Hurst Exponents, Markov Processes, and Fractional Brownian motion

Abstract

There is much confusion in the literature over Hurst exponents. Recently, we took a step in the direction of eliminating some of the confusion. One purpose of this paper is to illustrate the difference between fBm on the one hand and Gaussian Markov processes where H not equal to 1/2 on the other. The difference lies in the increments, which are stationary and correlated in one case and nonstationary and uncorrelated in the other. The two- and one-point densities of fBm are constructed explicitly. The two-point density doesn't scale. The one-point density is identical with that for a Markov process with H not 1/2. We conclude that both Hurst exponents and histograms for one point densities are inadequate for deducing an underlying stochastic dynamical system from empirical data.

References in corpus (3)

• Fractional calculus and continuous-time finance
• Fractional calculus and continuous-time finance II: the waiting-time distribution
• Nonstationary Increments, Scaling Distributions, and Variable Diffusion Processes in Financial Markets

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