Testing the martingale difference hypothesis using integrated regression functions

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dc.contributor.author Escanciano, Juan Carlos
dc.contributor.author Velasco, Carlos
dc.date.accessioned 2009-06-05T15:08:06Z
dc.date.available 2009-06-05T15:08:06Z
dc.date.issued 2006-12
dc.identifier.bibliographicCitation Computational Statistics & Data Analysis. 2006, vol. 51, nº 4, p. 2278-2294
dc.identifier.issn 0167-9473
dc.identifier.uri http://hdl.handle.net/10016/4361
dc.description.abstract An omnibus test for testing a generalized version of the martingale difference hypothesis (MDH) is proposed. This generalized hypothesis includes the usual MDH, testing for conditional moments constancy such as conditional homoscedasticity (ARCH effects) or testing for directional predictability. A unified approach for dealing with all of these testing problems is proposed. These hypotheses are long standing problems in econometric time series analysis, and typically have been tested using the sample autocorrelations or in the spectral domain using the periodogram. Since these hypotheses cover also nonlinear predictability, tests based on those second order statistics are inconsistent against uncorrelated processes in the alternative hypothesis. In order to circumvent this problem pairwise integrated regression functions are introduced as measures of linear and nonlinear dependence. The proposed test does not require to chose a lag order depending on sample size, to smooth the data or to formulate a parametric alternative model. Moreover, the test is robust to higher order dependence, in particular to conditional heteroskedasticity. Under general dependence the asymptotic null distribution depends on the data generating process, so a bootstrap procedure is considered and a Monte Carlo study examines its finite sample performance. Then, the martingale and conditional heteroskedasticity properties of the Pound/Dollar exchange rate are investigated.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Elsevier
dc.rights © Elsevier
dc.subject.other Nonlinear time series
dc.subject.other Martingale difference hypothesis
dc.subject.other Empirical processes
dc.subject.other Exchange rates
dc.title Testing the martingale difference hypothesis using integrated regression functions
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1016/j.csda.2006.07.039
dc.subject.eciencia Economía
dc.identifier.doi 10.1016/j.csda.2006.07.039
dc.rights.accessRights openAccess
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