A Multivariate Fgd Technique to Improve VAR Computation in Equity Markets

30 Pages Posted: 15 Jan 2003

See all articles by Francesco Audrino

Francesco Audrino

University of St. Gallen; Swiss Finance Institute

Giovanni Barone-Adesi

University of Lugano; Swiss Finance Institute

Date Written: September 2002

Abstract

We present a multivariate, non-parametric technique for constructing reliable daily VaR predictions for individual assets belonging to a common equity market segment, which takes also into account the possible dependence structure between the assets and is still computationally feasible in large dimensions. The procedure is based on functional gradient descent (FGD) estimation for the volatility matrix (Audrino and Bühlmann, 2002) in connection with asset historical simulation and can also be seen as a multivariate extension of the filtered historical simulation method proposed by Barone-Adesi et al. (1998). Our FGD algorithm is very general and can be further adapted to other multivariate problems dealing with (volatility) function estimation. We concentrate our empirical investigations on the Swiss pharmaceutical and the US biotechnological equity market and we collect, using statistical and economical backtests, strong empirical evidence of the better predictive potential of our multivariate strategy over other univariate techniques, with a resulting significant improvement in the measurement of risk.

Keywords: Volatility estimation, Filtered Historical Simulation, Value-at-Risk

JEL Classification: C14, C19

Suggested Citation

Audrino, Francesco and Barone-Adesi, Giovanni, A Multivariate Fgd Technique to Improve VAR Computation in Equity Markets (September 2002). Available at SSRN: https://ssrn.com/abstract=363740 or http://dx.doi.org/10.2139/ssrn.363740

Francesco Audrino (Contact Author)

University of St. Gallen ( email )

Bodanstrasse 6
St. Gallen, CH-9000
Switzerland

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Giovanni Barone-Adesi

University of Lugano ( email )

Via Buffi 13
CH-6904 Lugano
Switzerland
+41 58 666 4671 (Phone)
+41 58 666 46 47 (Fax)

Swiss Finance Institute

c/o University of Geneva
40 Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland