1. Value at Risk (VaR) In this exercise, we will use the same framework we used in the teamwork in Module 1, but instead of using the historical simulation method to compute the VaR, we will consider a framework incorporating a variance forecasting model such as the RiskMetrics. We will consider a trader that has a risk limit given by a 10day, 1% Sm (or SVaRgfm) equal to $100,000. This means that, on each day, her position should respect the following limit $Position ac VaRgfm 5 $100,000 Now, let's assume that: 1) The trader only invests in the 5&P500 Index; 2) The trader computes the 10day VaR by simply rescaling the 1day m by v10; 3) The trader, on each day, invests the maximum amount of money possible, that is, she chooses how much money to invest (i.e., her position) such that: . . $1odooo $Pos:tton = W. \"Ra 10 Question: 1) Use the data below to compute the VaRgfm using a model in which the innovation term is distributed as a standard normal and the variance is given by the RiskMetrics model, thatis: Rt+1 = Ut+1zt+1 Where Zt+1~N(0,1) and 61524.1 = [10"? + (1 _ 11)th Hint: Estimate the RiskMetrics mode! on the full sample. \f