Fat-Tailed Models for Risk Estimation
Posted: 26 Feb 2011
Date Written: December 20, 2010
In the post-crisis era, financial institutions seem to be more aware of the risks posed by extreme events. Even though there are attempts to adapt methodologies drawing from the vast academic literature on the topic, there is also skepticism that fat-tailed models are needed. In this paper, we address the common criticism and discuss three popular methods for extreme risk modeling based on full distribution modeling and and extreme value theory.
Keywords: Fat-Tailed Distributions, Tempered Stable Distributions, Extreme Value Theory, Student's T Distribution, Risk Measurement
JEL Classification: C16, G11
Suggested Citation: Suggested Citation
Stoyanov, Stoyan Veselinov and Rachev, Svetlozar and Racheva-Iotova, Boryana and Fabozzi, Frank J., Fat-Tailed Models for Risk Estimation (December 20, 2010). Journal of Portfolio Management, Vol. 37, No. 2, 2011, Available at SSRN: https://ssrn.com/abstract=1729040
Do you have a job opening that you would like to promote on SSRN?
Feedback to SSRN
If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday.