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Goodness–of–Fit Test for Stochastic Volatility Models

In: From Statistics to Mathematical Finance

Author

Listed:
  • Wenceslao González-Manteiga

    (University of Santiago de Compostela, Faculty of Mathematics)

  • Jorge Passamani Zubelli

    (Institute for Pure and Applied Mathematics (IMPA))

  • Abelardo Monsalve-Cobis

    (University Centroccidental Lisandro Alvarado)

  • Manuel Febrero-Bande

    (University of Santiago de Compostela, Faculty of Mathematics)

Abstract

A goodness–of–fit test based on empirical processes is proposed as a model diagnostic check method for continuous time stochastic volatility models. More specifically, as the volatility is not observable, a marked empirical process is constructed from the representation in a state space model form associated to the discretized version of the underlying process. Distributions of these processes are approximated using bootstrap techniques. Some simulation results and an empirical application to an EURIBOR (Euro Interbank Offered Rate) data set are presented for illustration.

Suggested Citation

  • Wenceslao González-Manteiga & Jorge Passamani Zubelli & Abelardo Monsalve-Cobis & Manuel Febrero-Bande, 2017. "Goodness–of–Fit Test for Stochastic Volatility Models," Springer Books, in: Dietmar Ferger & Wenceslao González Manteiga & Thorsten Schmidt & Jane-Ling Wang (ed.), From Statistics to Mathematical Finance, chapter 0, pages 89-104, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-50986-0_6
    DOI: 10.1007/978-3-319-50986-0_6
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