Portfolio Value at Risk Based on Independent Components Analysis

SFB 649 Discussion Paper 2005-060

25 Pages Posted: 9 Jan 2017

See all articles by Ying Chen

Ying Chen

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Wolfgang K. Härdle

Blockchain Research Center; Xiamen University - Wang Yanan Institute for Studies in Economics (WISE); Charles University; National Yang Ming Chiao Tung University; Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

V. Spokoiny

Weierstras Institute for Applied Analysis and Stochastics (WIAS)

Date Written: December 15, 2005

Abstract

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy tailed distributional properties that are observed in data. A principle component based method (tied closely to the elliptical structure of the distribution) is therefore expected to be unsatisfactory. Here we propose and analyze a technology that is based on Independent Component Analysis (ICA). We study the proposed ICVaR methodology in an extensive simulation study and apply it to a high dimensional portfolio situation. Our analysis yields very accurate VaRs.

Keywords: independent component analysis, Value-at-Risk

JEL Classification: C14, C15, C32, C53, G20

Suggested Citation

Chen, Ying and Härdle, Wolfgang K. and Spokoiny, Vladimir, Portfolio Value at Risk Based on Independent Components Analysis (December 15, 2005). SFB 649 Discussion Paper 2005-060, Available at SSRN: https://ssrn.com/abstract=2894431 or http://dx.doi.org/10.2139/ssrn.2894431

Ying Chen

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Spandauer Strasse 1
Berlin, D-10178
Germany

Wolfgang K. Härdle (Contact Author)

Blockchain Research Center ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 10246
China

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

National Yang Ming Chiao Tung University ( email )

No. 1001, Daxue Rd. East Dist.
Hsinchu City 300093
Taiwan

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Unter den Linden 6
Berlin, D-10099
Germany

Vladimir Spokoiny

Weierstras Institute for Applied Analysis and Stochastics (WIAS) ( email )

Mohrenstr. 39
Berlin, 10117
Germany

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
32
Abstract Views
1,060
PlumX Metrics