Write a brief description of the time series plots of the four series of log returns. Do the series look stationary? Do the fluctuations in the series seem to be of constant size? If not, describe how...

Write a brief description of the time series plots of the four series of log returns. Do the series look stationary? Do the fluctuations in the series seem to be of constant size? If not, describe how the volatility fluctuates.

 In R, data can be stored as a data frame, which does not assume that the data are in time order and would be appropriate, for example, with crosssectional data. To appreciate how plot() works on a data frame rather than on a multivariate time series, run the following code. You will be plotting the same data as before, but they will be plotted in a different way

plot (as.data.frame(logR))

Run the code that follows to create normal plots of the four indices and to test each for normality using the Shapiro–Wilk test. You should understand what each line of code does.

par (mfrow=c(2, 2))

 for(i in colnames(logR))

 { qqnorm(logR[ ,i], datax = T, main = i)

 qqline(logR[ ,i], datax = T)

 print(shapiro.test(logR[ ,i]))