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Estimation of the pointwise Hölder exponent of hidden multifractional Brownian motion using wavelet coefficients

Author

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  • Sixian Jin

    (Claremont Graduate University)

  • Qidi Peng

    (Claremont Graduate University)

  • Henry Schellhorn

    (Claremont Graduate University)

Abstract

We propose a wavelet-based approach to construct consistent estimators of the pointwise Hölder exponent of a multifractional Brownian motion, in the case where this underlying process is not directly observed. The relative merits of our estimator are discussed, and we introduce an application to the problem of estimating the functional parameter of a nonlinear model.

Suggested Citation

  • Sixian Jin & Qidi Peng & Henry Schellhorn, 2018. "Estimation of the pointwise Hölder exponent of hidden multifractional Brownian motion using wavelet coefficients," Statistical Inference for Stochastic Processes, Springer, vol. 21(1), pages 113-140, April.
    • Handle: RePEc:spr:sistpr:v:21:y:2018:i:1:d:10.1007_s11203-016-9145-1
    DOI: 10.1007/s11203-016-9145-1
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    References listed on IDEAS

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    Cited by:

    1. Peng, Qidi & Zhao, Ran, 2018. "A general class of multifractional processes and stock price informativeness," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 248-267.

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