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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

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    Title
    • A multivariate FGD technique to improve VaR computation in equity markets
    Author
    • Audrino, Francesco. Institute of Finance, University of Lugano, USI, Via G. Buffi 13, 6900, Lugano, Switzerland
    • Barone-Adesi, Giovanni. Institute of Finance, University of Lugano, USI, Via G. Buffi 13, 6900, Lugano, Switzerland
    Document Type
    • Postprint
    Classification
    • Economics
    OAI-PMH Identifier
    • oai:doc.rero.ch:314303
    Summary
    Abstract.: 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 provides strong empirical evidence of the better predictive ability of the proposed procedure over classical filtered historical simulation, with a resulting significant improvement in the measurement of risk