Testing the parametric form of the volatility in continuous time diffusion models—a stochastic process approach.

We present new tests for the form of the volatility function which are based on stochastic processes of the integrated volatility. We prove weak convergence of these processes to centered processes whose conditional distributions are Gaussian. In the case of testing for a constant volatility the lim...

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Publicado en:Journal of Econometrics Vol. 143; no. 1; pp. 56 - 74
Autores principales: Dette, Holger, Podolskij, Mark
Formato: Artículo
Publicado: Elsevier Science March 2008
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        511396145
        10.1016/j.jeconom.2007.08.002
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        atl: Testing the parametric form of the volatility in continuous time diffusion models—a stochastic process approach.
      aug:
        au:
          Dette, Holger
          Podolskij, Mark
      su:
        Statistical hypothesis testing
        Market volatility
        Stochastic processes
        Statistical bootstrapping
      sug:
        subj:
          Statistical hypothesis testing
          Market volatility
          Stochastic processes
          Statistical bootstrapping
      ab: We present new tests for the form of the volatility function which are based on stochastic processes of the integrated volatility. We prove weak convergence of these processes to centered processes whose conditional distributions are Gaussian. In the case of testing for a constant volatility the limiting process are standard Brownian bridges. As a consequence an asymptotic distribution free test and bootstrap tests (for testing of a general parametric form) can easily be implemented. It is demonstrated that the new tests are more than the currently available procedures. The new approach is also demonstrated by means of a simulation study. Copyright (c) 2008 Elsevier B.V.
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    language: English
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