EconPapers    
Economics at your fingertips  
 

Vast Volatility Matrix Estimation Using High-Frequency Data for Portfolio Selection

Jianqing Fan, Yingying Li and Ke Yu

Journal of the American Statistical Association, 2012, vol. 107, issue 497, 412-428

Abstract: Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of portfolios selection among a vast pool of assets, as demonstrated by Fan, Zhang, and Yu. The required high-dimensional volatility matrix can be estimated by using high-frequency financial data. This enables us to better adapt to the local volatilities and local correlations among a vast number of assets and to increase significantly the sample size for estimating the volatility matrix. This article studies the volatility matrix estimation using high-dimensional, high-frequency data from the perspective of portfolio selection. Specifically, we propose the use of “pairwise-refresh time” and “all-refresh time” methods based on the concept of “refresh time” proposed by Barndorff-Nielsen, Hansen, Lunde, and Shephard for the estimation of vast covariance matrix and compare their merits in the portfolio selection. We establish the concentration inequalities of the estimates, which guarantee desirable properties of the estimated volatility matrix in vast asset allocation with gross-exposure constraints. Extensive numerical studies are made via carefully designed simulations. Comparing with the methods based on low-frequency daily data, our methods can capture the most recent trend of the time varying volatility and correlation, hence provide more accurate guidance for the portfolio allocation in the next time period. The advantage of using high-frequency data is significant in our simulation and empirical studies, which consist of 50 simulated assets and 30 constituent stocks of Dow Jones Industrial Average index.

Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (28) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1080/01621459.2012.656041 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Vast Volatility Matrix Estimation using High Frequency Data for Portfolio Selection (2010) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlasa:v:107:y:2012:i:497:p:412-428

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UASA20

Access Statistics for this article

Journal of the American Statistical Association is currently edited by Xuming He, Jun Liu, Joseph Ibrahim and Alyson Wilson

More articles in Journal of the American Statistical Association from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2019-03-31
Handle: RePEc:taf:jnlasa:v:107:y:2012:i:497:p:412-428