ITBAL Session 6

Assignment 1:Create a log of returns on data from 01.01.2012 to 31.01.2013 and calculate historical volatility.
2.create ACF plot for log returns perform adf test and interpret.

closingprice<-ass1[,5]

closingprice.ts<-ts(closingprice,frequency=252)

temptable<-closingprice.ts-lag(closingprice.ts,k=-1)

lagtable<-cbind(closingprice.ts,lag(closingprice.ts,k=-1),temptable)

lagtable

head(lagtable)

returns<-(closingprice.ts-lag(closingprice.ts,k=-1))/lag(closingprice.ts,k=-1)

l<-scale(returns)+10
logreturns<-log(l)

acf(logreturns)

from the above graph we can see the measurements lie with in the 95% confidence interval therefore the time series is stationary.


2.commands
T=(252)^0.5
historicalvolatility<-sd(logreturns)*T
historicalvolatility
adf.test(logreturns)

From the picture it is clear that p value=0.01 is less than 0.05

Therefore we reject the null hypothesis and accept the alternative hypothesis which states the time series is stationary.