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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)

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

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G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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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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