Fat-Tailed Models for Risk Estimation

Posted: 26 Feb 2011

See all articles by Stoyan V. Stoyanov

Stoyan V. Stoyanov

Stony Brook University

Svetlozar Rachev

Texas Tech University

Boryana Racheva-Iotova

affiliation not provided to SSRN

Frank J. Fabozzi

EDHEC Business School

Date Written: December 20, 2010

Abstract

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

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

Stoyan Veselinov Stoyanov (Contact Author)

Stony Brook University ( email )

306 Harriman Hall
Stony Brook, NY 11794
United States

Svetlozar Rachev

Texas Tech University ( email )

Dept of Mathematics and Statistics
Lubbock, TX 79409
United States
631-662-6516 (Phone)

Boryana Racheva-Iotova

affiliation not provided to SSRN ( email )

Frank J. Fabozzi

EDHEC Business School ( email )

France
215 598-8924 (Phone)

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