Abstract. The aim of this note is to give a straightforward proof of a general version of the Ciesielski-Taylor identity for positive self-similar Markov processes of the spectrally negative type which umbrellas all previously known Ciesielski-Taylor identities within the latter class. The approach makes use of three fundamental features. Firstly a new transformation which maps a subset of the family of Laplace exponents of spectrally negative Lévy processes into itself. Secondly some classical features of fluctuation theory for spectrally negative Lévy processes (see eg. [15]) as well as more recent fluctuation identities for positive self-similar Markov processes found in Patie [19]
In this paper we consider the first passage process of a spectrally negative Markov additive process...
AbstractWe describe and investigate a class of Markovian models based on a form of “dynamic occupanc...
31 pagesIn his 1972 paper, John Lamperti characterized all positive self-similar Markov processes as...
The aim of this note is to give a straightforward proof of a general version of the Ciesielski-Taylo...
AbstractWe consider some special classes of Lévy processes with no gaussian component whose Lévy mea...
Abstract: We establish integral tests in connection with laws of the iterated logarithm at 0 and at ...
We consider some special classes of Lévy processes with no gaussian component whose Lévy measure is ...
38 pagesWe present a new approach to positive self-similar Markov processes (pssMps) by reformulatin...
Abstract We establish integral tests and laws of the iterated logarithm for the upper envelope of th...
Using Lamperti’s relationship between Lévy processes and positive self-similar Markov processes (pss...
For a positive self-similar Markov process, X, we construct a local time for the random set, Θ, of t...
We establish integral tests and laws of the iterated logarithm at $0$ and at $+\infty$, for the uppe...
We establish integral tests and laws of the iterated logartihm for the upper envelope of the future ...
A classical result, due to Lamperti, establishes a one-to-one correspondence between a class of stri...
An R d-valued Markov process X (x) t = (X 1,x 1 t ,. .. , X d,x d t), t ≥ 0, x ∈ R d is said to be m...
In this paper we consider the first passage process of a spectrally negative Markov additive process...
AbstractWe describe and investigate a class of Markovian models based on a form of “dynamic occupanc...
31 pagesIn his 1972 paper, John Lamperti characterized all positive self-similar Markov processes as...
The aim of this note is to give a straightforward proof of a general version of the Ciesielski-Taylo...
AbstractWe consider some special classes of Lévy processes with no gaussian component whose Lévy mea...
Abstract: We establish integral tests in connection with laws of the iterated logarithm at 0 and at ...
We consider some special classes of Lévy processes with no gaussian component whose Lévy measure is ...
38 pagesWe present a new approach to positive self-similar Markov processes (pssMps) by reformulatin...
Abstract We establish integral tests and laws of the iterated logarithm for the upper envelope of th...
Using Lamperti’s relationship between Lévy processes and positive self-similar Markov processes (pss...
For a positive self-similar Markov process, X, we construct a local time for the random set, Θ, of t...
We establish integral tests and laws of the iterated logarithm at $0$ and at $+\infty$, for the uppe...
We establish integral tests and laws of the iterated logartihm for the upper envelope of the future ...
A classical result, due to Lamperti, establishes a one-to-one correspondence between a class of stri...
An R d-valued Markov process X (x) t = (X 1,x 1 t ,. .. , X d,x d t), t ≥ 0, x ∈ R d is said to be m...
In this paper we consider the first passage process of a spectrally negative Markov additive process...
AbstractWe describe and investigate a class of Markovian models based on a form of “dynamic occupanc...
31 pagesIn his 1972 paper, John Lamperti characterized all positive self-similar Markov processes as...