ITBA Lab session 6

Assignment:
1) create log of returns data (from 01.01.2012 to 01.01.2013) and calculate historical volatility
 2)Create ACF plot for the log returns data ,perform adf test and interpret.

Commands:
> stockprice<-read.csv(file.choose(),header=T)
> head(stockprice)
> closingprice<-stockprice[,5]
> closingprice.ts<-ts(closingprice,frequency=252)
> returns<-(closingprice.ts-lag(closingprice.ts,k=-1))/lag(closingprice.ts,k=-1)
> z<-scale(returns)+10
> logreturns<-log(z)
> logreturns

> acf(logreturns)

 

From the above graph, we can see that the measurements lie with in the 95% confidence interval. Therefore, the time series is stationary.

> T=252^0.5

> historicalvolatility<-sd(logreturns)*T

> historicalvolatility

> adf.test(logreturns)

 

 

From the test results, we can see that p-value=0.01 (<0.05).
 Therefore, we reject the null hypothesis and accept the alternate hypothesis which states that the time series is stationary.