Dovonon, Prosper and Goncalves, Silvia and Meddahi, Nour (2010): Bootstrapping realized multivariate volatility measures.

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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 BarndorffNielsen 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 firstorder 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.
Item Type:  MPRA Paper 

Original Title:  Bootstrapping realized multivariate volatility measures 
Language:  English 
Keywords:  Realized regression, realized beta, realized correlation, bootstrap, Edgeworth expansions 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C15  Statistical Simulation Methods: General C  Mathematical and Quantitative Methods > C0  General > C01  Econometrics 
Item ID:  40123 
Depositing User:  Prosper Dovonon 
Date Deposited:  18 Jul 2012 10:04 
Last Modified:  28 Sep 2019 04:09 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/40123 