3. Multiple Data Feeds (Instruments) on a single strategy
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Multiple Data Feeds (Instruments) on a single strategy

  • S

    Hi All

    I am new to Back trader and I am in need of your help to test my strategy on multiple instrument data.
    I have pasted the code below, I am expecting the strategy to run for both the data feeds, but actually its running for only one data feed. Please let me know what I should be changing to make it run for both the instrument data feeds. Thanks in advance

    -- Satheesh Kumar

    from future import (absolute_import, division, print_function,
    unicode_literals)

    import argparse
    import backtrader as bt
    import backtrader.feeds as btfeeds
    import datetime as dt
    import pandas as p

    class TestStrategy(bt.Strategy):
    params = (
    ('smaPeriod', 10),
    )

    def __init__(self):
    
    #Retrieves Close price data from the object
    self.dataclose = self.data.close
    
    #To keep track of pending orders and buy price / commission.
    self.order = None
    self.buyprice = None
    self.commission = None
    
    #SMA Indicator
    self.sma = bt.indicators.MovingAverageSimple(self.data, period=self.params.smaPeriod)

    # Indicators for the plotting show
    bt.indicators.ExponentialMovingAverage(self.data, period=25)
    bt.indicators.WeightedMovingAverage(self.data, period=25).subplot = True
    bt.indicators.StochasticSlow(self.data)
    bt.indicators.MACDHisto(self.data)
    rsi = bt.indicators.RSI(self.data)
    bt.indicators.SmoothedMovingAverage(rsi, period=10)
    bt.indicators.ATR(self.data).plot = False
    
    
def notify_order(self, order):

    #Check whether an order is Submitted or Accepted by the Broker
    if order.status in [order.Submitted, order.Accepted]:
        return

    #Check if an order is completed
    if order.status in [order.Completed]:
        if order.isbuy():

            print('Buy Executed Price: %.2f, Cost : %.2f, Commission : %.2f' % 
                  (order.executed.price,
                   order.executed.value,
                   order.executed.comm
                  ))

            self.buyprice = order.executed.price
            self.commission = order.executed.comm


        elif order.issell():
            print('Sell Executed Price: %.2f, Cost : %.2f, Commission : %.2f' % 
                  (order.executed.price,
                   order.executed.value, #for sell this is not working as expected
                   order.executed.comm
                  ))

        self.bar_executed = len(self)

    elif order.status in [order.Canceled, order.Margin, order.Rejected]:
        print('Order Canceled/Margin/Rejected')
        
    
    self.order = None
    
def notify_trade(self, trade):
        if not trade.isclosed:
            return

        print('OPERATION PROFIT, GROSS %.2f, NET %.2f' %
             (trade.pnl, trade.pnlcomm))

    
def next(self): 
   
    print('Date, %s, Close, %.2f' % (self.data.datetime.date(0), self.dataclose[0]))

    #Check if an order is in Pending state, if yes, we cannot send a 2nd one
    if self.order:

        print('An order already in Pending state')
        return

    #Check whether we have an open position already, if no, then we can enter a new position by entering a BUY trade
    if not self.position:

        if self.dataclose[0] > self.sma[0]:
            print('BUY Signal:, %.2f' % self.dataclose[0])
            self.order = self.buy()
  
    #if there is an existing position already, then we have to close it after 5 consecutive bars 
    else:
        if self.dataclose[0] < self.sma[0]:
            print('Sell Signal:, %.2f' % self.dataclose[0])
            self.order = self.sell()

    if name == 'main':

    cerebro = bt.Cerebro() 
cerebro.addstrategy(TestStrategy) #Adds the strategy

orcl = p.read_csv('D:\Algoticks\Excercises\Data\orcl_price-history-05-21-2018.csv')
orcl['datetime'] = orcl['datetime'].astype('datetime64[ns]')

orcl_stg = bt.feeds.PandasData(dataname = orcl)

hcl = p.read_csv('D:\Algoticks\Excercises\Data\hcl_price-history-05-21-2018.csv')
hcl['datetime'] = hcl['datetime'].astype('datetime64[ns]')

hcl_stg = bt.feeds.PandasData(dataname = hcl)

cerebro.adddata(orcl_stg)   #Adds the data for the strategy
cerebro.adddata(hcl_stg)

#set the cash
cerebro.broker.setcash(100000.0)
#set broker commission
cerebro.broker.setcommission(commission = 0.001) #.1 percentage
#set the quantity
cerebro.addsizer(bt.sizers.FixedSize, stake = 10)

#cerebro.addwriter(bt.WriterFile, csv=True)

print('Starting Portfolio Value : %.2f' % cerebro.broker.getvalue())
cerebro.run()
#data.head()
print('Final Portfolio Value : %.2f' % cerebro.broker.getvalue())
    0
  • S

    Hi All

    Please ignore the previous code and please look at this code block. Sorry for the mistake

    from future import (absolute_import, division, print_function,
    unicode_literals)

    import argparse

    import backtrader as bt
    import backtrader.feeds as btfeeds
    import datetime as dt

    import pandas as p

    class TestStrategy(bt.Strategy):
    params = (
    ('smaPeriod', 10),
    )

    def __init__(self):
    
    #Retrieves Close price data from the object
    #self.dataclose = self.data.close
    
    #To keep track of pending orders and buy price / commission.
    self.order = None
    self.buyprice = None
    self.commission = None
    

    
def notify_order(self, order):

    #Check whether an order is Submitted or Accepted by the Broker
    if order.status in [order.Submitted, order.Accepted]:
        return

    #Check if an order is completed
    if order.status in [order.Completed]:
        if order.isbuy():

            print('Buy Executed Price: %.2f, Cost : %.2f, Commission : %.2f' % 
                  (order.executed.price,
                   order.executed.value,
                   order.executed.comm
                  ))

            self.buyprice = order.executed.price
            self.commission = order.executed.comm


        elif order.issell():
            print('Sell Executed Price: %.2f, Cost : %.2f, Commission : %.2f' % 
                  (order.executed.price,
                   order.executed.value, #for sell this is not working as expected
                   order.executed.comm
                  ))

        self.bar_executed = len(self)

    elif order.status in [order.Canceled, order.Margin, order.Rejected]:
        print('Order Canceled/Margin/Rejected')
        
    
    self.order = None
    
def notify_trade(self, trade):
        if not trade.isclosed:
            return

        print('OPERATION PROFIT, GROSS %.2f, NET %.2f' %
             (trade.pnl, trade.pnlcomm))

    
def next(self): 
   
    

    for datafeed in self.getdatanames():
        print('Date, %s, Close, %.2f' % (self.getdatabyname(datafeed).datetime.date(0), self.getdatabyname(datafeed).close[0]))
        #Check if an order is in Pending state, if yes, we cannot send a 2nd one
        if self.order:

            print('An order already in Pending state')
            return

    #Check whether we have an open position already, if no, then we can enter a new position by entering a BUY trade
        if not self.position:

            if self.getdatabyname(datafeed).close[0] < self.getdatabyname(datafeed).close[-1]:

                if self.getdatabyname(datafeed).close[-1] < self.getdatabyname(datafeed).close[-2]:
                    
                    print('BUY Signal:, %.2f' % self.getdatabyname(datafeed).close[0])
                    self.order = self.buy()
        
        elif self.position:

             if len(self) >= (self.bar_executed + 4):

                print('Sell Signal:, %.2f' % self.getdatabyname(datafeed).close[0])
                self.order = self.sell()

    if name == 'main':

    cerebro = bt.Cerebro() 
cerebro.addstrategy(TestStrategy) #Adds the strategy

orcl = p.read_csv('D:\Algoticks\Excercises\Data\orcl_price-history-05-21-2018.csv')
orcl['datetime'] = orcl['datetime'].astype('datetime64[ns]')

orcl_stg = bt.feeds.PandasData(dataname = orcl)

hcl = p.read_csv('D:\Algoticks\Excercises\Data\hcl_price-history-05-21-2018.csv')
hcl['datetime'] = hcl['datetime'].astype('datetime64[ns]')

hcl_stg = bt.feeds.PandasData(dataname = hcl)

cerebro.adddata(orcl_stg)   #Adds the data for the strategy
cerebro.adddata(hcl_stg)    

#set the cash
cerebro.broker.setcash(100000.0)
#set broker commission
cerebro.broker.setcommission(commission = 0.001) #.1 percentage
#set the quantity
cerebro.addsizer(bt.sizers.FixedSize, stake = 10)

#cerebro.addwriter(bt.WriterFile, csv=True)

print('Starting Portfolio Value : %.2f' % cerebro.broker.getvalue())
cerebro.run()
#data.head()
print('Final Portfolio Value : %.2f' % cerebro.broker.getvalue())
    0
    D
    B
     2 Replies
  • D

    @satheesh7134 Go through the multi data feeds example.

    You need to use enumerate(self.datas) to evaluate strategy on each data feed separately.

    0
    P
     1 Reply
  • P

    @divyanshu-bagga :
    In that case, wouldn't cerebro.run( ) execute twice? If I run twice then I would get two different datasets.

    What if, I want to execute this strategy on both data sets and generate single report as one single portfolio.

    0
  • B
    administrators

    @satheesh7134 said in Multiple Data Feeds (Instruments) on a single strategy:

                        print('BUY Signal:, %.2f' % self.getdatabyname(datafeed).close[0])
                    self.order = self.buy()

    He wasn't telling the system what to buy (or sell). See Docs - Strategy and the reference for buy / sell

    or as pointed out by @Divyanshu-Bagga

    @divyanshu-bagga said in Multiple Data Feeds (Instruments) on a single strategy:

    @satheesh7134 Go through the multi data feeds example.

    @param-jeet said in Multiple Data Feeds (Instruments) on a single strategy:

    In that case, wouldn't cerebro.run( ) execute twice? If I run twice then I would get two different datasets.
    What if, I want to execute this strategy on both data sets and generate single report as one single portfolio.

    You enumerate within the strategy.

    0
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