ITBAL-5 on Jan 25

Question 1:

Command:

z<-read.csv(file.choose(),header=T)
Close<-z$Close
Close
Close.ts<-ts(Close)
Close.ts<-ts(Close,deltat= 1/252)
z1<-ts(data=Close.ts[10:95],frequency=1,deltat=1/252)
z1.ts<-ts(z1)
z1.ts
z1.diff<-diff(z1)
z2<-lag(z1.ts,K=-1)
Returns<-z1.diff/z2
plot(Returns,main=" Returns from 10 th to 95th day of NSE Mid-cap Index ")
z3<-cbind(z1.ts,z1.diff,Returns)
plot(z3,main=" Data from 10th-95th day ; Difference ; Returns")

Question 2:

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

Command:

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

z1<-z[1:700,1:9]

head(z1)

z1$ed<-factor(z1$ed)

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

summary(z1.est)

forecast<-z[701:850,1:8]

forecast$ed<-factor(forecast$ed)

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

head(forecast)