Computation of Portfolio VaRs with GARCH-Type Volatility

Posted: 2 Apr 2013

See all articles by Dinghai Xu

Dinghai Xu

Independent

Tony S. Wirjanto

University of Waterloo - School of Accounting and Finance; University of Waterloo, Department of Statistics & Actuarial Science

Date Written: March 1, 2013

Abstract

In this paper, we explore the use of Independent Component Analysis (ICA) from the field of signal processing to model and estimate the dynamics of multivariate volatilities of financial asset returns in the GARCH framework. The resulting ICA-GARCH approach is shown to provide a computationally tractable method for constructing Value at Risk (VaR) of portfolios consisting of a large number of assets that are typically characterized by nonlinearity and nonnormality. In addition, it is also shown to be effective in capturing the time-varying features of volatilities and is more stable than other comparable models.

Keywords: Multivariate Models, Independent Component Analysis, Principal Component Analysis, GARCH, Value at Risk

JEL Classification: C22, C53, G17

Suggested Citation

Xu, Dinghai and Wirjanto, Tony S., Computation of Portfolio VaRs with GARCH-Type Volatility (March 1, 2013). Available at SSRN: https://ssrn.com/abstract=2242929

Dinghai Xu

Independent ( email )

Tony S. Wirjanto (Contact Author)

University of Waterloo - School of Accounting and Finance ( email )

200 University Avenue West
Waterloo, Ontario N2L 3G1
Canada
519-888-4567 x35210 (Phone)

HOME PAGE: http://https://uwaterloo.ca/statistics-and-actuarial-science/people-profiles/tony-wirjanto

University of Waterloo, Department of Statistics & Actuarial Science ( email )

200 University Avenue West
Waterloo, Ontario N2L 3G1
Canada
519-888-4567 x35210 (Phone)
519-746-1875 (Fax)

HOME PAGE: http://math.uwaterloo.ca/statistics-and-actuarial-science/people-profiles/tony-wirjanto

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