вторник, 22 мая 2018 г.

Backtrader: Multiple Data Feeds & Indicators

Backtrader: Multiple Data Feeds & Indicators
Multi Example

import backtrader as bt
from datetime import datetime

class BOLLStrat(bt.Strategy):

    This is a simple mean reversion bollinger band strategy.

    Entry Critria:
        - Long: Price crossing/close below the upper band
        - Short: Price crossing/close above the lower band
    Exit Critria
        - Long/Short: Price touching the median line

    params = (
        ("period", 20),
        ("devfactor", 2),
        ("size", 20),
        ("debug", False)

    def __init__(self):
        self.boll = bt.indicators.BollingerBands(period=self.p.period, devfactor=self.p.devfactor)
        #self.sx = bt.indicators.CrossDown(self.data.close, self.boll.lines.top)
        #self.lx = bt.indicators.CrossUp(self.data.close, self.boll.lines.bot)

    def next(self):

        orders = self.broker.get_orders_open()

        # Cancel open orders so we can track the median line
        if orders:
            for order in orders:

        if not self.position:
        #if True:

            if self.data.close > self.boll.lines.top:

                self.sell(exectype=bt.Order.Stop, price=self.boll.lines.top[0], size=self.p.size)

            if self.data.close < self.boll.lines.bot:
                self.buy(exectype=bt.Order.Stop, price=self.boll.lines.bot[0], size=self.p.size)


            if self.position.size > 0:
                self.sell(exectype=bt.Order.Limit, price=self.boll.lines.mid[0], size=self.p.size)
                #self.sell(exectype=bt.Order.Limit, price=self.boll.lines.top[0], size=self.p.size)

                self.buy(exectype=bt.Order.Limit, price=self.boll.lines.mid[0], size=self.p.size)
                #self.buy(exectype=bt.Order.Stop, price=self.boll.lines.bot[0], size=self.p.size)

        if self.p.debug:
            print('---------------------------- NEXT ----------------------------------')
            print("1: Data Name:                            {}".format(data._name))
            print("2: Bar Num:                              {}".format(len(data)))
            print("3: Current date:                         {}".format(data.datetime.datetime()))
            print('4: Open:                                 {}'.format(data.open[0]))
            print('5: High:                                 {}'.format(data.high[0]))
            print('6: Low:                                  {}'.format(data.low[0]))
            print('7: Close:                                {}'.format(data.close[0]))
            print('8: Volume:                               {}'.format(data.volume[0]))
            print('9: Position Size:                        {}'.format(self.position.size))

    def notify_trade(self,trade):
        if trade.isclosed:
            dt = self.data.datetime.date()

            print('---------------------------- TRADE ---------------------------------')
            print("1: Data Name:                            {}".format(trade.data._name))
            print("2: Bar Num:                              {}".format(len(trade.data)))
            print("3: Current date:                         {}".format(dt))
            print('4: Status:                               Trade Complete')
            print('5: Ref:                                  {}'.format(trade.ref))
            print('6: PnL:                                  {}'.format(round(trade.pnl,2)))

class OandaCSVData(bt.feeds.GenericCSVData):
    params = (
        ('nullvalue', float('NaN')),
        #('dtformat', '%Y-%m-%dT%H:%M:%S.%fZ'),
        ('dtformat', '%Y-%m-%d'),
        ('datetime', 1),
        ('time', -1),
        ('open', 2),
        ('high', 3),
        ('low', 4),
        ('close', 5),
        ('volume', 6),
        ('openinterest', 7),

#Variable for our starting cash
startcash = 100000

#Create an instance of cerebro
cerebro = bt.Cerebro()

#Add our strategy

#cerebro.addstrategy(BOLLStrat, oneplot=False)

#create our data list
datalist = [
    ('data.csv', 'BTCUSDT'), #[0] = Data file, [1] = Data name

#Loop through the list adding to cerebro.
for i in range(len(datalist)):
    data = OandaCSVData(dataname=datalist[i][0])
    cerebro.adddata(data, name=datalist[i][1])

# Set our desired cash start

# Run over everything

#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

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