Analyzing risk measures using the cdf developed by GJR-GARCH and t-copula model

2 views (last 30 days)
Hello everyone, I am working to optimize the portfolio weights using Distortion Risk Measures (Wang Transform, Proportional Hazard, Beta Transform, etc). For it what I thought to do was to simulate the market data using GJR-GARCH and t-copula. I did the required the changes for it in the given example:https://in.mathworks.com/help/econ/using-extreme-value-theory-and-copulas-to-evaluate-market-risk.html;jsessionid=e6f917d4745f10c39b6c23a06cb9
The problem I am facing is the output of the copula model is an array of doubles, but to use the distribution is the optimization problem I will need a function to integerate and perform the required mathematical operations.
How can I move forward, should I try to get the distribution using GJR-GARCH and Copula in a different format.
Please suggest what can I do.
You can find more about the distortion risk measures on page 42 of this work
Thanks a lot

Answers (0)

Categories

Find more on Probability Distributions and Hypothesis Tests in Help Center and File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!