Clustering Huge Number of Financial Time Series: A Panel Data Approach With High-Dimensional Predictors and Factor Structures

Tomohiro Ando and Jushan Bai

Journal of the American Statistical Association, 2017, vol. 112, issue 519, 1182-1198

Abstract: This article introduces a new procedure for clustering a large number of financial time series based on high-dimensional panel data with grouped factor structures. The proposed method attempts to capture the level of similarity of each of the time series based on sensitivity to observable factors as well as to the unobservable factor structure. The proposed method allows for correlations between observable and unobservable factors and also allows for cross-sectional and serial dependence and heteroscedasticities in the error structure, which are common in financial markets. In addition, theoretical properties are established for the procedure. We apply the method to analyze the returns for over 6000 international stocks from over 100 financial markets. The empirical analysis quantifies the extent to which the U.S. subprime crisis spilled over to the global financial markets. Furthermore, we find that nominal classifications based on either listed market, industry, country or region are insufficient to characterize the heterogeneity of the global financial markets. Supplementary materials for this article are available online.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (66)

Downloads: (external link)
http://hdl.handle.net/10.1080/01621459.2016.1195743 (text/html)
Access to full text is restricted to subscribers.

Related works:
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:112:y:2017:i:519:p:1182-1198

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

DOI: 10.1080/01621459.2016.1195743

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 ().