New Risk Management Findings from Federal University of Rio Grande do Sul Reported (Numerical comparison of multivariate models to forecasting risk…

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New Risk Management Findings from Federal University of Rio Grande do Sul Reported (Numerical comparison of multivariate models to forecasting risk measures)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Research findings on Risk Management are discussed in a new report. According to news reporting from Porto Alegre, Brazil, by VerticalNews journalists, research stated, "We evaluated the performance of multivariate models for forecasting Value at Risk (VaR), Expected Shortfall (ES), and Expectile Value at Risk (EvaR). We used Historical Simulation (HS), Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedastic (DCC-GARCH) and copula methods: Regular copulas, Vine copulas, and Nested Archimedean copulas (NAC)."

The news correspondents obtained a quote from the research from the Federal University of Rio Grande do Sul, "We assessed the performance of the models using Monte Carlo simulations, considering different scenarios, regarding the marginal distributions, correlation, and number of portfolio assets. Numerical results evidenced the accuracy forecasting risk measures are associated with marginal distributions. For a data-generating process where the marginal distribution is Gaussian, Regular and Vine copulas demonstrated better performance. For data generated with Student's t distribution, we verified better performance by NAC."

According to the news reporters, the research concluded: "In addition, we identified the superiority of copula methods over HS and DCC-GARCH, which reduces the model risk."

For more information on this research see: Numerical comparison of multivariate models to forecasting risk measures. Risk Management-Journal of Risk Crisis and Disaster, 2018;20(1):29-50. Risk Management-Journal of Risk Crisis and Disaster can be contacted at: Palgrave Macmillan Ltd, Brunel Rd Bldg, Houndmills, Basingstoke RG21 6XS, Hants, England.

Our news journalists report that additional information may be obtained by contacting F.M. Muller, Univ Fed Rio Grande do Sul, Sch Business, BR-90010460 Porto Alegre, RS, Brazil.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1057/s41283-017-0026-8. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

Keywords for this news article include: Porto Alegre, Brazil, South America, Risk Management, Federal University of Rio Grande do Sul.