Accessing last monday's value

[Dinesh Dileep Gaurav]

I am trying to learn trading and using backtrader. I am trying to use a simple strategy which will look at close value on previous monday on each monday. My code below checks if current day is monday and if so, then prints last monday's close price. Thus, I just use dataclose[-5] to get previous monday's value (dataclose is line which stores close values). The issue with this approach is that if someday's data is missing, then this becomes incorrect. What is a better way to do this. I guess, we can save every monday's value in a variable which can be accessed later. Is there a better/alternative way?

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

#import datetime  # For datetime objects
from datetime import datetime, timedelta
import os.path  # To manage paths
import sys  # To find out the script name (in argv[0])
import pandas as pd
import quandl
import numpy as np
import os


# Import the backtrader platform
import backtrader as bt
import backtrader.feeds as btfeeds
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
%matplotlib inline

def MakeArbitraryData(fromDate, ToDate):
    fromDateObj = datetime.strptime(fromDate,'%Y-%m-%d')
    toDateObj = datetime.strptime(toDate,'%Y-%m-%d')
    Delta = toDateObj - fromDateObj
    DateRange = [fromDateObj + timedelta(days=i) for i in range(Delta.days+1)] #create list of days
    WeekDays = [day.isoformat() for day in DateRange if day.isoweekday() not in [6,7]] # removing weekends
    nDays = len(WeekDays)
    A = np.random.randint(1,100,size=(nDays,4)) #create nDays X 4 matrix of random integers
    Apd = pd.DataFrame(data=A,columns=['Open','High','Close','Low'])
    Apd['Date']=pd.Series(WeekDays,dtype='datetime64[ns]')
    Apd = Apd.set_index('Date')
    return Apd


class TestStrategy(bt.Strategy):

    def log(self, txt, dt=None):
        """logging function for this strategy
            this is essentially the print function for the strategy"""
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(),txt))

    def __init__(self):
        self.dataclose = self.datas[0].close
        # To keep track of pending orders
        self.order = None

    def next(self):
        if len(self) >= 7: #start processing only after 7 days, to make sure at least one monday exists
            #check if monday
            if self.datas[0].datetime.date().isoweekday() == 1:
                print('self.dataclose[0] is %.2f' % self.dataclose[0])
                print('self.dataclose[-5] is %.2f' % self.dataclose[-5])
                print('self.datas[0].datetime.date(-5).isoformat() is %s' % self.datas[0].datetime.date(-5).isoformat())
                print('self.datas[0].datetime.date(0).isoformat() is %s' % self.datas[0].datetime.date(0).isoformat())
                print('\n')       

        if self.order:
            return


cerebro = bt.Cerebro()
cerebro.addstrategy(TestStrategy)
fromDate = '2018-03-04'
toDate = '2018-04-04'
StockData = MakeArbitraryData(fromDate, toDate)
data = bt.feeds.PandasData(dataname=StockData,
                               # datetime='Date',
                               nocase=True,
                               )
#add stock to cerebro
cerebro.adddata(data)


cerebro.broker.setcash(1000.0)

#printing out starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

#run over everything
cerebro.run()

# Print out the final result
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

print(StockData)

[backtrader]

@dinesh-dileep-gaurav said in Accessing last monday's value:

I guess, we can save every monday's value in a variable which can be accessed later. Is there a better/alternative way?

That's the only way, because trading holidays (which sometimes happen in a row) render a fixed value of -5 useless.