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When is a linear combination of independent fBm's equivalent to a single fBm?

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  • van Zanten, Harry

Abstract

We study and answer the question posed in the title. The answer is derived from some new necessary and sufficient conditions for equivalence of Gaussian processes with stationary increments and recent frequency domain results for the fBm. The result shows in particular precisely in which cases the local almost sure behaviour of a linear combination of independent fBm's is the same as that of a multiple of a single fBm.

Suggested Citation

  • van Zanten, Harry, 2007. "When is a linear combination of independent fBm's equivalent to a single fBm?," Stochastic Processes and their Applications, Elsevier, vol. 117(1), pages 57-70, January.
    • Handle: RePEc:eee:spapps:v:117:y:2007:i:1:p:57-70
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    References listed on IDEAS

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    1. Baudoin, Fabrice & Nualart, David, 2003. "Equivalence of Volterra processes," Stochastic Processes and their Applications, Elsevier, vol. 107(2), pages 327-350, October.
    2. Dzhaparidze, Kacha & van Zanten, Harry & Zareba, Pawel, 2005. "Representations of fractional Brownian motion using vibrating strings," Stochastic Processes and their Applications, Elsevier, vol. 115(12), pages 1928-1953, December.
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    Cited by:

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    2. Chigansky, Pavel & Kleptsyna, Marina, 2018. "Exact asymptotics in eigenproblems for fractional Brownian covariance operators," Stochastic Processes and their Applications, Elsevier, vol. 128(6), pages 2007-2059.
    3. Chen, Wenting & Yan, Bowen & Lian, Guanghua & Zhang, Ying, 2016. "Numerically pricing American options under the generalized mixed fractional Brownian motion model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 180-189.
    4. Marco Dozzi & Yuliya Mishura & Georgiy Shevchenko, 2015. "Asymptotic behavior of mixed power variations and statistical estimation in mixed models," Statistical Inference for Stochastic Processes, Springer, vol. 18(2), pages 151-175, July.

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