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Heavy-tailed fractional Pearson diffusions.

N N Leonenko1, I Papić2, A Sikorskii3

  • 1School of Mathematics, Cardiff University, Senghennydd Road, Cardiff CF244AG, UK.

Stochastic Processes and Their Applications
|October 10, 2017
PubMed
Summary
This summary is machine-generated.

We introduce heavy-tailed fractional diffusions using a time change in Pearson diffusions. These new models exhibit heavy-tailed distributions and have explicit transition densities, advancing stochastic process theory.

Keywords:
Fractional backward Kolmogorov equationFractional diffusionHypergeometric functionMittag-Leffler functionPearson diffusionSpectral representationTransition densityWhittaker function

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Area of Science:

  • Stochastic Processes
  • Mathematical Physics
  • Probability Theory

Background:

  • Pearson diffusions are foundational models governed by backward Kolmogorov equations with polynomial coefficients.
  • These diffusions find broad applications in various scientific and engineering fields.
  • Existing models may not fully capture heavy-tailed phenomena crucial in many real-world systems.

Purpose of the Study:

  • To define novel heavy-tailed fractional reciprocal gamma and Fisher-Snedecor diffusions.
  • To investigate the properties of these new diffusion processes, particularly their heavy-tailed marginal distributions.
  • To derive analytical solutions for the associated fractional backward Kolmogorov equations.

Main Methods:

  • A non-Markovian time change was applied to standard Pearson diffusions.
  • Fractional backward Kolmogorov equations were utilized to govern the new processes.
  • Explicit expressions for transition densities were derived.
  • Strong solutions for the Cauchy problems of the fractional backward Kolmogorov equation were obtained.

Main Results:

  • The introduction of heavy-tailed fractional reciprocal gamma and Fisher-Snedecor diffusions.
  • Demonstration that these diffusions possess heavy-tailed marginal distributions in the steady state.
  • Derivation of explicit formulas for the transition densities of the newly defined diffusions.
  • Establishment of strong solutions for the associated fractional backward Kolmogorov equations.

Conclusions:

  • The study successfully defines and characterizes new heavy-tailed fractional diffusion processes.
  • The derived explicit transition densities and solutions provide valuable tools for analyzing systems with heavy tails.
  • These findings extend the theory of stochastic diffusions and offer new modeling capabilities.