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dc.contributor.authorLi, Yushu
dc.contributor.authorAndersson, Lars Jonas
dc.PublishedLi Y, Andersson J. A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting. Journal of Forecasting. 2019eng
dc.description.abstractIn this paper, we propose a likelihood ratio based method to evaluate density forecasts which can jointly evaluate the unconditional forecasted distribution and dependence of the outcomes. Unlike the well‐known Berkowitz test, the proposed method does not requires a parametric specification of time dynamics. We compare our method with the method proposed by several other tests and show that our methodology has very high power against both dependence and incorrect forecasting distributions. Moreover, the loss of power, caused by the non‐parametric nature of the specification of the dynamics, is shown to be small compared to Berkowitz test, even when the parametric form of dynamics is correctly specified in the latter method.en_US
dc.rightsAttribution-Non Commercial CC BY-NCeng
dc.subjectdensity forecastingeng
dc.subjectlikelihood ratio testeng
dc.subjectMarkov chaineng
dc.titleA Likelihood Ratio and Markov Chain-Based Method to Evaluate Density Forecastingen_US
dc.typePeer reviewed
dc.typeJournal article
dc.rights.holderCopyright 2019 The Authorsen_US
dc.source.journalJournal of Forecasting
dc.relation.projectNorges forskningsråd: 274569

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Except where otherwise noted, this item's license is described as Attribution-Non Commercial CC BY-NC