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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Tinbergen Institute Discussion Paper ; No. 05-089/4

Classification and Topics

• Classification: Wirtschaft ; Portfolio Choice; Investment Decisions
• Subject: realized volatility ; high-frequency data ; volatility timing ; mean-variance analysis ; tracking error

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): de Pooter, Michiel ; Martens, Martin ; van Dijk, Dick
• Event: Veröffentlichung
• (who): Tinbergen Institute
• (where): Amsterdam and Rotterdam
• (when): 2005

Further information

• Handle: http://hdl.handle.net/10419/86328
• Last update: 10.03.2025, 11:43 AM CET