Forward-Looking Tail Risk Measures

67 Pages Posted: 1 Feb 2017 Last revised: 17 Jun 2018

See all articles by Markus Huggenberger

Markus Huggenberger

University of Mannheim - Department of Risk Theory, Portfolio Management and Insurance

Chu Zhang

Hong Kong University of Science & Technology (HKUST) - Department of Finance

Ti Zhou

Southern University of Science and Technology-Department of Finance

Date Written: June 5, 2018

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.

Keywords: Tail Risk, Options, Risk Management, Value-at-Risk, Expected Shortfall

JEL Classification: G12, G20, G31

Suggested Citation

Huggenberger, Markus and Zhang, Chu and Zhou, Ti, Forward-Looking Tail Risk Measures (June 5, 2018). Available at SSRN: https://ssrn.com/abstract=2909808 or http://dx.doi.org/10.2139/ssrn.2909808

Markus Huggenberger

University of Mannheim - Department of Risk Theory, Portfolio Management and Insurance ( email )

Schloss
D-68131 Mannheim
Germany

Chu Zhang

Hong Kong University of Science & Technology (HKUST) - Department of Finance ( email )

Clear Water Bay, Kowloon
Hong Kong

Ti Zhou (Contact Author)

Southern University of Science and Technology-Department of Finance ( email )

Department of Finance
Southern University of Science and Technology
Shenzhen, Guangdong 518000
China
+8675588018610 (Phone)

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