Assignment# 6

Assignment 1: To find the historical volatility and log of returns data

Assignment 2: To create ACF plot of log returns and do Augmented Dickey-Fuller test

Assignment # 5

Assignment-1
Download NSE data for a 6months period at least and show the returns, having selected the 10^th data point as start and 95^th as end.

Commands:-

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

> close<-z$Close

> close.ts<-ts(close)

> close.ts<-ts(close,deltat= 1/252)

> x<-ts(data=close.ts[10:95],frequency=1,deltat=1/252)

> x.ts<-ts(x)

> x.diff<-diff(x)

> y<-lag(x.ts,K=-1)

> Returns<-x.diff/y

> plot(Returns,main=" Returns from 10th to 95th day of NSE Mid-cap Index ")

> z1<-cbind(x.ts,x.diff,Returns)

> plot(z1,main=" Data from 10th to 95th day ; Difference ; Returns")

 

 

Assignment#2. 

1-700 data is available. Predict the data from 701-850, use the GLM estimation using LOGIT Analysis for the same.

 Commands  

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

> z1<-logit.eg[1:700,1:9]

> head(z1)

> z1$ed<-factor(z1$ed)

> z1.est<-glm(default ~ age + ed + employ + address + income, data=z1, family ="binomial")

> summary(z1.est)

> forecast<-logit.eg[701:850,1:8]

> forecast$ed<-factor(forecast$ed)

> forecast$probability<-predict(z1.est,newdata=forecast,type="response")

> head(forecast)