1. Consider the price time series for the Amazon stock {AMEN}. The sample period is from January 2, 2W4 to May 19, 2131?. The data can be downloaded from 'r'ahoo via the quantmod package. Use the {adjusted} closing prices to compute the daily log returns. For the 'v'aFt calculations, assume that you hold the stock valued at $1 million {long position). {a}. Calculate the Val? of your position for the next trading day using the RiskMetrics method on May 19, 201?. You must estimate the corresponding lGARCHt1,1}I model. What is the associated expected shortfall? Also, what is the Val? for the next 10 trading days? {b}. Build a GARCHII1,1]I model for the log return series with Gaussian innovations. What is the 'v'aR based on the fitted model for the next trading day? What is the corresponding expected shortfall? {c}. Build a GARCHf1,1l model with Studentt innovations for the log return series. What is the VaRfor the next trading dayr based on the fitted model? What is the corresponding expected shortfall? 2. Consider the tickbytick trade data of Starbucks stock from December 20 to December 31, 2014. The data are in the le taqtsbuxdecZU312314btt. {a}. Use the data within the normal trading hours only, i.e. from 9:30 am to 4:00 pm Eastern time, to construct a series of intraday 5minute log returns. If there is no trading within a 5minute interval, assume that the log return is zero. If there are multiple trades in a 5-minute interval, use the last trade to obtain the price for that interval. Plot the log return series. {b}. Are there any serial correlations in the intra-dayr 5-minute log return series? Use Gilt)! to perform the test. {c}. Use 5-minute intraday log returns to compute the realized volatility for each of the trading days. {d}. Use 1minute intraday log returns to compute the realized volatility for each of the trading days. 3. Again, consider the tickby-tick trade data of Starbucks from December 20 to December 31, 2014