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On fluctuation theory for spectrally negative Levy processes with Parisian reflection below, and applications

2016/12/02 by Florin Avram, Avram, Florin, Xiaowen Zhou +1
Decision Sciences · Economics, Econometrics and Finance · Mathematics · #FOS: Mathematics #Probability (math.PR) #Probability and Risk Models #Stochastic processes and financial applications #Stochastic processes and statistical mechanics

paper · pdf · doi:10.48550/arxiv.1612.00587

openalex publication_date 2016/12/02 · openalex created_date 2016/12/16 · openalex updated_date 2026/07/28

Abstract

As well known, all functionals of a Markov process may be expressed in terms of the generator operator, modulo some analytic work. In the case of spectrally negative Markov processes however, it is conjectured that everything can be expressed in a more direct way using the W scale function which intervenes in the two-sided first passage problem, modulo performing various integrals. This conjecture arises from work on Levy processes \citeAKP,Pispot,APP,Iva,IP, ivanovs2013potential,AIZ,APY, where the W scale function has explicit Laplace transform, and is therefore easily computable; furthermore it was found in the papers above that a second scale function Z introduced in \citeAKP greatly simplifies first passage laws, especially for reflected processes. This paper gathers a collection of first passage formulas for spectrally negative Parisian Lévy processes, expressed in terms of W,Z which may serve as an "instruction kit" for computing quantities of interest in applications, for example in risk theory and mathematical finance. To illustrate the usefulness of our list, we construct a new index for the valuation of financial companies modeled by spectrally negative Lévy processes, based on a Dickson-Waters modifications of the de Finetti optimal expected discounted dividends objective. We offer as well an index for the valuation of conglomerates of financial companies. An implicit question arising is to investigate analog results for other classes of spectrally negative Markovian processes.

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