Fat-Tailed Models for Risk Estimation
- 31 January 2011
- journal article
- Published by With Intelligence LLC in The Journal of Portfolio Management
- Vol. 37 (2), 107-117
- https://doi.org/10.3905/jpm.2011.37.2.107
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 article, the authors address the common criticism and discuss three popular methods for extreme risk modeling based on full distribution modeling and extreme value theory.Keywords
This publication has 22 references indexed in Scilit:
- Do financial returns have finite or infinite variance? A paradox and an explanationQuantitative Finance, 2010
- Tempered infinitely divisible distributions and processesTeoriya Veroyatnostei I Ee Primeneniya, 2010
- Non-Normality of Market Returns: A Framework for Asset Allocation Decision MakingThe Journal of Alternative Investments, 2009
- Improved Estimates of Higher-Order Comoments and Implications for Portfolio SelectionThe Review of Financial Studies, 2009
- Financial market models with Lévy processes and time-varying volatilityJournal of Banking & Finance, 2008
- Tail Risk ManagementThe Journal of Portfolio Management, 2008
- Beyond Value at Risk: Forecasting Portfolio Loss at Multiple HorizonsSSRN Electronic Journal, 2007
- A Gentle Introduction to the RM2006 MethodologySSRN Electronic Journal, 2007
- Mandelbrot and the Stable Paretian HypothesisThe Journal of Business, 1963
- The Variation of Certain Speculative PricesThe Journal of Business, 1963