Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility

Filip Žikeš and Jozef Baruník

No 20, FinMaP-Working Papers from Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents

Abstract: 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 exible 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.

Keywords: conditional quantiles; Value-at-Risk; quantile regression; realized measures (search for similar items in EconPapers)
JEL-codes: C14 C21 G17 G32 (search for similar items in EconPapers)
Date: 2014
New Economics Papers: this item is included in nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Related works:
Journal Article: Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility (2016)
Working Paper: Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:fmpwps:20

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