A regime-switching approach to model-based stress testing
Adam P. Tashman Department of Statistics and Applied Probability, South Hall 5517, University of California Santa Barbara, Santa Barbara, CA 93106-3110; email: tashman@pstat.ucsb.edu
The current financial marketplace has seen the development of increasingly complex products and thus, proper risk management has become a challenging task. Accurate stress testing relies upon models that capture their essential features. Novel, powerful ideas have emerged regarding the dynamics of financial instruments, such as incorporating mechanisms to model regime-switching and non-linearity. This paper outlines the logistic mixture of the linear components (LMLC) model and illustrates how it can be used to perform stress testing on an asset that follows regimeswitching dynamics. Once the model is estimated, running a stress test is straightforward; expected loss estimates are produced from the fitting equation. A market stress test is run on a merger arbitrage hedge fund position. It is demonstrated that the LMLC stress test produces expected loss estimates that are more conservative than estimates produced from a linear factor model.
What to do if you do not know your username and password:
• If you are a The Journal of Risk Model Validation subscriber, click here and we will email you straight away with your username and password.
What to do if you are not a The Journal of Risk Model Validation subscriber:
The Risk Books and Journals group on is where editors, authors and readers can launch discussions about published and forthcoming books.
Click here to read these discussions and become part of the Risk Books and Journals group.
Login
