Day 5

Assignment 1:
Download data for more than 6 months and calculate returns on a daily basis,for the 10th to 95th data point.

> nse<-read.csv(file.choose(),header=T)
> close<-nse$Close
> close.ts<-ts(close,deltat=1/252)
> close.ts.ts<-ts(data=close.ts[10:95],deltat=1/252)
> close.ts.ts<-ts(close.ts.ts)
> close.diff<-diff(close.ts.ts)
> returns<-close.diff/lag(close.ts.ts,k=-1)
> plot(returns,main="NSE plot for 10th to 95th data point for Close")

> display<-cbind(close.ts.ts,close.diff,lag(close.ts.ts,k=-1),returns)
> display

> plot(display,main="Returns and Difference")

Assignment 2:
Predict the loan possibility for the 701 to 850th data point in the given data.

> data<-read.csv(file.choose(),headet=T)
> data.eg<-data[1:700,1:9]

> data.eg$ed<-factor(data.eg$ed)
> data.est<-glm(default~ed+income+debtinc+creddebt+othdebt,data=data.eg,family="binomial")
> confint.default(data.est)

> data2.eg<with(data[701:850,1:8],data.frame(age=age,ed=factor(ed),employ=employ,address=address, income=income,debtinc=debtinc,creddebt=creddebt,othdebt=othdebt))

> data2.eg$default<-predict(data.est,newdata=data2.eg,type="response")

> data2.eg