This project is a continuation of Problem Set I in computing increasingly rened risk measures and evaluating their Out-Of-Sample performance. Let IS and OOS be the In-Sample and Out-Of-Sample...

This project is a continuation of Problem Set I in computing increasingly rened
risk measures and evaluating their Out-Of-Sample performance. Let IS and OOS
be the In-Sample and Out-Of-Sample periods, respectively.
Part A
1. For the best IS specications 1-3, 4-6 and 7-9 of Problem Set I produce OOS
1-period-ahead forecasts of the 5%, 1% and 0.1% VaRs using:
i. Extreme Value Theory
ii. Filtered Historical Simulations
iii. Filtered Weighted Historical Simulations
2. Produce OOS 1-period-ahead forecasts of the 5%, 1% and 0.1% VaRs using:
iv. Historical Simulations
v. Weighted Historical Simulations
3. Backtest your VaR forecasts i.-v. performing Unconditional Coverage Testing
and Independence Hypothesis Testing.
Part B
1. Produce OOS 20-, 60- and 120-periods-ahead forecasts of the 5%, 1% and
0.1% VaRs for i.-v. and the Gaussian case of Problem Set I.
2. Backtest the 20-, 60- and 120-periods-ahead VaR forecasts.
Part C
1. Produce OOS 1-period-ahead forecasts of the Expected Shortfall for i.-v.
2. Backtest the Expected Shortfall forecasts.
Report
Once you have completed the empirical analysis prepare a technical report dis-
cussing and interpreting your ndings. You should comment, among others, on:
 the performance of the various approaches to VaR
 the performance of the various approaches to Expected Shortfall
 the sensitivity of the two risk measures to the specication/modeling of the
conditional distribution