Predicting the Daily Covariance Matrix for S&P 100 Stocks using Intraday Data - But which Frequency to use?

Preprint
Publisher Website
Google Scholar
  • 1 January 2005
    • preprint
      • Published in RePEc
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.
All Related Versions

This publication has 0 references indexed in Scilit: