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Hurst exponents, Markov processes, and nonlinear diffusion equations

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Author Info
Bassler, Kevin E.
Gunaratne, Gemunu H.
McCauley, Joseph L.
Abstract

We show by explicit closed form calculations that a Hurst exponent H≠1/2 does not necessarily imply long time correlations like those found in fractional Brownian motion. We construct a large set of scaling solutions of Fokker-Planck partial differential equations where H≠1/2. Thus Markov processes, which by construction have no long time correlations, can have H≠1/2. If a Markov process scales with Hurst exponent H≠ 1/2 then it simply means that the process has nonstationary increments. For the scaling solutions, we show how to reduce the calculation of the probability density to a single integration once the diffusion coefficient D(x,t) is specified. As an example, we generate a class of student-t-like densities from the class of quadratic diffusion coefficients. Notably, the Tsallis density is one member of that large class. The Tsallis density is usually thought to result from a nonlinear diffusion equation, but instead we explicitly show that it follows from a Markov process generated by a linear Fokker-Planck equation, and therefore from a corresponding Langevin equation. Having a Tsallis density with H≠1/2 therefore does not imply dynamics with correlated signals, e.g., like those of fractional Brownian motion. A short review of the requirements for fractional Brownian motion is given for clarity, and we explain why the usual simple argument that H≠1/2 implies correlations fails for Markov processes with scaling solutions. Finally, we discuss the question of scaling of the full Green function g(x,t;x',t') of the Fokker-Planck pde.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 2152.

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Date of creation: 01 Dec 2005
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Handle: RePEc:pra:mprapa:2152

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Related research
Keywords: Hurst exponent Markov process scaling stochastic calculus autocorrelations fractional Brownian motion Tsallis model nonlinear diffusion

Find related papers by JEL classification:
G1 - Financial Economics - - General Financial Markets
G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies

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