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Nonparametric estimation of diffusion process: a closer look

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  • Orazio Di Miscia

    (Banca Intesa)

Abstract

A Monte Carlo simulation is performed to investigate the finite sample properties of a nonparametric estimator, based on discretely sampled observations of continuous-time Ito diffusion process. Chapman and Pearson (2000) studies finite-sample properties of the nonparametric estimator of Aýt-Sahalia (1996) and Stanton (1997) and they find that nonlinearity of the short rate drift is not a robust stylized fact but it’s an artifacts of the estimation procedure. This paper examine the finite sample properties of a different nonparametric estimator within the Stanton (1997)’s framework.

Suggested Citation

  • Orazio Di Miscia, 2005. "Nonparametric estimation of diffusion process: a closer look," Finance 0504016, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpfi:0504016
    Note: Type of Document - pdf; pages: 17
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    References listed on IDEAS

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    6. John C. Cox & Jonathan E. Ingersoll Jr. & Stephen A. Ross, 2005. "A Theory Of The Term Structure Of Interest Rates," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 5, pages 129-164, World Scientific Publishing Co. Pte. Ltd..
    7. David A. Chapman & Neil D. Pearson, 2000. "Is the Short Rate Drift Actually Nonlinear?," Journal of Finance, American Finance Association, vol. 55(1), pages 355-388, February.
    8. Phillips, P. C. B., 1973. "The problem of identification in finite parameter continuous time models," Journal of Econometrics, Elsevier, vol. 1(4), pages 351-362, December.
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