Department of Economics and Business Economics

Bootstrapping pre-averaged realized volatility under market microstructure noise

Research output: Working paperResearch


  • rp13_28

    Submitted manuscript, 672 KB, PDF document

  • Ulrich Hounyo, Oxford-Man Institute of Quantitative Finance
  • ,
  • Sílvia Goncalves , Université de Montréal
  • ,
  • Nour Meddahi, Toulouse School of Economics
The main contribution of this paper is to propose a bootstrap method for inference on integrated volatility based on the pre-averaging approach of Jacod et al. (2009), where the pre-averaging is done over all possible overlapping blocks of consecutive observations. The overlapping nature of the pre-averaged returns implies that these are kn-dependent with kn growing slowly with the sample size n. This motivates the application of a blockwise bootstrap method. We show that the "blocks of blocks" bootstrap method suggested by Politis and Romano (1992) (and further studied by Bühlmann and Künsch (1995)) is valid only when volatility is constant. The failure of the blocks of blocks bootstrap is due to the heterogeneity of the squared pre-averaged returns when volatility is stochastic. To preserve both the dependence and the heterogeneity of squared pre-averaged returns, we propose a novel procedure that combines the wild bootstrap with the blocks of blocks bootstrap. We provide a proof of the first order asymptotic validity of this method for percentile intervals. Our Monte Carlo simulations show that the wild blocks of blocks bootstrap improves the finite sample properties of the existing first order asymptotic theory. We use empirical work to illustrate its use in practice.
Original languageEnglish
Place of publicationAarhus
PublisherCREATES, Institut for Økonomi, Aarhus Universitet
Number of pages37
Publication statusPublished - 9 Sep 2013
SeriesCREATES Research Papers

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