Forward-looking tail risk measures


Huggenberger, Markus ; Zhang, Chu ; Zhou, Ti



DOI: https://doi.org/10.2139/ssrn.2909808
URL: https://ssrn.com/abstract=2909808
Document Type: Working paper
Year of publication: 2017
The title of a journal, publication series: SSRN Working Paper Series
Place of publication: Rochester, NY
Edition: Rev. 17 June 2018
Publication language: English
Institution: Business School > ABWL, Risikotheorie, Portfolio Management u. Versicherungswissenschaft (Albrecht)
Subject: 330 Economics
Abstract: We present an analytical framework for the forward-looking measurement of extreme market risk. In contrast to standard techniques relying on past return data, we propose to extract Value-at-Risk and Expected Shortfall under the physical measure from current option prices. Our empirical evidence suggests that the resulting estimates accurately capture the tail risk of the S&P 500 and that they quickly react to changing market conditions. Compared to dynamic tail risk forecasts driven by past returns, our forward-looking estimates are relatively higher during good times and lower during adverse economic conditions, which could reduce the amplification effects of conventional dynamic risk management policies.

Dieser Eintrag ist Teil der Universitätsbibliographie.




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Huggenberger, Markus ; Zhang, Chu ; Zhou, Ti (2017) Forward-looking tail risk measures. SSRN Working Paper Series Rochester, NY [Working paper]


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