)
# Run over everything
cerebro.addanalyzer(btanalyzers.SharpeRatio, _name='mysharpe')
cerebro.addanalyzer(btanalyzers.VWR,
_name='vwr',
timeframe=bt.TimeFrame.Years)
#cerebro.addanalyzer(btanalyzers.AnnualReturn, _name='annual')
cerebro.addanalyzer(btanalyzers.Returns,
_name='logreturn',
timeframe=bt.TimeFrame.Years)
cerebro.addanalyzer(btanalyzers.SQN, _name='SQN')
cerebro.addanalyzer(btanalyzers.TradeAnalyzer, _name='TradeAnalyzer')