Power variation of multiple fractional integrals
Constantin Tudor, Maria Tudor (2007)
Open Mathematics
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Constantin Tudor, Maria Tudor (2007)
Open Mathematics
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Lanjri Zadi, Noureddine, Nualart, David (2003)
Electronic Communications in Probability [electronic only]
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Tudor, Ciprian A., Viens, Frederi G. (2003)
Electronic Journal of Probability [electronic only]
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J. Šnupárková (2009)
Czechoslovak Mathematical Journal
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Existence of a weak solution to the -dimensional system of stochastic differential equations driven by a fractional Brownian motion with the Hurst parameter is shown for a time-dependent but state-independent diffusion and a drift that may by split into a regular part and a singular one which, however, satisfies the hypotheses of the Girsanov Theorem. In particular, a stochastic nonlinear oscillator driven by a fractional noise is considered.
Mueller, Carl E., Wu, Zhixin (2009)
Electronic Communications in Probability [electronic only]
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Dai, W., Heyde, C.C. (1996)
Journal of Applied Mathematics and Stochastic Analysis
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David Nualart (2006)
Annales de la faculté des sciences de Toulouse Mathématiques
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Fractional Brownian motion (fBm) is a centered self-similar Gaussian process with stationary increments, which depends on a parameter called the Hurst index. In this conference we will survey some recent advances in the stochastic calculus with respect to fBm. In the particular case , the process is an ordinary Brownian motion, but otherwise it is not a semimartingale and Itô calculus cannot be used. Different approaches have been introduced to construct stochastic integrals with...
David Nualart, Aurel Rascanu (2002)
Collectanea Mathematica
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A global existence and uniqueness result of the solution for multidimensional, time dependent, stochastic differential equations driven by a fractional Brownian motion with Hurst parameter H > 1/2 is proved. It is shown, also, that the solution has finite moments. The result is based on a deterministic existence and uniqueness theorem whose proof uses a contraction principle and a priori estimates.