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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
Martin Martens
Dick van Dijk

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Abstract

This article investigates the merits of high-frequency intraday data when forming mean-variance efficient stock 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 as judged by the performance of these portfolios. The optimal sampling frequency ranges between 30 and 65 minutes, considerably lower than the popular five-minute frequency, which typically is motivated by the aim of striking a balance between the variance and bias in covariance matrix estimates due to market microstructure effects such as non-synchronous trading and bid-ask bounce. Bias-correction procedures, based on combining low-frequency and high-frequency covariance matrix estimates and on the addition of leads and lags do not substantially affect the optimal sampling frequency or the portfolio performance. Our findings are also robust to the presence of transaction costs and to the portfolio rebalancing frequency.

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File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/07474930701873333&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
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Article provided by Taylor and Francis Journals in its journal Econometric Reviews.

Volume (Year): 27 (2008)
Issue (Month): 1-3 ()
Pages: 199-229
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Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:199-229

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Related research
Keywords: Bias-correction; High-frequency data; Mean-variance analysis; Realized volatility; Tracking error; Volatility timing;

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References listed on IDEAS
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, School of Economics and Management, University of Aarhus. [Downloadable!]
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