Moments of generalized fractional polynomial processes

Fuente: arXiv
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Autori principali: Assefa, Johannes, Keller-Ressel, Martin
Natura: Preprint
Pubblicazione: 2025
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author Assefa, Johannes
Keller-Ressel, Martin
author_facet Assefa, Johannes
Keller-Ressel, Martin
contents We derive a moment formula for generalized fractional polynomial processes, i.e., for polynomial-preserving Markov processes time-changed by an inverse Lévy-subordinator. If the time change is inverse $α$-stable, the time-derivative of the Kolmogorov backward equation is replaced by a Caputo fractional derivative of order $α$, and we demonstrate that moments of such processes are computable, in a closed form, using matrix Mittag-Leffler functions. The same holds true for cross-moments in equilibrium, generalizing results of Leonenko, Meerschaert and Sikorskii from the one-dimensional diffusive case of second-order moments to the multivariate, jump-diffusive case of moments of arbitrary order. We show that also in this more general setting, fractional polynomial processes exhibit long-range dependence, with correlations decaying as a power law with exponent $α$.
format Preprint
id arxiv_https___arxiv_org_abs_2501_13854
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Moments of generalized fractional polynomial processes
Assefa, Johannes
Keller-Ressel, Martin
Probability
60G22 (Primary), 60J99, 60K50 (Secondary)
We derive a moment formula for generalized fractional polynomial processes, i.e., for polynomial-preserving Markov processes time-changed by an inverse Lévy-subordinator. If the time change is inverse $α$-stable, the time-derivative of the Kolmogorov backward equation is replaced by a Caputo fractional derivative of order $α$, and we demonstrate that moments of such processes are computable, in a closed form, using matrix Mittag-Leffler functions. The same holds true for cross-moments in equilibrium, generalizing results of Leonenko, Meerschaert and Sikorskii from the one-dimensional diffusive case of second-order moments to the multivariate, jump-diffusive case of moments of arbitrary order. We show that also in this more general setting, fractional polynomial processes exhibit long-range dependence, with correlations decaying as a power law with exponent $α$.
title Moments of generalized fractional polynomial processes
topic Probability
60G22 (Primary), 60J99, 60K50 (Secondary)
url https://arxiv.org/abs/2501.13854