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Fat-tailed models for risk estimation

Author

Listed:
  • Stoyanov, Stoyan V.
  • Rachev, Svetlozar T.
  • Racheva-Iotova, Boryana
  • Fabozzi, Frank J.

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.

Suggested Citation

  • Stoyanov, Stoyan V. & Rachev, Svetlozar T. & Racheva-Iotova, Boryana & Fabozzi, Frank J., 2011. "Fat-tailed models for risk estimation," Working Paper Series in Economics 30, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    • Handle: RePEc:zbw:kitwps:30
    DOI: 10.5445/IR/1000023244
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    References listed on IDEAS

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    1. Shin Kim, Young & Rachev, Svetlozar T. & Leonardo Bianchi, Michele & Fabozzi, Frank J., 2010. "Tempered stable and tempered infinitely divisible GARCH models," Journal of Banking & Finance, Elsevier, vol. 34(9), pages 2096-2109, September.
    2. Stoyanov, Stoyan V. & Rachev, Svetlozar T. & Fabozzi, Frank J., 2013. "CVaR sensitivity with respect to tail thickness," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 977-988.
    3. Kanamura, Takashi & Rachev, Svetlozar T. & Fabozzi, Frank J., 2011. "A profit model for spread trading with an application to energy futures," Working Paper Series in Economics 27, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
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