2. On each day in the full sample, suppose you are in the morning and don't know the day's return yet, predict the day's return2 using - 1-month moving average (use past 21 observations) - 1-year moving average (use past 252 observations) Hints: Some methods do not apply to some earlier days in the full sample. Please just leave them blank. It should not matter for later procedures. I prefer to have the prediction target and the corresponding predicted value on the same row. But always remember which variable is in what information set. For example, the prediction target and the predicted value are known on what dates respectively? 3. Do the same task with the RiskMetrics model. Repeat the task twice withA = 0.94 (the recommended RiskMetrics parameter) andA = 0.96 (a supposedly less preferred parameter) respectively. Hints: for the first day of the sample, since there is no history yet, put an arbitrary sensible number as the prediction of as a start. Write the general recursive formula from the second day of the sample onward. 4. Now we are about a month 5. Estimate the GARCH model in the full sample