Suppose that the daily log return of a security follows the model rt = 0.01 + 0.2rt2 + at, where {at} is a Gaussian white noise series with mean zero and variance 0.02. What are the mean and variance of the return series rt ? Compute the lag-1 and lag-2 autocorrelations of rt . Assume that r100 = 0.01, and r99 = 0.02. Compute the 1- and 2-step-ahead forecasts of the return series at the forecast origin t = 100. What are the associated standard deviations of the forecast errors? Please use R code to solve this question.