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dc.contributor.authorCai, Lilien
dc.contributor.authorSwanson, Norman R.en
dc.date.accessioned2011-06-14-
dc.date.accessioned2012-06-25T11:57:10Z-
dc.date.available2012-06-25T11:57:10Z-
dc.date.issued2011-
dc.identifier.urihttp://hdl.handle.net/10419/59457-
dc.description.abstractWe review and construct consistent in-sample specification and out-of-sample model selection tests on conditional distributions and predictive densities associated with continuous multifactor (possibly with jumps) and (non)linear discrete models of the short term interest rate. The results of our empirical analysis are used to carry out a horserace; comparing discrete and continuous models across multiple sample periods, forecast horizons, and evaluation intervals. Our evaluation involves comparing models during two distinct historical periods, as well as across our entire weekly sample of Eurodollar deposit rates from 1982-2008. Interestingly, when our entire sample of data is used to estimate competing models, the best performer in terms of distributional fit as well as predictive density accuracy, both in-sample and out-of-sample, is the three factor Chen (CHEN: 1996) model examined by Andersen, Benzoni and Lund (2004). Just as interestingly, a logistic type discrete smooth transition autoregression (STAR) model is preferred to the best continuous model (i.e. the one factor Cox, Ingersoll, and Ross (CIR: 1985) model) when comparing predictive accuracy for the Stable 1990s period that we examine. Moreover, an analogous result holds for the Post 1990s period that we examine, where the STAR model is preferred to a two factor stochastic mean model. Thus, when the STAR model is parameterized using only data corresponding to a particular sub-sample, it outperforms the best continuous alternative during that period. However, when models are estimated using the entire dataset, the continuous CHEN model is preferred, regardless of the variety of model specification (selection) test that is carried out. Given that it is very difficult to ascertain the particular future regime that will ensue when constructing ex ante predictions, thus, the CHEN model is our overall winning; model, regardless of sample period.en
dc.language.isoengen
dc.publisher|aRutgers University, Department of Economics |cNew Brunswick, NJen
dc.relation.ispartofseries|aWorking Paper |x2011-02en
dc.subject.jelC1en
dc.subject.jelC5en
dc.subject.jelG0en
dc.subject.ddc330en
dc.subject.keywordinterest rateen
dc.subject.keywordmulti-factor diffusion processen
dc.subject.keywordspecification testen
dc.subject.keywordout-of-sample forecastsen
dc.subject.keywordconditional distributionen
dc.subject.keywordmodel selectionen
dc.subject.keywordblock bootstrapen
dc.subject.keywordjump processen
dc.subject.stwPrognoseverfahrenen
dc.subject.stwZinsen
dc.subject.stwEuroen
dc.subject.stwUS-Dollaren
dc.subject.stwZeitreihenanalyseen
dc.subject.stwModellierungen
dc.subject.stwTheorieen
dc.titleIn- and out-of-sample specification analysis of spot rate models: Further evidence for the period 1982-2008-
dc.typeWorking Paperen
dc.identifier.ppn662025490en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:rut:rutres:201102en

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