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A Functional Filtering and Neighborhood Truncation Approach to Integrated Quarticity Estimation

  • Torben G. Andersen

    ()

    (Northwestern University, NBER, and CREATES)

  • Dobrislav Dobrev

    ()

    (Federal Reserve Board of Governors)

  • Ernst Schaumburg

    ()

    (Federal Reserve Bank of New York)

We provide a first in-depth look at robust estimation of integrated quarticity (IQ) based on high frequency data. IQ is the key ingredient enabling inference about volatility and the presence of jumps in financial time series and is thus of considerable interest in applications. We document the significant empirical challenges for IQ estimation posed by commonly encountered data imperfections and set forth three complementary approaches for improving IQ based inference. First, we show that many common deviations from the jump diffusive null can be dealt with by a novel filtering scheme that generalizes truncation of individual returns to truncation of arbitrary functionals on return blocks. Second, we propose a new family of efficient robust neighborhood truncation (RNT) estimators for integrated power variation based on order statistics of a set of unbiased local power variation estimators on a block of returns. Third, we find that ratio-based inference, originally proposed in this context by Barndorff-Nielsen and Shephard (2002), has desirable robustness properties in the face of regularly occurring data imperfections and thus is well suited for our empirical applications. We confirm that the proposed filtering scheme and the RNT estimators perform well in our extensive simulation designs and in an application to the individual Dow Jones 30 stocks.

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File URL: ftp://ftp.econ.au.dk/creates/rp/11/rp11_23.pdf
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Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2011-23.

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Length: 67
Date of creation: 29 May 2011
Date of revision:
Handle: RePEc:aah:create:2011-23
Contact details of provider: Web page: http://www.econ.au.dk/afn/

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  1. Barndorff-Nielsen, Ole Eiler & Graversen, Svend Erik & Jacod, Jean & Podolskij, Mark, 2004. "A central limit theorem for realised power and bipower variations of continuous semimartingales," Technical Reports 2004,51, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  2. Neil Shephard, 2004. "A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales," Economics Series Working Papers 2004-FE-21, University of Oxford, Department of Economics.
  3. repec:oxf:wpaper:264 is not listed on IDEAS
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