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Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data - But Which Frequency to Use?

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Author Info

  • Michiel de Pooter

    ()
    (Faculty of Economics, Erasmus Universiteit Rotterdam)

  • Martin Martens

    ()
    (Faculty of Economics, Erasmus Universiteit Rotterdam)

  • Dick van Dijk

    ()
    (Faculty of Economics, Erasmus Universiteit Rotterdam)

Abstract

This paper investigates the merits of high-frequency intraday data when forming minimum variance portfolios and minimum tracking error portfolios with daily rebalancing from the individual constituents of the S&P 100 index. We focus on the issue of determining the optimal sampling frequency, which strikes a balance between variance and bias in covariance matrix estimates due to market microstructure effects such as non-synchronous trading and bid-ask bounce. The optimal sampling frequency typically ranges between 30- and 65-minutes, considerably lower than the popular five-minute frequency. We also examine how bias-correction procedures, based on the addition of leads and lags and on scaling, and a variance-reduction technique, based on subsampling, affect the performance.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 05-089/4.

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Date of creation: 12 Oct 2005
Date of revision: 03 Jan 2006
Handle: RePEc:dgr:uvatin:20050089

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Web page: http://www.tinbergen.nl

Related research

Keywords: realized volatility; high-frequency data; volatility timing; mean-variance analysis; tracking error;

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