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Modelling (and forecasting) extremes in time series: A naive approach

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Resumo:In Extreme Value Theory, we are essentially interested in the estimation of quantities related to extreme events. Whenever the focus is in large values, estimation is usually performed based on the largest k order statistics in the sample or on the excesses over a high level u. Here we are interested in modelling (and forecast- ing) extremes in time series. For modelling and forecasting classical time series, Boot.EXPOS is a computational procedure built in the R environment that has revealed to perform quite well in a large number of forecasting competitions. However, to deal with extreme values, a modification of that algorithm needs to be considered and is here under study
Autores principais:Neves, M.Manuela
Outros Autores:Cordeiro, Clara
Assunto:extreme value theory extremal index estimation re-sampling procedures; time series
Ano:2020
País:Portugal
Tipo de documento:documento de conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade de Lisboa
Idioma:inglês
Origem:Repositório da Universidade de Lisboa

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