Department of Economics and Business Economics

Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns

Research output: Working paperResearch

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  • Rp13 07

    Submitted manuscript, 806 KB, PDF document

  • Sílvia Gonçalves, Université de Montréal, Canada
  • Ulrich Hounyo, University of Oxford , United Kingdom
  • Nour Meddahi, Toulouse School of Economics, France
The main contribution of this paper is to propose bootstrap methods for realized volatility-like estimators defined on pre-averaged returns. In particular, we focus on the pre-averaged realized volatility estimator proposed by Podolskij and Vetter (2009). This statistic can be written (up to a bias correction term) as the (scaled) sum of squared pre-averaged returns, where the pre-averaging is done over all possible non-overlapping blocks of consecutive observations. Pre-averaging reduces the influence of the noise and allows for realized volatility estimation on the pre-averaged returns. The non-overlapping nature of the pre-averaged returns implies that these are asymptotically independent, but possibly heteroskedastic. This motivates the application of the wild bootstrap in this context. We provide a proof of the first order asymptotic validity of this method for percentile and percentile-t intervals. Our Monte Carlo simulations show that the wild bootstrap can improve the finite sample properties of the existing first order asymptotic theory provided we choose the external random variable appropriately. We use empirical work to illustrate its use in practice.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages22
Publication statusPublished - 11 Mar 2013
SeriesCREATES Research Papers
Number2013-7

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