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A multivariate FGD technique to improve VaR computation in equity markets

Audrino, Francesco ; Barone-Adesi, Giovanni

In: Computational management science, 2005, vol. 2, no. 2, p. 87-106

It is difficult to compute Value-at-Risk (VaR) using multivariate models able to take into account the dependence structure between large numbers of assets and being still computationally feasible. A possible procedure is based on functional gradient descent (FGD) estimation for the volatility matrix in connection with asset historical simulation. Backtest analysis on simulated and real data...

A multivariate FGD technique to improve VaR computation in equity markets

Audrino, Francesco ; Barone-Adesi, Giovanni

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...