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Publication details

Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility

Journal Article

Žikeš F., Baruník Jozef

serial: Journal of Financial Econometrics vol.14, 1 (2016), p. 185-226

project(s): 612955, , GA13-32263S, GA ČR

keywords: conditional quantiles, quantile regression, realized measures, value-at-risk

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abstract (eng):

This paper investigates how the conditional quantiles of future returns and volatility of financial assets vary with various measures of ex post variation in asset prices as well as option-implied volatility. We work in the flexible quantile regression framework and rely on recently developed model-free measures of integrated variance, upside and downside semivariance, and jump variation. Our results for the S&P 500 and WTI Crude Oil futures contracts show that simple linear quantile regressions for returns and heterogenous quantile autoregressions for realized volatility perform very well in capturing the dynamics of the respective conditional distributions, both in absolute terms as well as relative to a couple of well-established benchmark models. The models can therefore serve as useful risk management tools for investors trading the futures contracts themselves or various derivative contracts written on realized volatility.


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Last modification: 21.12.2012
Institute of Information Theory and Automation