Markov Processes, Hurst Exponents, and Nonlinear Diffusion Equations with application to finance
arXiv:cond-mat/0602316 · doi:10.1016/j.physa.2006.01.081
Abstract
We show by explicit closed form calculations that a Hurst exponent H that is not 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 is not 1/2. Thus Markov processes, which by construction have no long time correlations, can have H not equal to 1/2. If a Markov process scales with Hurst exponent H 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 not equal to 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 unequal to 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.
to appear in Physica A
References in corpus (5)
- Fractional calculus and continuous-time finance
- Non Linear Kinetics underlying Generalized Statistics
- Fractional calculus and continuous-time finance II: the waiting-time distribution
- Option Pricing Formulas based on a non-Gaussian Stock Price Model
- Microscopic dynamics underlying the anomalous diffusion
Cited by in corpus (23)
- A non-intrusive reduced order modeling framework for quasi-geostrophic turbulence
- Nonstationary Increments, Scaling Distributions, and Variable Diffusion Processes in Financial Markets
- Response to Worrying Trends in Econophysics
- Kramers escape driven by fractional Brownian motion
- Liquidity and the multiscaling properties of the volume traded on the stock market
- Anomalous Scaling of Stochastic Processes and the Moses Effect
- Fluctuations, correlations and the nonextensivity
- Markov vs. nonMarkovian processes A comment on the paper Stochastic feedback, nonlinear families of Markov processes, and nonlinear Fokker-Planck equations by T.D. Frank
- Fluctuations, correlations and non-extensivity
- Anomalous diffusion and the Moses effect in a model of aging
- Time vs. Ensemble Averages for Nonstationary Time Series
- Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets
- Spurious memory in non-equilibrium stochastic models of imitative behavior
- Order flow in the financial markets from the perspective of the Fractional Lévy stable motion
- Serial Correlation, Periodicity and Scaling of Eigenmodes in an Emerging Market
- Anti-persistent random walks in time-delayed systems
- Effectiveness of Measures of Performance During Speculative Bubbles
- Understanding the nature of the long-range memory phenomenon in socioeconomic systems
- Approximation of the first passage time distribution for the birth-death processes
- Fokker-Planck and Chapman-Kolmogorov equations for Ito processes with finite memory
- Long-range memory test by the burst and inter-burst duration distribution
- Martingales, Detrending Data, and the Efficient Market Hypothesis
- Martingale Option Pricing