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Asymmetric Realized Volatility Risk

School of Mathematics and Statistics, University of Sydney, and Centre for Applied Financial Studies,UniSA Business School, University of South Australia, Adelaide SA 5000, Australia
Department of Quantitative Finance, National Tsing Hua University, Taichung 402, Taiwan
Econometric Institute, Erasmus University Rotterdam, Rotterdam 3000, The Netherlands
Tinbergen Institute, Rotterdam 3000, The Netherlands
Department of Quantitative Economics, Complutense University of Madrid, Madrid 28040, Spain
Australian School of Business, University of New South Wales, Sydney NSW 2052, Australia
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2014, 7(2), 80-109;
Received: 4 April 2014 / Revised: 23 May 2014 / Accepted: 23 June 2014 / Published: 25 June 2014
(This article belongs to the Collection Feature Papers of JRFM)
PDF [579 KB, uploaded 25 June 2014]


In this paper, we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly Gaussian, this unpredictability brings considerably more uncertainty to the empirically relevant ex ante distribution of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility model, which incorporates the fact that realized volatility series are systematically more volatile in high volatility periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed account of the empirical advantages of the model using data on the S&P 500 index and eight other indexes and stocks. View Full-Text
Keywords: realized volatility; volatility of volatility; volatility risk; value-at-risk; forecasting; conditional heteroskedasticity realized volatility; volatility of volatility; volatility risk; value-at-risk; forecasting; conditional heteroskedasticity

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Allen, D.E.; McAleer, M.; Scharth, M. Asymmetric Realized Volatility Risk. J. Risk Financial Manag. 2014, 7, 80-109.

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