Bootstrap specification tests for diffusion processes.

This paper discusses specification tests for diffusion processes. In the one-dimensional case, our proposed test is closest to the nonparametric test of Ait-Sahalia (Rev. Financ. Stud. 9 (1996) 385). However, we compare CDFs instead of densities. In the multidimensional and/or multifactor case, our...

Descripción completa

Detalles Bibliográficos
Publicado en:Journal of Econometrics Vol. 124; no. 1; pp. 117 - 149
Autores principales: Corradi, Valentina, Swanson, Norman R.
Formato: Artículo
Publicado: Elsevier Science January 2005
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=513184217&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 513184217
    longDbName: Social Sciences Full Text (H.W. Wilson)
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        03044076
        ECM
      jtl: Journal of Econometrics
      issn: 03044076
      maglogo: N
    pubinfo:
      dt: January 2005
      vid: 124
      iid: 1
      pid: 1004
      pub: Elsevier Science
    artinfo:
      ui:
        513184217
        10.1016/j.jeconom.2004.02.013
      ppf: 117
      ppct: 32
      formats:
      tig:
        atl: Bootstrap specification tests for diffusion processes.
      aug:
        au:
          Corradi, Valentina
          Swanson, Norman R.
      su:
        Statistical bootstrapping
        Diffusion processes
      sug:
        subj:
          Statistical bootstrapping
          Diffusion processes
      ab: This paper discusses specification tests for diffusion processes. In the one-dimensional case, our proposed test is closest to the nonparametric test of Ait-Sahalia (Rev. Financ. Stud. 9 (1996) 385). However, we compare CDFs instead of densities. In the multidimensional and/or multifactor case, our proposed test is based on comparison of the empirical CDF of actual data and the empirical CDF of simulated data. Asymptotically valid critical values are obtained using an empirical process version of the block bootstrap which accounts for parameter estimation error. An example based on a simple version of the Cox et al. (Econometrica 53 (1985) 385) model is outlined and related Monte Carlo experiments are carried out. Copyright (c) 2003 Elsevier B.V.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N