Template-Type: ReDIF-Paper 1.0 Series: Tinbergen Institute Discussion Papers Creation-Date: 2005-10-12 Revision-Date: 2006-01-03 Number: 05-089/4 Author-Name: Michiel de Pooter Author-Email: depooter@few.eur.nl Author-Workplace-Name: Faculty of Economics, Erasmus Universiteit Rotterdam Author-Name: Martin Martens Author-Email: mmartens@few.eur.nl Author-Workplace-Name: Faculty of Economics, Erasmus Universiteit Rotterdam Author-Name: Dick van Dijk Author-Email: djvandijk@few.eur.nl Author-Workplace-Name: Faculty of Economics, Erasmus Universiteit Rotterdam Title: Predicting the Daily Covariance Matrix for S&P 100 Stocks using Intraday Data - But which Frequency to use? Abstract: This discussion paper resulted in a publication in 'Econometric Reviews', 2008, 27, 199-229.

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. Classification-JEL: G11 Keywords: realized volatility; high-frequency data; volatility timing; mean-variance analysis; tracking error File-Url: https://papers.tinbergen.nl/05089.pdf File-Format: application/pdf File-Size: 308867 bytes Handle: RePEc:tin:wpaper:20050089