Hi guys ,

I'm new here.

I discovered BACKTRADER and I'm struggling with PAIR TRADING even if I found out a GitHub repository where we have the full access...but It doesn't work.

Anyway , I tried to apply the code to my .csv files but I get this error :

Traceback (most recent call last):
File "PairTradingStrategy.py", line 174, in <module>
cerebro.run()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1127, in run
runstrat = self.runstrategies(iterstrat)
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1212, in runstrategies
data.preload()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 688, in preload
while self.load():
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 479, in load
_loadret = self._load()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 710, in _load
return self._loadline(linetokens)
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feeds/yahoo.py", line 134, in _loadline
h = float(linetokens[next(i)])
IndexError: list index out of range

and the code is as following :

import backtrader as bt
import backtrader.analyzers as btanalyzers
import backtrader.indicators as btind
import datetime

class PairTradingStrategy(bt.Strategy):
params = dict(
period=10,
stake=10,
qty1=0,
qty2=0,
printout=True,
upper=2.1,
lower=-2.1,
up_medium=0.5,
low_medium=-0.5,
status=0,
portfolio_value=10000,
)

def log(self, txt, dt=None):
    if self.p.printout:
        dt = dt or self.data.datetime[0]
        dt = bt.num2date(dt)
        print('%s, %s' % (dt.isoformat(), txt))

def __init__(self):
   # To control operation entries
    self.orderid = None
    self.qty1 = self.p.qty1
    self.qty2 = self.p.qty2
    self.upper_limit = self.p.upper
    self.lower_limit = self.p.lower
    self.up_medium = self.p.up_medium
    self.low_medium = self.p.low_medium
    self.status = self.p.status
    self.portfolio_value = self.p.portfolio_value

# Signals performed with PD.OLS :
    self.transform = btind.OLS_TransformationN(self.data1, self.data2,
                                               period=self.p.period)
    self.zscore = self.transform.zscore

    # Checking signals built with StatsModel.API :
    # self.ols_transfo = btind.OLS_Transformation(self.data1, self.data2,
    #                                             period=self.p.period,
    #                                             plot=True)

def next(self):
if self.orderid:
return # if an order is active, no new orders are allowed

    if self.p.printout:
        print('Self  len:', len(self))
        print('Data1 len:', len(self.data1))
        print('Data2 len:', len(self.data2))
        print('Data1 len == Data2 len:',
              len(self.data1) == len(self.data2))

        print('Data1 dt:', self.data1.datetime.datetime())
        print('Data2 dt:', self.data2.datetime.datetime())

    print('status is', self.status)
    print('zscore is', self.zscore[0])


    # Step 2: Check conditions for SHORT & place the order
    # Checking the condition for SHORT
    if (self.zscore[0] > self.upper_limit) and (self.status != 1):

        # Calculating the number of shares for each stock
        value = 0.5 * self.portfolio_value  # Divide the cash equally
        x = int(value / (self.data1.close))  # Find the number of shares for Stock1
        y = int(value / (self.data2.close))  # Find the number of shares for Stock2
        print('x + self.qty1 is', x + self.qty1)
        print('y + self.qty2 is', y + self.qty2)

        # Placing the order
        self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data1.close[0], x + self.qty1))
        self.sell(data=self.data1, size=(x + self.qty1))  # Place an order for buying y + qty2 shares
        self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("KO", self.data2.close[0], y + self.qty2))
        self.buy(data=self.data2, size=(y + self.qty2))  # Place an order for selling x + qty1 shares

        # Updating the counters with new value
        self.qty1 = x  # The new open position quantity for Stock1 is x shares
        self.qty2 = y  # The new open position quantity for Stock2 is y shares

        self.status = 1  # The current status is "short the spread"

        # Step 3: Check conditions for LONG & place the order
        # Checking the condition for LONG
    elif (self.zscore[0] < self.lower_limit) and (self.status != 2):

        # Calculating the number of shares for each stock
        value = 0.5 * self.portfolio_value  # Divide the cash equally
        x = int(value / (self.data1.close))  # Find the number of shares for Stock1
        y = int(value / (self.data2.close))  # Find the number of shares for Stock2
        print('x + self.qty1 is', x + self.qty1)
        print('y + self.qty2 is', y + self.qty2)

        # Place the order
        self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data1.close[0], x + self.qty1))
        self.buy(data=self.data1, size=(x + self.qty1))  # Place an order for buying x + qty1 shares
        self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AAME", self.data2.close[0], y + self.qty2))
        self.sell(data=self.data2, size=(y + self.qty2))  # Place an order for selling y + qty2 shares

        # Updating the counters with new value
        self.qty1 = x  # The new open position quantity for Stock1 is x shares
        self.qty2 = y  # The new open position quantity for Stock2 is y shares
        self.status = 2  # The current status is "long the spread"


        # Step 4: Check conditions for No Trade
        # If the z-score is within the two bounds, close all

    elif (self.zscore[0] < self.up_medium and self.zscore[0] > self.low_medium):
        self.log('CLOSE LONG %s, price = %.2f' % ("PEP", self.data1.close[0]))
        self.close(self.data1)
        self.log('CLOSE LONG %s, price = %.2f' % ("KO", self.data2.close[0]))
        self.close(self.data2)


def stop(self):
        print('==================================================')
        print('Starting Value - %.2f' % self.broker.startingcash)
        print('Ending   Value - %.2f' % self.broker.getvalue())
        print('==================================================')

#Instantiate Cerebro engine
cerebro = bt.Cerebro()

#Add data feed to Cerebro
data1 = bt.feeds.YahooFinanceCSVData(dataname='/Users/bibani/Desktop/AACQW.csv',
dtformat=('%Y.%m.%d'),
fromdate = datetime.datetime(2018,1,2),
todate = datetime.datetime(2021,1,15),
datetime=0,
time=-1,
high=-1,
low=-1,
open=-1,
close=1,
volume=-1,
openinterest=-1)
cerebro.adddata(data1)

data2 = bt.feeds.YahooFinanceCSVData(dataname='/Users/bibani/Desktop/AAME.csv',
dtformat=('%Y.%m.%d'),
fromdate = datetime.datetime(2018,1,2),
todate = datetime.datetime(2021,1,15),
datetime=0,
time=-1,
high=-1,
low=-1,
open=-1,
close=1,
volume=-1,
openinterest=-1)
cerebro.adddata(data2)

#Add strategy to Cerebro
cerebro.addstrategy(PairTradingStrategy)


if name == 'main':
# Run Cerebro Engine
start_portfolio_value = cerebro.broker.getvalue()

cerebro.run()

end_portfolio_value = cerebro.broker.getvalue()

pnl = end_portfolio_value - start_portfolio_value
print(f'Starting Portfolio Value: {start_portfolio_value:2f}')
print(f'Final Portfolio Value: {end_portfolio_value:2f}')
print(f'PnL: {pnl:.2f}')
#Run Cerebro Engine
cerebro.run()

Can anyone tell me please why I have an error and if the code is ok to make it run successfully ?

Thank you for your help!

Hi to my lovely Community ,

Where is the error in the code please for implementing the Pair Trading Strategy ?

Thank you very much

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
import argparse
import backtrader as bt 
import backtrader.analyzers as btanalyzers
import backtrader.feeds as btfeeds
import backtrader.indicators as btind
import datetime
import pandas as pd 
import matplotlib
import pandas as pd
import quantstats

class PairsTradingStrategy(bt.Strategy) : 
    params = dict(
        period = 10,
        stake = 10,
        qty1 = 0,
        qty2 = 0,
        printout = True,
        upper = 2.1,
        lower = -2.1,
        up_medium = 0.5,
        low_medium = -0.5,
        upper_level = 2.1,
        lower_level = -2.1,
        status = 0,
        portfolio_value=10000,
        )

    def log(self,txt,dt=None) : 
        if self.p.printout :
            dt = dt or self.data.datetime[0]
            dt = bt.num2date(dt)
            print('%s,%s' % (dt.isoformat(),txt))

    def notify_order(self,order) :
        if order.status in [bt.Order.Submitted,bt.Order.Accepted] : 
            return 
        if order.status == order.Completed :
            if order.isbuy():
                buytxt = 'BUY COMPLETE,%2f' % order.executed.price
                self.log(buytxt,order.executed.dt)
            else:
                selltxt = 'SELL COMPLETE,%.2f' % order.executed.price
                self.log(selltxt,order.executed.dt)

        elif  order.status in [order.Expired,order.Canceled,order.Margin]:
            self.log('%s,'% order.Status[order.status])
            pass 

        self.orderid = None

    def __init__(self):

        self.orderid = None
        self.qty1 = self.p.qty1
        self.qty2 = self.p.qty2
        self.upper_limit = self.p.upper
        self.lower_limit = self.p.lower
        self.up_medium = self.p.up_medium
        self.low_medium = self.p.low_medium
        self.status = self.p.status 
        self.portfolio_value = self.p.portfolio_value

        self.transform = btind.OLS_TransformationN(self.data0,self.data1,period=self.p.period)

        self.zscore = self.transform.zscore


    def next(self) :

        if self.orderid : 
            return 

        if self.p.printout:
            print('Self  len:', len(self))
            print('Data0 len:', len(self.data0))
            print('Data1 len:', len(self.data1))
            print('Data0 len == Data1 len:',
                  len(self.data0) == len(self.data1))

            print('Data0 dt:', self.data0.datetime.datetime())
            print('Data1 dt:', self.data1.datetime.datetime())

        print('status is', self.status)
        print('zscore is', self.zscore[0])

        # Step 2: Check conditions for SHORT & place the order
        # Checking the condition for SHORT
        if (self.zscore[0] > self.upper_limit) and (self.status != 1):

            # Calculating the number of shares for each stock
            value = 0.5 * self.portfolio_value  # Divide the cash equally
            x = int(value / (self.data0.close))  # Find the number of shares for Stock1
            y = int(value / (self.data1.close))  # Find the number of shares for Stock2
            print('x + self.qty1 is', x + self.qty1)
            print('y + self.qty2 is', y + self.qty2)

            # Placing the order
            self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data0.close[0], x + self.qty1))
            self.sell(data=self.data0, size=(x + self.qty1))  # Place an order for buying y + qty2 shares
            self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("AAME", self.data1.close[0], y + self.qty2))
            self.buy(data=self.data1, size=(y + self.qty2))  # Place an order for selling x + qty1 shares

            # Updating the counters with new value
            self.qty1 = x  # The new open position quantity for Stock1 is x shares
            self.qty2 = y  # The new open position quantity for Stock2 is y shares
            self.status = 1  # The current status is "short the spread"

            # Step 3: Check conditions for LONG & place the order
            # Checking the condition for LONG
        elif (self.zscore[0] < self.lower_limit) and (self.status != 2):

            # Calculating the number of shares for each stock
            value = 0.5 * self.portfolio_value  # Divide the cash equally
            x = int(value / (self.data0.close))  # Find the number of shares for Stock1
            y = int(value / (self.data1.close))  # Find the number of shares for Stock2
            print('x + self.qty1 is', x + self.qty1)
            print('y + self.qty2 is', y + self.qty2)

            # Place the order
            self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data0.close[0], x + self.qty1))
            self.buy(data=self.data0, size=(x + self.qty1))  # Place an order for buying x + qty1 shares
            self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AAME", self.data1.close[0], y + self.qty2))
            self.sell(data=self.data1, size=(y + self.qty2))  # Place an order for selling y + qty2 shares

            # Updating the counters with new value
            self.qty1 = x  # The new open position quantity for Stock1 is x shares
            self.qty2 = y  # The new open position quantity for Stock2 is y shares
            self.status = 2  # The current status is "long the spread"

            # Step 4: Check conditions for No Trade
            # If the z-score is within the two bounds, close all
       
        elif (self.zscore[0] < self.up_medium and self.zscore[0] > self.low_medium):
            self.log('CLOSE LONG %s, price = %.2f' % ("AACQW", self.data0.close[0]))
            self.close(self.data0)
            self.log('CLOSE LONG %s, price = %.2f' % ("AAME", self.data1.close[0]))
            self.close(self.data1)
            

    def stop(self):
        print('==================================================')
        print('Starting Value - %.2f' % self.broker.startingcash)
        print('Ending   Value - %.2f' % self.broker.getvalue())
        print('==================================================')

    
def parse_args():
    parser = argparse.ArgumentParser(description='MultiData Strategy')

    parser.add_argument('--data0', '-d0',
                        default='/Users/bibani/Desktop/AACQW.csv',
                        help='1st data into the system')

    parser.add_argument('--data1', '-d1',
                        default='/Users/bibani/Desktop/AAME.csv',
                        help='2nd data into the system')

    parser.add_argument('--fromdate', '-f',
                        default='2018-01-02',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--todate', '-t',
                        default='2021-01-15',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--period', default=10, type=int,
                        help='Period to apply to the Simple Moving Average')

    parser.add_argument('--cash', default=100000, type=int,
                        help='Starting Cash')

    parser.add_argument('--runnext', action='store_true',
                        help='Use next by next instead of runonce')

    parser.add_argument('--nopreload', action='store_true',
                        help='Do not preload the data')

    parser.add_argument('--oldsync', action='store_true',
                        help='Use old data synchronization method')

    parser.add_argument('--commperc', default=0.005, type=float,
                        help='Percentage commission (0.005 is 0.5%%')

    parser.add_argument('--stake', default=10, type=int,
                        help='Stake to apply in each operation')

    parser.add_argument('--plot', '-p', default=True, action='store_true',
                        help='Plot the read data')

    parser.add_argument('--numfigs', '-n', default=1,
                        help='Plot using numfigs figures')

    return parser.parse_args()

def runstrategy():
    args = parse_args()

    # Create a cerebro
    cerebro = bt.Cerebro()

    # Get the dates from the args
    fromdate = datetime.datetime.strptime(args.fromdate, '%Y-%m-%d')
    todate = datetime.datetime.strptime(args.todate, '%Y-%m-%d')

    # Create the 1st data
    data0 = btfeeds.GenericCSVData(
        dataname=args.data0,
        dtformat = ('%Y-%m-%d'),
        fromdate=fromdate,
        todate=todate,
        datetime=0, 
        high=-1, 
        low=-1, 
        open=-1,
        close=1, 
        volume=-1, 
        openinterest=-1
)

    # Add the 1st data to cerebro
    cerebro.adddata(data0)

    # Create the 2nd data
    data1 = btfeeds.GenericCSVData(
        dataname=args.data1,
        dtformat = ('%Y-%m-%d'),
        fromdate=fromdate,
        todate=todate,
        datetime=0, 
        high=-1, 
        low=-1, 
        open=-1,
        close=1, 
        volume=-1, 
        openinterest=-1
        )

    # Add the 2nd data to cerebro
    cerebro.adddata(data1)

    # Add the strategy
    cerebro.addstrategy(PairsTradingStrategy,
        period=args.period,
        stake=args.stake)

    cerebro.broker.setcash(args.cash)

    # Add the commission - only stocks like a for each operation
    cerebro.broker.setcommission(commission=args.commperc)

    # And run it
    results = cerebro.run(runonce=not args.runnext,
        preload=not args.nopreload,
        oldsync=args.oldsync)

    cerebro.broker.getvalue()

    cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name='SharpeRatio')
    cerebro.addanalyzer(bt.analyzers.DrawDown, _name='DW')
    end_portfolio_value = cerebro.broker.getvalue()

    #print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
    #print('SR:', cerebro.analyzers.SharpeRatio.get_analysis())
    #print('DW:', cerebro.analyzers.DW.get_analysis())

    # Plot if requested
    if args.plot:
        cerebro.plot(numfigs=args.numfigs, volume=False, zdown=False,iplot= False)

if __name__ == '__main__':
    runstrategy()

@vladisld Actually , YES , it helps but not sufficient :)

I have as an ending value : NaN

Also , I don't have any signals on the positions taken ....

BackTrader_Test.png image url)

@vladisld Actually No , the problem is not in the "cerebro.plot" ....If any one has any idea please do not hesitate

@vladisld thanks again :)

@vladisld yes I found out already ; I should put the GenericCSVData and its arguments as you said)

Thks

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

import argparse
import backtrader as bt 
import backtrader.analyzers as btanalyzers
import backtrader.feeds as btfeeds
import backtrader.indicators as btind
import datetime
import pandas as pd 
import matplotlib
import pandas as pd
import quantstats

class PairsTradingStrategy(bt.Strategy) : 
    params = dict(
        period = 10,
        stake = 10,
        qty1 = 0,
        qty2 = 0,
        printout = True,
        upper = 2.1,
        lower = -2.1,
        up_medium = 0.5,
        low_medium = -0.5,
        upper_level = 2.1,
        lower_level = -2.1,
        status = 0,
        portfolio_value=10000,
        )

    def log(self,txt,dt=None) : 
        if self.p.printout :
            dt = dt or self.data.datetime[0]
            dt = bt.num2date(dt)
            print('%s,%s' % (dt.isoformat(),txt))

    def notify_order(self,order) :
        if order.status in [bt.Order.Submitted,bt.Order.Accepted] : 
            return 
        if order.status == order.Completed :
            if order.isbuy():
                buytxt = 'BUY COMPLETE,%2f' % order.executed.price
                self.log(buytxt,order.executed.dt)
            else:
                selltxt = 'SELL COMPLETE,%.2f' % order.executed.price
                self.log(selltxt,order.executed.dt)

        elif  order.status in [order.Expired,order.Canceled,order.Margin]:
            self.log('%s,'% order.Status[order.status])
            pass 

        self.orderid = None

    def __init__(self):

        self.orderid = None
        self.qty1 = self.p.qty1
        self.qty2 = self.p.qty2
        self.upper_limit = self.p.upper
        self.lower_limit = self.p.lower
        self.up_medium = self.p.up_medium
        self.low_medium = self.p.low_medium
        self.status = self.p.status 
        self.portfolio_value = self.p.portfolio_value

        self.transform = btind.OLS_TransformationN(self.data0,self.data1,period=self.p.period)

        self.zscore = self.transform.zscore


    def next(self) :

        if self.orderid : 
            return 

        if self.p.printout:
            print('Self  len:', len(self))
            print('Data0 len:', len(self.data0))
            print('Data1 len:', len(self.data1))
            print('Data0 len == Data1 len:',
                  len(self.data0) == len(self.data1))

            print('Data0 dt:', self.data0.datetime.datetime())
            print('Data1 dt:', self.data1.datetime.datetime())

        print('status is', self.status)
        print('zscore is', self.zscore[0])

        # Step 2: Check conditions for SHORT & place the order
        # Checking the condition for SHORT
        if (self.zscore[0] > self.upper_limit) and (self.status != 1):

            # Calculating the number of shares for each stock
            value = 0.5 * self.portfolio_value  # Divide the cash equally
            x = int(value / (self.data0.close))  # Find the number of shares for Stock1
            y = int(value / (self.data1.close))  # Find the number of shares for Stock2
            print('x + self.qty1 is', x + self.qty1)
            print('y + self.qty2 is', y + self.qty2)

            # Placing the order
            self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data0.close[0], x + self.qty1))
            self.sell(data=self.data0, size=(x + self.qty1))  # Place an order for buying y + qty2 shares
            self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("AAME", self.data1.close[0], y + self.qty2))
            self.buy(data=self.data1, size=(y + self.qty2))  # Place an order for selling x + qty1 shares

            # Updating the counters with new value
            self.qty1 = x  # The new open position quantity for Stock1 is x shares
            self.qty2 = y  # The new open position quantity for Stock2 is y shares
            self.status = 1  # The current status is "short the spread"

            # Step 3: Check conditions for LONG & place the order
            # Checking the condition for LONG
        elif (self.zscore[0] < self.lower_limit) and (self.status != 2):

            # Calculating the number of shares for each stock
            value = 0.5 * self.portfolio_value  # Divide the cash equally
            x = int(value / (self.data0.close))  # Find the number of shares for Stock1
            y = int(value / (self.data1.close))  # Find the number of shares for Stock2
            print('x + self.qty1 is', x + self.qty1)
            print('y + self.qty2 is', y + self.qty2)

            # Place the order
            self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data0.close[0], x + self.qty1))
            self.buy(data=self.data0, size=(x + self.qty1))  # Place an order for buying x + qty1 shares
            self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AAME", self.data1.close[0], y + self.qty2))
            self.sell(data=self.data1, size=(y + self.qty2))  # Place an order for selling y + qty2 shares

            # Updating the counters with new value
            self.qty1 = x  # The new open position quantity for Stock1 is x shares
            self.qty2 = y  # The new open position quantity for Stock2 is y shares
            self.status = 2  # The current status is "long the spread"

            # Step 4: Check conditions for No Trade
            # If the z-score is within the two bounds, close all
       
        elif (self.zscore[0] < self.up_medium and self.zscore[0] > self.low_medium):
            self.log('CLOSE LONG %s, price = %.2f' % ("AACQW", self.data0.close[0]))
            self.close(self.data0)
            self.log('CLOSE LONG %s, price = %.2f' % ("AAME", self.data1.close[0]))
            self.close(self.data1)
            

    def stop(self):
        print('==================================================')
        print('Starting Value - %.2f' % self.broker.startingcash)
        print('Ending   Value - %.2f' % self.broker.getvalue())
        print('==================================================')

    
def parse_args():
    parser = argparse.ArgumentParser(description='MultiData Strategy')

    parser.add_argument('--data0', '-d0',
                        default='/Users/bibani/Desktop/AACQW.csv',
                        help='1st data into the system')

    parser.add_argument('--data1', '-d1',
                        default='/Users/bibani/Desktop/AAME.csv',
                        help='2nd data into the system')

    parser.add_argument('--fromdate', '-f',
                        default='2018-01-02',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--todate', '-t',
                        default='2021-01-15',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--period', default=10, type=int,
                        help='Period to apply to the Simple Moving Average')

    parser.add_argument('--cash', default=100000, type=int,
                        help='Starting Cash')

    parser.add_argument('--runnext', action='store_true',
                        help='Use next by next instead of runonce')

    parser.add_argument('--nopreload', action='store_true',
                        help='Do not preload the data')

    parser.add_argument('--oldsync', action='store_true',
                        help='Use old data synchronization method')

    parser.add_argument('--commperc', default=0.005, type=float,
                        help='Percentage commission (0.005 is 0.5%%')

    parser.add_argument('--stake', default=10, type=int,
                        help='Stake to apply in each operation')

    parser.add_argument('--plot', '-p', default=True, action='store_true',
                        help='Plot the read data')

    parser.add_argument('--numfigs', '-n', default=1,
                        help='Plot using numfigs figures')

    return parser.parse_args()

def runstrategy():
    args = parse_args()

    # Create a cerebro
    cerebro = bt.Cerebro()

    # Get the dates from the args
    fromdate = datetime.datetime.strptime(args.fromdate, '%Y-%m-%d')
    todate = datetime.datetime.strptime(args.todate, '%Y-%m-%d')

    # Create the 1st data
    data0 = btfeeds.GenericCSVData(
        dataname=args.data0,
        dtformat = ('%Y-%m-%d'),
        fromdate=fromdate,
        todate=todate,
        datetime=0, 
        high=-1, 
        low=-1, 
        open=-1,
        close=1, 
        volume=-1, 
        openinterest=-1
)

    # Add the 1st data to cerebro
    cerebro.adddata(data0)

    # Create the 2nd data
    data1 = btfeeds.GenericCSVData(
        dataname=args.data1,
        dtformat = ('%Y-%m-%d'),
        fromdate=fromdate,
        todate=todate,
        datetime=0, 
        high=-1, 
        low=-1, 
        open=-1,
        close=1, 
        volume=-1, 
        openinterest=-1
        )

    # Add the 2nd data to cerebro
    cerebro.adddata(data1)

    # Add the strategy
    cerebro.addstrategy(PairsTradingStrategy,
        period=args.period,
        stake=args.stake)

    cerebro.broker.setcash(args.cash)

    # Add the commission - only stocks like a for each operation
    cerebro.broker.setcommission(commission=args.commperc)

    # And run it
    results = cerebro.run(runonce=not args.runnext,
        preload=not args.nopreload,
        oldsync=args.oldsync)

    cerebro.broker.getvalue()

    cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name='SharpeRatio')
    cerebro.addanalyzer(bt.analyzers.DrawDown, _name='DW')
    end_portfolio_value = cerebro.broker.getvalue()

    #print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
    #print('SR:', cerebro.analyzers.SharpeRatio.get_analysis())
    #print('DW:', cerebro.analyzers.DW.get_analysis())

    # Plot if requested
    if args.plot:
        cerebro.plot(numfigs=args.numfigs, volume=False, zdown=False)

if __name__ == '__main__':
    runstrategy()

why am I getting this error :

<IPython.core.display.Javascript object>
<IPython.core.display.HTML object>
Traceback (most recent call last):
File "Test_Iheb.py", line 275, in <module>
runstrategy()
File "Test_Iheb.py", line 272, in runstrategy
cerebro.plot(numfigs=args.numfigs, volume=False, zdown=False)
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 996, in plot
plotter.show()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/plot/plot.py", line 817, in show
self.mpyplot.show()
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/pyplot.py", line 269, in show
return _show(*args, **kw)
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_nbagg.py", line 261, in show
manager.show()
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_nbagg.py", line 90, in show
self._create_comm()
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_nbagg.py", line 122, in _create_comm
self.add_web_socket(comm)
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_webagg_core.py", line 432, in add_web_socket
self.resize(w, h)
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_webagg_core.py", line 418, in resize
size=(w / self.canvas._dpi_ratio, h / self.canvas._dpi_ratio))
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_webagg_core.py", line 489, in _send_event
s.send_json(payload)
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_nbagg.py", line 199, in send_json
self.comm.send({'data': json.dumps(content)})
File "/opt/anaconda3/lib/python3.7/site-packages/ipykernel/comm/comm.py", line 123, in send
data=data, metadata=metadata, buffers=buffers,
File "/opt/anaconda3/lib/python3.7/site-packages/ipykernel/comm/comm.py", line 66, in _publish_msg
self.kernel.session.send(self.kernel.iopub_socket, msg_type,
AttributeError: 'NoneType' object has no attribute 'session'
Error in atexit._run_exitfuncs:
Traceback (most recent call last):
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/_pylab_helpers.py", line 73, in destroy_all
manager.destroy()
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_nbagg.py", line 126, in destroy
self._send_event('close')
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_webagg_core.py", line 489, in _send_event
s.send_json(payload)
File "/opt/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_nbagg.py", line 199, in send_json
self.comm.send({'data': json.dumps(content)})
File "/opt/anaconda3/lib/python3.7/site-packages/ipykernel/comm/comm.py", line 123, in send
data=data, metadata=metadata, buffers=buffers,
File "/opt/anaconda3/lib/python3.7/site-packages/ipykernel/comm/comm.py", line 66, in _publish_msg
self.kernel.session.send(self.kernel.iopub_socket, msg_type,
AttributeError: 'NoneType' object has no attribute 'session'

Hi guys , I have a problem with code as I get the following error :

Traceback (most recent call last):
File "PairTradingStrategy.py", line 174, in <module>
cerebro.run()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1127, in run
runstrat = self.runstrategies(iterstrat)
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1212, in runstrategies
data.preload()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 688, in preload
while self.load():
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 479, in load
_loadret = self._load()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 710, in _load
return self._loadline(linetokens)
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feeds/yahoo.py", line 134, in _loadline
h = float(linetokens[next(i)])
IndexError: list index out of range

import backtrader as bt
import backtrader.analyzers as btanalyzers
import backtrader.indicators as btind
import datetime

class PairTradingStrategy(bt.Strategy):
params = dict(
period=10,
stake=10,
qty1=0,
qty2=0,
printout=True,
upper=2.1,
lower=-2.1,
up_medium=0.5,
low_medium=-0.5,
status=0,
portfolio_value=10000,
)

def log(self, txt, dt=None):
   if self.p.printout:
       dt = dt or self.data.datetime[0]
       dt = bt.num2date(dt)
       print('%s, %s' % (dt.isoformat(), txt))

def __init__(self):
  # To control operation entries
   self.orderid = None
   self.qty1 = self.p.qty1
   self.qty2 = self.p.qty2
   self.upper_limit = self.p.upper
   self.lower_limit = self.p.lower
   self.up_medium = self.p.up_medium
   self.low_medium = self.p.low_medium
   self.status = self.p.status
   self.portfolio_value = self.p.portfolio_value

# Signals performed with PD.OLS :
   self.transform = btind.OLS_TransformationN(self.data1, self.data2,
                                              period=self.p.period)
   self.zscore = self.transform.zscore

   # Checking signals built with StatsModel.API :
   # self.ols_transfo = btind.OLS_Transformation(self.data1, self.data2,
   #                                             period=self.p.period,
   #                                             plot=True)

def next(self):
if self.orderid:
return # if an order is active, no new orders are allowed

   if self.p.printout:
       print('Self  len:', len(self))
       print('Data1 len:', len(self.data1))
       print('Data2 len:', len(self.data2))
       print('Data1 len == Data2 len:',
             len(self.data1) == len(self.data2))

       print('Data1 dt:', self.data1.datetime.datetime())
       print('Data2 dt:', self.data2.datetime.datetime())

   print('status is', self.status)
   print('zscore is', self.zscore[0])


   # Step 2: Check conditions for SHORT & place the order
   # Checking the condition for SHORT
   if (self.zscore[0] > self.upper_limit) and (self.status != 1):

       # Calculating the number of shares for each stock
       value = 0.5 * self.portfolio_value  # Divide the cash equally
       x = int(value / (self.data1.close))  # Find the number of shares for Stock1
       y = int(value / (self.data2.close))  # Find the number of shares for Stock2
       print('x + self.qty1 is', x + self.qty1)
       print('y + self.qty2 is', y + self.qty2)

       # Placing the order
       self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data1.close[0], x + self.qty1))
       self.sell(data=self.data1, size=(x + self.qty1))  # Place an order for buying y + qty2 shares
       self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("KO", self.data2.close[0], y + self.qty2))
       self.buy(data=self.data2, size=(y + self.qty2))  # Place an order for selling x + qty1 shares

       # Updating the counters with new value
       self.qty1 = x  # The new open position quantity for Stock1 is x shares
       self.qty2 = y  # The new open position quantity for Stock2 is y shares

       self.status = 1  # The current status is "short the spread"

       # Step 3: Check conditions for LONG & place the order
       # Checking the condition for LONG
   elif (self.zscore[0] < self.lower_limit) and (self.status != 2):

       # Calculating the number of shares for each stock
       value = 0.5 * self.portfolio_value  # Divide the cash equally
       x = int(value / (self.data1.close))  # Find the number of shares for Stock1
       y = int(value / (self.data2.close))  # Find the number of shares for Stock2
       print('x + self.qty1 is', x + self.qty1)
       print('y + self.qty2 is', y + self.qty2)

       # Place the order
       self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data1.close[0], x + self.qty1))
       self.buy(data=self.data1, size=(x + self.qty1))  # Place an order for buying x + qty1 shares
       self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AAME", self.data2.close[0], y + self.qty2))
       self.sell(data=self.data2, size=(y + self.qty2))  # Place an order for selling y + qty2 shares

       # Updating the counters with new value
       self.qty1 = x  # The new open position quantity for Stock1 is x shares
       self.qty2 = y  # The new open position quantity for Stock2 is y shares
       self.status = 2  # The current status is "long the spread"


       # Step 4: Check conditions for No Trade
       # If the z-score is within the two bounds, close all

   elif (self.zscore[0] < self.up_medium and self.zscore[0] > self.low_medium):
       self.log('CLOSE LONG %s, price = %.2f' % ("PEP", self.data1.close[0]))
       self.close(self.data1)
       self.log('CLOSE LONG %s, price = %.2f' % ("KO", self.data2.close[0]))
       self.close(self.data2)


def stop(self):
       print('==================================================')
       print('Starting Value - %.2f' % self.broker.startingcash)
       print('Ending   Value - %.2f' % self.broker.getvalue())
       print('==================================================')

#Instantiate Cerebro engine
cerebro = bt.Cerebro()

#Add data feed to Cerebro
data1 = bt.feeds.YahooFinanceCSVData(dataname='/Users/bibani/Desktop/AACQW.csv',
dtformat=('%Y.%m.%d'),
fromdate = datetime.datetime(2018,1,2),
todate = datetime.datetime(2021,1,15),
datetime=0,
time=-1,
high=-1,
low=-1,
open=-1,
close=1,
volume=-1,
openinterest=-1)
cerebro.adddata(data1)

data2 = bt.feeds.YahooFinanceCSVData(dataname='/Users/bibani/Desktop/AAME.csv',
dtformat=('%Y.%m.%d'),
fromdate = datetime.datetime(2018,1,2),
todate = datetime.datetime(2021,1,15),
datetime=0,
time=-1,
high=-1,
low=-1,
open=-1,
close=1,
volume=-1,
openinterest=-1)
cerebro.adddata(data2)

#Add strategy to Cerebro
cerebro.addstrategy(PairTradingStrategy)


if name == 'main':
# Run Cerebro Engine
start_portfolio_value = cerebro.broker.getvalue()

cerebro.run()

end_portfolio_value = cerebro.broker.getvalue()

pnl = end_portfolio_value - start_portfolio_value
print(f'Starting Portfolio Value: {start_portfolio_value:2f}')
print(f'Final Portfolio Value: {end_portfolio_value:2f}')
print(f'PnL: {pnl:.2f}')
#Run Cerebro Engine
cerebro.run()

Thank you very much for your help :)

Hi guys ,

I'm new here.

I discovered BACKTRADER and I'm struggling with PAIR TRADING even if I found out a GitHub repository where we have the full access...but It doesn't work.

Anyway , I tried to apply the code to my .csv files but I get this error :

Traceback (most recent call last):
File "PairTradingStrategy.py", line 174, in <module>
cerebro.run()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1127, in run
runstrat = self.runstrategies(iterstrat)
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1212, in runstrategies
data.preload()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 688, in preload
while self.load():
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 479, in load
_loadret = self._load()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 710, in _load
return self._loadline(linetokens)
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feeds/yahoo.py", line 134, in _loadline
h = float(linetokens[next(i)])
IndexError: list index out of range

and the code is as following :

import backtrader as bt
import backtrader.analyzers as btanalyzers
import backtrader.indicators as btind
import datetime

class PairTradingStrategy(bt.Strategy):
params = dict(
period=10,
stake=10,
qty1=0,
qty2=0,
printout=True,
upper=2.1,
lower=-2.1,
up_medium=0.5,
low_medium=-0.5,
status=0,
portfolio_value=10000,
)

def log(self, txt, dt=None):
    if self.p.printout:
        dt = dt or self.data.datetime[0]
        dt = bt.num2date(dt)
        print('%s, %s' % (dt.isoformat(), txt))

def __init__(self):
   # To control operation entries
    self.orderid = None
    self.qty1 = self.p.qty1
    self.qty2 = self.p.qty2
    self.upper_limit = self.p.upper
    self.lower_limit = self.p.lower
    self.up_medium = self.p.up_medium
    self.low_medium = self.p.low_medium
    self.status = self.p.status
    self.portfolio_value = self.p.portfolio_value

# Signals performed with PD.OLS :
    self.transform = btind.OLS_TransformationN(self.data1, self.data2,
                                               period=self.p.period)
    self.zscore = self.transform.zscore

    # Checking signals built with StatsModel.API :
    # self.ols_transfo = btind.OLS_Transformation(self.data1, self.data2,
    #                                             period=self.p.period,
    #                                             plot=True)

def next(self):
if self.orderid:
return # if an order is active, no new orders are allowed

    if self.p.printout:
        print('Self  len:', len(self))
        print('Data1 len:', len(self.data1))
        print('Data2 len:', len(self.data2))
        print('Data1 len == Data2 len:',
              len(self.data1) == len(self.data2))

        print('Data1 dt:', self.data1.datetime.datetime())
        print('Data2 dt:', self.data2.datetime.datetime())

    print('status is', self.status)
    print('zscore is', self.zscore[0])


    # Step 2: Check conditions for SHORT & place the order
    # Checking the condition for SHORT
    if (self.zscore[0] > self.upper_limit) and (self.status != 1):

        # Calculating the number of shares for each stock
        value = 0.5 * self.portfolio_value  # Divide the cash equally
        x = int(value / (self.data1.close))  # Find the number of shares for Stock1
        y = int(value / (self.data2.close))  # Find the number of shares for Stock2
        print('x + self.qty1 is', x + self.qty1)
        print('y + self.qty2 is', y + self.qty2)

        # Placing the order
        self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data1.close[0], x + self.qty1))
        self.sell(data=self.data1, size=(x + self.qty1))  # Place an order for buying y + qty2 shares
        self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("KO", self.data2.close[0], y + self.qty2))
        self.buy(data=self.data2, size=(y + self.qty2))  # Place an order for selling x + qty1 shares

        # Updating the counters with new value
        self.qty1 = x  # The new open position quantity for Stock1 is x shares
        self.qty2 = y  # The new open position quantity for Stock2 is y shares

        self.status = 1  # The current status is "short the spread"

        # Step 3: Check conditions for LONG & place the order
        # Checking the condition for LONG
    elif (self.zscore[0] < self.lower_limit) and (self.status != 2):

        # Calculating the number of shares for each stock
        value = 0.5 * self.portfolio_value  # Divide the cash equally
        x = int(value / (self.data1.close))  # Find the number of shares for Stock1
        y = int(value / (self.data2.close))  # Find the number of shares for Stock2
        print('x + self.qty1 is', x + self.qty1)
        print('y + self.qty2 is', y + self.qty2)

        # Place the order
        self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data1.close[0], x + self.qty1))
        self.buy(data=self.data1, size=(x + self.qty1))  # Place an order for buying x + qty1 shares
        self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AAME", self.data2.close[0], y + self.qty2))
        self.sell(data=self.data2, size=(y + self.qty2))  # Place an order for selling y + qty2 shares

        # Updating the counters with new value
        self.qty1 = x  # The new open position quantity for Stock1 is x shares
        self.qty2 = y  # The new open position quantity for Stock2 is y shares
        self.status = 2  # The current status is "long the spread"


        # Step 4: Check conditions for No Trade
        # If the z-score is within the two bounds, close all

    elif (self.zscore[0] < self.up_medium and self.zscore[0] > self.low_medium):
        self.log('CLOSE LONG %s, price = %.2f' % ("PEP", self.data1.close[0]))
        self.close(self.data1)
        self.log('CLOSE LONG %s, price = %.2f' % ("KO", self.data2.close[0]))
        self.close(self.data2)


def stop(self):
        print('==================================================')
        print('Starting Value - %.2f' % self.broker.startingcash)
        print('Ending   Value - %.2f' % self.broker.getvalue())
        print('==================================================')

#Instantiate Cerebro engine
cerebro = bt.Cerebro()

#Add data feed to Cerebro
data1 = bt.feeds.YahooFinanceCSVData(dataname='/Users/bibani/Desktop/AACQW.csv',
dtformat=('%Y.%m.%d'),
fromdate = datetime.datetime(2018,1,2),
todate = datetime.datetime(2021,1,15),
datetime=0,
time=-1,
high=-1,
low=-1,
open=-1,
close=1,
volume=-1,
openinterest=-1)
cerebro.adddata(data1)

data2 = bt.feeds.YahooFinanceCSVData(dataname='/Users/bibani/Desktop/AAME.csv',
dtformat=('%Y.%m.%d'),
fromdate = datetime.datetime(2018,1,2),
todate = datetime.datetime(2021,1,15),
datetime=0,
time=-1,
high=-1,
low=-1,
open=-1,
close=1,
volume=-1,
openinterest=-1)
cerebro.adddata(data2)

#Add strategy to Cerebro
cerebro.addstrategy(PairTradingStrategy)


if name == 'main':
# Run Cerebro Engine
start_portfolio_value = cerebro.broker.getvalue()

cerebro.run()

end_portfolio_value = cerebro.broker.getvalue()

pnl = end_portfolio_value - start_portfolio_value
print(f'Starting Portfolio Value: {start_portfolio_value:2f}')
print(f'Final Portfolio Value: {end_portfolio_value:2f}')
print(f'PnL: {pnl:.2f}')
#Run Cerebro Engine
cerebro.run()

Can anyone tell me please why I have an error and if the code is ok to make it run successfully ?

Thank you for your help!

Hi guys ,

I'm new here.

I discovered BACKTRADER and I'm struggling with PAIR TRADING even if I found out a GitHub repository where we have the full access...but It doesn't work.

Anyway , I tried to apply the code to my .csv files but I get this error :

Traceback (most recent call last):
File "PairTradingStrategy.py", line 174, in <module>
cerebro.run()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1127, in run
runstrat = self.runstrategies(iterstrat)
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1212, in runstrategies
data.preload()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 688, in preload
while self.load():
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 479, in load
_loadret = self._load()
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feed.py", line 710, in _load
return self._loadline(linetokens)
File "/opt/anaconda3/lib/python3.7/site-packages/backtrader/feeds/yahoo.py", line 134, in _loadline
h = float(linetokens[next(i)])
IndexError: list index out of range

and the code is as following :

"""

import backtrader as bt
import backtrader.analyzers as btanalyzers
import backtrader.indicators as btind
import datetime
"""
"""
class PairTradingStrategy(bt.Strategy):
params = dict(
period=10,
stake=10,
qty1=0,
qty2=0,
printout=True,
upper=2.1,
lower=-2.1,
up_medium=0.5,
low_medium=-0.5,
status=0,
portfolio_value=10000,
)

def log(self, txt, dt=None):
    if self.p.printout:
        dt = dt or self.data.datetime[0]
        dt = bt.num2date(dt)
        print('%s, %s' % (dt.isoformat(), txt))

def __init__(self):
   # To control operation entries
    self.orderid = None
    self.qty1 = self.p.qty1
    self.qty2 = self.p.qty2
    self.upper_limit = self.p.upper
    self.lower_limit = self.p.lower
    self.up_medium = self.p.up_medium
    self.low_medium = self.p.low_medium
    self.status = self.p.status
    self.portfolio_value = self.p.portfolio_value

# Signals performed with PD.OLS :
    self.transform = btind.OLS_TransformationN(self.data1, self.data2,
                                               period=self.p.period)
    self.zscore = self.transform.zscore

    # Checking signals built with StatsModel.API :
    # self.ols_transfo = btind.OLS_Transformation(self.data1, self.data2,
    #                                             period=self.p.period,
    #                                             plot=True)

""""
def next(self):
if self.orderid:
return # if an order is active, no new orders are allowed

    if self.p.printout:
        print('Self  len:', len(self))
        print('Data1 len:', len(self.data1))
        print('Data2 len:', len(self.data2))
        print('Data1 len == Data2 len:',
              len(self.data1) == len(self.data2))

        print('Data1 dt:', self.data1.datetime.datetime())
        print('Data2 dt:', self.data2.datetime.datetime())

    print('status is', self.status)
    print('zscore is', self.zscore[0])


    # Step 2: Check conditions for SHORT & place the order
    # Checking the condition for SHORT
    if (self.zscore[0] > self.upper_limit) and (self.status != 1):

        # Calculating the number of shares for each stock
        value = 0.5 * self.portfolio_value  # Divide the cash equally
        x = int(value / (self.data1.close))  # Find the number of shares for Stock1
        y = int(value / (self.data2.close))  # Find the number of shares for Stock2
        print('x + self.qty1 is', x + self.qty1)
        print('y + self.qty2 is', y + self.qty2)

        # Placing the order
        self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data1.close[0], x + self.qty1))
        self.sell(data=self.data1, size=(x + self.qty1))  # Place an order for buying y + qty2 shares
        self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("KO", self.data2.close[0], y + self.qty2))
        self.buy(data=self.data2, size=(y + self.qty2))  # Place an order for selling x + qty1 shares

        # Updating the counters with new value
        self.qty1 = x  # The new open position quantity for Stock1 is x shares
        self.qty2 = y  # The new open position quantity for Stock2 is y shares

        self.status = 1  # The current status is "short the spread"

        # Step 3: Check conditions for LONG & place the order
        # Checking the condition for LONG
    elif (self.zscore[0] < self.lower_limit) and (self.status != 2):

        # Calculating the number of shares for each stock
        value = 0.5 * self.portfolio_value  # Divide the cash equally
        x = int(value / (self.data1.close))  # Find the number of shares for Stock1
        y = int(value / (self.data2.close))  # Find the number of shares for Stock2
        print('x + self.qty1 is', x + self.qty1)
        print('y + self.qty2 is', y + self.qty2)

        # Place the order
        self.log('BUY CREATE %s, price = %.2f, qty = %d' % ("AACQW", self.data1.close[0], x + self.qty1))
        self.buy(data=self.data1, size=(x + self.qty1))  # Place an order for buying x + qty1 shares
        self.log('SELL CREATE %s, price = %.2f, qty = %d' % ("AAME", self.data2.close[0], y + self.qty2))
        self.sell(data=self.data2, size=(y + self.qty2))  # Place an order for selling y + qty2 shares

        # Updating the counters with new value
        self.qty1 = x  # The new open position quantity for Stock1 is x shares
        self.qty2 = y  # The new open position quantity for Stock2 is y shares
        self.status = 2  # The current status is "long the spread"


        # Step 4: Check conditions for No Trade
        # If the z-score is within the two bounds, close all

    elif (self.zscore[0] < self.up_medium and self.zscore[0] > self.low_medium):
        self.log('CLOSE LONG %s, price = %.2f' % ("PEP", self.data1.close[0]))
        self.close(self.data1)
        self.log('CLOSE LONG %s, price = %.2f' % ("KO", self.data2.close[0]))
        self.close(self.data2)

"""

def stop(self):
        print('==================================================')
        print('Starting Value - %.2f' % self.broker.startingcash)
        print('Ending   Value - %.2f' % self.broker.getvalue())
        print('==================================================')

"""
"""
#Instantiate Cerebro engine
cerebro = bt.Cerebro()

#Add data feed to Cerebro
data1 = bt.feeds.YahooFinanceCSVData(dataname='/Users/bibani/Desktop/AACQW.csv',
dtformat=('%Y.%m.%d'),
fromdate = datetime.datetime(2018,1,2),
todate = datetime.datetime(2021,1,15),
datetime=0,
time=-1,
high=-1,
low=-1,
open=-1,
close=1,
volume=-1,
openinterest=-1)
cerebro.adddata(data1)

data2 = bt.feeds.YahooFinanceCSVData(dataname='/Users/bibani/Desktop/AAME.csv',
dtformat=('%Y.%m.%d'),
fromdate = datetime.datetime(2018,1,2),
todate = datetime.datetime(2021,1,15),
datetime=0,
time=-1,
high=-1,
low=-1,
open=-1,
close=1,
volume=-1,
openinterest=-1)
cerebro.adddata(data2)
"""
"""
#Add strategy to Cerebro
cerebro.addstrategy(PairTradingStrategy)

"""
"""
if name == 'main':
# Run Cerebro Engine
start_portfolio_value = cerebro.broker.getvalue()

cerebro.run()

end_portfolio_value = cerebro.broker.getvalue()

pnl = end_portfolio_value - start_portfolio_value
print(f'Starting Portfolio Value: {start_portfolio_value:2f}')
print(f'Final Portfolio Value: {end_portfolio_value:2f}')
print(f'PnL: {pnl:.2f}')

#Run Cerebro Engine
cerebro.run()

"""
"""

Can anyone tell me please why I have an error and if the code is ok to make it run successfully ?

Thank you for your help!