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dc.contributor.authorPincheira, Pablo
dc.contributor.authorHardy, Nicolás
dc.contributor.authorMuñoz, Felipe
dc.date.accessioned2021-12-20T11:51:30Z
dc.date.available2021-12-20T11:51:30Z
dc.date.issued2021
dc.identifier.citationPincheira, P., Hardy, N., & Muñoz, F. (2021). “Go Wild for a While!”: A New Test for Forecast Evaluation in Nested Models. Mathematics, 9(18), 2254.es
dc.identifier.issn2227-7390
dc.identifier.otherhttps://doi.org/10.3390/math9182254
dc.identifier.urihttp://hdl.handle.net/20.500.12254/2164
dc.description.abstractIn this paper, we present a new asymptotically normal test for out-of-sample evaluation in nested models. Our approach is a simple modification of a traditional encompassing test that is commonly known as Clark and West test (CW). The key point of our strategy is to introduce an independent random variable that prevents the traditional CW test from becoming degenerate under the null hypothesis of equal predictive ability. Using the approach developed by West (1996), we show that in our test, the impact of parameter estimation uncertainty vanishes asymptotically. Using a variety of Monte Carlo simulations in iterated multi-step-ahead forecasts, we evaluated our test and CW in terms of size and power. These simulations reveal that our approach is reasonably well-sized, even at long horizons when CW may present severe size distortions. In terms of power, results were mixed but CW has an edge over our approach. Finally, we illustrate the use of our test with an empirical application in the context of the commodity currencies literaturees
dc.language.isoen_USes
dc.publisherMDPIes
dc.relation.ispartofseriesMathematics;9(18)
dc.rightsAtribución-NoComercial-CompartirIgual 3.0 Chile (CC BY-NC-SA 3.0 CL)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/cl/
dc.subject.otherForecastinges
dc.subject.otherRandom walkes
dc.subject.otherOut-of-samplees
dc.subject.otherPredictiones
dc.subject.otherMean square prediction errores
dc.title“Go Wild for a While!”: A New Test for Forecast Evaluation in Nested Models.es
dc.typeArtículoes


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Atribución-NoComercial-CompartirIgual 3.0 Chile (CC BY-NC-SA 3.0 CL)
Except where otherwise noted, this item's license is described as Atribución-NoComercial-CompartirIgual 3.0 Chile (CC BY-NC-SA 3.0 CL)