ASSIGNMENT1: Create log of return data. Find Historical volatility of it.

(Log St – Log St-1)/ log St-1 or Log [(St- St-1 )/St-1]

ASSIGNMENT2: Create ACF plot on log returns data. Also do ADF test on it and interpret it. Work with closing price

> data<-read.csv(file.choose(),header=T)

> close<-data$Close

> close.ts<-ts(close,frequency=252)

> closeshift.ts<-lag(close.ts,k=-1)

> n<-log(close.ts)-log(closeshift.ts)

> returns<-n/log(closeshift.ts)

> plot(returns,main="Log Returns")

 acf(returns,main="Auto Correlation Function")

> adf.test(returns)

        Augmented Dickey-Fuller Test

data:  returns 

Dickey-Fuller = -5.6217, Lag order = 6, p-value = 0.01

alternative hypothesis: stationary 

Warning message:

In adf.test(returns) : p-value smaller than printed p-value

 T<-252^0.5

> HistoricalValue<-sd(returns)/T

> HistoricalValue

[1] 6.825207e-05