Bootstrapping realized multivariate volatility measures

Prosper Dovonon, Silvia Goncalves () and Nour Meddahi

MPRA Paper from University Library of Munich, Germany

Abstract: We study bootstrap methods for statistics that are a function of multivariate high frequency returns such as realized regression coefficients and realized covariances and correlations. For these measures of covariation, the Monte Carlo simulation results of Barndorff-Nielsen and Shephard (2004) show that finite sample distortions associated with their feasible asymptotic theory approach may arise if sampling is not too frequent. This motivates our use of the bootstrap as an alternative tool of inference for covariation measures. We consider an i.i.d. bootstrap applied to the vector of returns. We show that the finite sample performance of the bootstrap is superior to the existing first-order asymptotic theory. Nevertheless, and contrary to the existing results in the bootstrap literature for regression models subject to heteroskedasticity in the error term, the Edgeworth expansion for the i.i.d. bootstrap that we develop here shows that this method is not second order accurate. We argue that this is due to the fact that the conditional mean parameters of realized regression models are heterogeneous under stochastic volatility.

Keywords: Realized regression; realized beta; realized correlation; bootstrap; Edgeworth expansions (search for similar items in EconPapers)
JEL-codes: C01 C15 (search for similar items in EconPapers)
Date: 2010-07
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Related works:
Journal Article: Bootstrapping realized multivariate volatility measures (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:40123

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