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How rich is the class of multifractional Brownian motions?

Author

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  • Stoev, Stilian A.
  • Taqqu, Murad S.

Abstract

The multifractional Brownian motion (MBM) processes are locally self-similar Gaussian processes. They extend the classical fractional Brownian motion processes by allowing their self-similarity parameter H[set membership, variant](0,1) to depend on time. Two types of MBM processes were introduced independently by Peltier and Lévy-Vehel [Multifractional Brownian motion: definition and preliminary results, Technical Report 2645, Institut National de Recherche en Informatique et an Automatique, INRIA, Le Chesnay, France, 1995] and Benassi, Jaffard, Roux [Elliptic Gaussian random processes, Rev. Mat. Iber. 13(1) (1997) 19-90] by using time-domain and frequency-domain integral representations of the fractional Brownian motion, respectively. Their correspondence was studied by Cohen [From self-similarity to local self-similarity: the estimation problem, in: M. Dekking, J.L. Véhel, E. Lutton, C. Tricot (Eds.), Fractals: Theory and Applications in Engineering, Springer, Berlin, 1999]. Contrary to what has been stated in the literature, we show that these two types of processes have different correlation structures when the function H(t) is non-constant. We focus on a class of MBM processes parameterized by , which contains the previously introduced two types of processes as special cases. We establish the connection between their time- and frequency-domain integral representations and obtain explicit expressions for their covariances. We show, that there are non-constant functions H(t) for which the correlation structure of the MBM processes depends non-trivially on the value of (a+,a-) and hence, even for a given function H(t), there are an infinite number of MBM processes with essentially different distributions.

Suggested Citation

  • Stoev, Stilian A. & Taqqu, Murad S., 2006. "How rich is the class of multifractional Brownian motions?," Stochastic Processes and their Applications, Elsevier, vol. 116(2), pages 200-221, February.
    • Handle: RePEc:eee:spapps:v:116:y:2006:i:2:p:200-221
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    Citations

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    Cited by:

    1. Joachim Lebovits & Mark Podolskij, 2016. "Estimation of the global regularity of a multifractional Brownian motion," CREATES Research Papers 2016-33, Department of Economics and Business Economics, Aarhus University.
    2. Cohen, Serge & Lacaux, Céline & Ledoux, Michel, 2008. "A general framework for simulation of fractional fields," Stochastic Processes and their Applications, Elsevier, vol. 118(9), pages 1489-1517, September.
    3. Lebovits, Joachim & Lévy Véhel, Jacques & Herbin, Erick, 2014. "Stochastic integration with respect to multifractional Brownian motion via tangent fractional Brownian motions," Stochastic Processes and their Applications, Elsevier, vol. 124(1), pages 678-708.
    4. Chen, Zhe & Leskelä, Lasse & Viitasaari, Lauri, 2019. "Pathwise Stieltjes integrals of discontinuously evaluated stochastic processes," Stochastic Processes and their Applications, Elsevier, vol. 129(8), pages 2723-2757.
    5. Anderes, Ethan B. & Stein, Michael L., 2011. "Local likelihood estimation for nonstationary random fields," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 506-520, March.
    6. Dai, Hongshuai & Li, Yuqiang, 2010. "A weak limit theorem for generalized multifractional Brownian motion," Statistics & Probability Letters, Elsevier, vol. 80(5-6), pages 348-356, March.
    7. Bardet, Jean-Marc & Surgailis, Donatas, 2013. "Nonparametric estimation of the local Hurst function of multifractional Gaussian processes," Stochastic Processes and their Applications, Elsevier, vol. 123(3), pages 1004-1045.
    8. Marco Dozzi & Yuriy Kozachenko & Yuliya Mishura & Kostiantyn Ralchenko, 2018. "Asymptotic growth of trajectories of multifractional Brownian motion, with statistical applications to drift parameter estimation," Statistical Inference for Stochastic Processes, Springer, vol. 21(1), pages 21-52, April.
    9. Lavancier, Frédéric & Philippe, Anne & Surgailis, Donatas, 2009. "Covariance function of vector self-similar processes," Statistics & Probability Letters, Elsevier, vol. 79(23), pages 2415-2421, December.
    10. Ehsan Azmoodeh & Ozan Hur, 2023. "Multi-fractional Stochastic Dominance: Mathematical Foundations," Papers 2307.08651, arXiv.org.
    11. Balança, Paul, 2015. "Some sample path properties of multifractional Brownian motion," Stochastic Processes and their Applications, Elsevier, vol. 125(10), pages 3823-3850.
    12. Loboda, Dennis & Mies, Fabian & Steland, Ansgar, 2021. "Regularity of multifractional moving average processes with random Hurst exponent," Stochastic Processes and their Applications, Elsevier, vol. 140(C), pages 21-48.
    13. 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.
    14. Balança, Paul & Herbin, Erick, 2012. "2-microlocal analysis of martingales and stochastic integrals," Stochastic Processes and their Applications, Elsevier, vol. 122(6), pages 2346-2382.

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