Modelling and Forecasting Dynamic VAR Thresholds for Risk Management and Regulation

14 Pages Posted: 24 Aug 2006

See all articles by David E. Allen

David E. Allen

School of Mathematics and Statistics, The University of Sydney; Financial Research Network (FIRN); Department of Finance; School of Business and Law, Edith Cowan University

Michael McAleer

Erasmus University Rotterdam - Erasmus School of Economics, Econometric Institute; Tinbergen Institute; University of Tokyo - Centre for International Research on the Japanese Economy (CIRJE), Faculty of Economics

Bernardo da Veiga

Curtin University - School of Economics and Finance

Date Written: October 2005

Abstract

The paper describes alternative methods of estimating Value-at-Risk (VaR) thresholds based on two calibrated models and three conditional volatility or GARCH models. The five models of volatility are used to estimate and forecast the VaR thresholds of an equally-weighted portfolio, comprising four financial stock indexes, namely S&P500, CAC40, FTSE100 a Swiss market index (SMI). On the basis of the number of (non-)violations of the Basel Accord thresholds, the best performing model is PS-GARCH, followed closely by VARMA-AGARCH, neither of which would lead to the imposition of any penalties. The next best performing threshold forecasts are given by the Portfolio-GARCH and RiskmetricsTM-EWMA models, both of which would have a penalty of 0.5. Not surprisingly, the worst forecasts are obtained from the standard normal method based on historical variances.

Keywords: VaR, Portfolio GARCH, Basel II

JEL Classification: C22, G21

Suggested Citation

Allen, David Edmund and McAleer, Michael and da Veiga, Bernardo, Modelling and Forecasting Dynamic VAR Thresholds for Risk Management and Regulation (October 2005). Available at SSRN: https://ssrn.com/abstract=926270 or http://dx.doi.org/10.2139/ssrn.926270

David Edmund Allen (Contact Author)

School of Mathematics and Statistics, The University of Sydney ( email )

School of Mathematics and Statistics F07
University of Sydney
Sydney, New South Wales 2006
Australia

HOME PAGE: http://www.maths.usyd.edu.au

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Department of Finance ( email )

Taiwan
Taiwan

School of Business and Law, Edith Cowan University

100 Joondalup Drive
Joondalup, WA 6027
Australia

HOME PAGE: http://www.dallenwapty.com

Michael McAleer

Erasmus University Rotterdam - Erasmus School of Economics, Econometric Institute ( email )

Rotterdam
Netherlands

Tinbergen Institute

Rotterdam
Netherlands

University of Tokyo - Centre for International Research on the Japanese Economy (CIRJE), Faculty of Economics

Tokyo
Japan

Bernardo Da Veiga

Curtin University - School of Economics and Finance ( email )

GPO Box U 1987
Perth, Western Australia 6845
Australia

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