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

41 Pages Posted: 13 Aug 2015 Last revised: 28 Jul 2016

See all articles by Tomohiro Ando

Tomohiro Ando

University of Melbourne - Melbourne Business School

Jushan Bai

Columbia University

Date Written: August 11, 2015

Abstract

This paper 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 risk factors as well as to the unobservable factor structure, which is group specific. The proposed method allows for correlations between observable and unobservable factors and also allows for cross-sectional and serial dependence and heteroskedasticities 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 6,000 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 complexity of the global financial markets.

Keywords: Clustering; Factor structure; Heterogeneous panel; Lasso; Serial and cross-sectional error correlations.

JEL Classification: C23; C55

Suggested Citation

Ando, Tomohiro and Bai, Jushan, Clustering Huge Number of Financial Time Series: A Panel Data Approach with High-Dimensional Predictors and Factor Structures (August 11, 2015). 28th Australasian Finance and Banking Conference, Available at SSRN: https://ssrn.com/abstract=2642526 or http://dx.doi.org/10.2139/ssrn.2642526

Tomohiro Ando (Contact Author)

University of Melbourne - Melbourne Business School ( email )

200 Leicester Street
Carlton, Victoria 3053 3186
Australia

Jushan Bai

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

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