Local Inference for Multifractional Brownian Motion


Unpublished


Fabian Mies, Benedikt Wilkens

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Mies, F., & Wilkens, B. Local Inference for Multifractional Brownian Motion.


Chicago/Turabian   Click to copy
Mies, Fabian, and Benedikt Wilkens. “Local Inference for Multifractional Brownian Motion,” n.d.


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Mies, Fabian, and Benedikt Wilkens. Local Inference for Multifractional Brownian Motion.


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@unpublished{fabian-a,
  title = {Local Inference for Multifractional Brownian Motion},
  author = {Mies, Fabian and Wilkens, Benedikt}
}

The fractional Brownian motion (fBm) is parameterized by the Hurst exponent $H\in(0,1)$, which determines the dependence structure and regularity of sample paths. Empirical findings suggest that for various phenomena, the Hurst exponent may be non-constant in time, giving rise to the so-called multifractional Brownian motion (mBm). The Itô-mBm is an alternative to the classical mBm, and has been shown to admit more intuitive sample path properties. In this paper, we show that Itô-mBm also allows for a simplified statistical treatment compared to the classical mBm. In particular, estimation of the local Hurst parameter $H(t)$ with Hölder exponent $\eta>0$ achieves rates of convergence which are standard in nonparametric regression, whereas similar results for the classical mBm only hold for $\eta>1$. Furthermore, we derive an estimator of the integrated Hurst exponent $\int_0^t H(s)\, ds$ which achieves a parametric rate of convergence, and use it to construct goodness-of-fit tests.

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