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Journal article

A multivariate FGD technique to improve VaR computation in equity markets

  • Audrino, Francesco Istituto di finanza (IFin), Facoltà di scienze economiche, Università della Svizzera italiana, Svizzera
  • Barone-Adesi, Giovanni Istituto di finanza (IFin), Facoltà di scienze economiche, Università della Svizzera italiana, Svizzera
    2003
Published in:
  • Computational management science. - Springer. - 2005, vol. 2, no. 2, p. 87-106
Volatility estimation
functional gradient descent
filtered historical simulation
value-at-risk
English 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.
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  • English
Classification
Economics
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https://n2t.net/ark:/12658/srd1318393
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