We consider here convolution operators, in the Caputo sense, with nonsingular kernels. We prove that the solutions to some integro-differential equations with such operators (acting on the space variable) coincide with the transition densities of a particular class of Lévy subordinators (i.e. compound Poisson processes with non-negative jumps). We then extend these results to the case where the kernels of the operators have random parameters, with given distribution. This assumption allows greater flexibility in the choice of the kernel’s parameters and, consequently, of the jumps’ density function.

Stochastic applications of Caputo-type convolution operators with nonsingular kernels / Beghin, L.; Caputo, M.. - In: STOCHASTIC ANALYSIS AND APPLICATIONS. - ISSN 0736-2994. - (2021), pp. 1-17. [10.1080/07362994.2021.2021091]

Stochastic applications of Caputo-type convolution operators with nonsingular kernels

Beghin L.
Primo
;
Caputo M.
Secondo
2021

Abstract

We consider here convolution operators, in the Caputo sense, with nonsingular kernels. We prove that the solutions to some integro-differential equations with such operators (acting on the space variable) coincide with the transition densities of a particular class of Lévy subordinators (i.e. compound Poisson processes with non-negative jumps). We then extend these results to the case where the kernels of the operators have random parameters, with given distribution. This assumption allows greater flexibility in the choice of the kernel’s parameters and, consequently, of the jumps’ density function.
2021
Bernstein functions; Caputo-like convolution operators; compound Poisson process; Prabhakar function; risk reserve process
01 Pubblicazione su rivista::01a Articolo in rivista
Stochastic applications of Caputo-type convolution operators with nonsingular kernels / Beghin, L.; Caputo, M.. - In: STOCHASTIC ANALYSIS AND APPLICATIONS. - ISSN 0736-2994. - (2021), pp. 1-17. [10.1080/07362994.2021.2021091]
File allegati a questo prodotto
File Dimensione Formato  
Beghin_Stochastic-applications_2022.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.58 MB
Formato Adobe PDF
1.58 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1617206
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 2
social impact