Cross-sectional dependence in idiosyncratic volatility

Ilze Kalnina and Kokouvi Tewou

Cahiers de recherche from Universite de Montreal, Departement de sciences economiques

Abstract: This paper introduces a framework for analysis of cross-sectional dependence in the idiosyncratic volatilities of assets using high frequency data. We first consider the estimation of standard measures of dependence in the idiosyncratic volatilities such as covariances and correlations. Next, we study an idiosyncratic volatility factor model, in which we decompose the co-movements in idiosyncratic volatilities into two parts: those related to factors such as the market volatility, and the residual co-movements. When using high frequency data, naive estimators of all of the above measures are biased due to the estimation errors in idiosyncratic volatility. We provide bias-corrected estimators and establish their asymptotic properties. We apply our estimators to high-frequency data on 27 individual stocks from nine different sectors, and document strong cross-sectional dependence in their idiosyncratic volatilities. We also find that on average 74% of this dependence can be explained by the market volatility.

Keywords: High frenquency data; Idiosyncratic volatility; Factor structure; Cross-sectional returns (search for similar items in EconPapers)
JEL-codes: C14 C22 (search for similar items in EconPapers)
Pages: 59 pages
Date: 2015
New Economics Papers: this item is included in nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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http://hdl.handle.net/1866/12689 (application/pdf)

Related works:
Working Paper: Cross-sectional Dependence in Idiosyncratic Volatility (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:mtl:montde:2015-04

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