Analytical Value-at-Risk and Expected Shortfall under regime-switching
It is well known that the use of Gaussian models to assess financial risk leads to an underestimation of risk. The reason is because these models are unable to capture some important facts such as heavy tails and volatility clustering which indicate the presence of large fluctuations in returns. An alternative way is to use regime-switching models, the latter are able to capture the previous facts. Using regime-switching model, we propose an analytical approximation for multi-horizon conditional Value-at-Risk and a closed-form solution for conditional Expected Shortfall. By comparing the Value-at-Risks and Expected Shortfalls calculated analytically and using simulations, we find that the both approaches lead to almost the same result. Further, the analytical approach is less time and computer intensive compared to simulations, which are typically used in risk management.
Year of publication: |
2009
|
---|---|
Authors: | Taamouti, Abderrahim |
Published in: |
Finance Research Letters. - Elsevier, ISSN 1544-6123. - Vol. 6.2009, 3, p. 138-151
|
Publisher: |
Elsevier |
Keywords: | Regime-switching Probability distribution Value-at-Risk Expected Shortfall Analytical approximation Closed-form solution Simulation Multi-horizon |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Sovereign credit ratings, market volatility, and financial gains
Afonso, António, (2014)
-
A Better Understanding of Granger Causality Analysis: A Big Data Environment
Song, Xiaojun, (2018)
-
Troster, Victor, (2021)
- More ...