dc.creatorFernández, Viviana
dc.date2014-07-31T21:25:18Z
dc.date2014-07-31T21:25:18Z
dc.date2003
dc.date.accessioned2018-04-19T21:04:17Z
dc.date.available2018-04-19T21:04:17Z
dc.identifierRevista de Análisis Económico 18(1): 2003, p. 57-85
dc.identifier0716-5927
dc.identifiereISSN 0718-8870
dc.identifier
dc.identifierhttp://repositorio.uahurtado.cl/handle/11242/1776
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1370800
dc.descriptionValue at Risk (VaR) is a measure of the maximum potential change in value of a portfolio of financial assets with a given probability over a given time horizon. VaR became a key measure of market risk since the Basle Committee stated that banks should be able to cover losses on their trading portfolios over a ten-day horizon, 99 percent of the time. A common practice is to compute VaR by assuming that changes in value of the portfolio are normally distributed, conditional on past in-formation. However, assets returns usually come from fat-tailed distri-butions. Therefore, computing VaR under the assumption of conditional normality can be an important source of error. We illustrate this point with Chilean and U.S. returns series by resorting to extreme value theory (EVT) and GARCH-type models. In addition, we show that dynamic estimation of empirical quantiles can also give more accurate VaR estimates than quantiles of a standard normal.
dc.languageeng
dc.publisherILADES; Georgetown University; Universidad Alberto Hurtado. Facultad de Economía y Negocios
dc.rightsAttribution 3.0 Unported
dc.rightshttp://creativecommons.org/licenses/by/3.0/
dc.subjectBancos administración
dc.subjectRiesgo (Economía)
dc.titleExtreme Value Theory and Value at Risk
dc.typeArtículos de revistas


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