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Path decomposition is performed to characterize the law of the pre/post-supremum, post-infimum and the intermediate processes of a spectrally negative Levy process taken up to an independent exponential time T: As a result, mainly the…

Probability · Mathematics 2019-10-21 C. Vardar-Acar , M. Caglar , F. Avram

The joint distribution of the maximum loss and the maximum gain is obtained for a spectrally negative Levy process until the passage time of a given level. Their marginal distributions up to an independent exponential time are also…

Probability · Mathematics 2019-01-30 Ceren Vardar Acar , Mine Caglar

Let $X$ be a real L\'evy process and let $\Xpos $ be the process conditioned to stay positive. We assume that $ 0 $ is regular for $(-\infty, 0)$ and $(0, +\infty) $ with respect to $X$. Using elementary excursion theory arguments, we…

Probability · Mathematics 2007-05-23 Thomas Duquesne

We study the convergence in distribution of the supremum of the local time and of the favorite site for a transient diffusion in a spectrally negative L\'evy potential. To do so, we study the h-valleys of a spectrally negative L\'evy…

Probability · Mathematics 2018-02-27 Grégoire Véchambre

In this paper we consider the distribution of the location of the path supremum in a fixed interval for self-similar processes with stationary increments. To this end, a point process is constructed and its relation to the distribution of…

Probability · Mathematics 2016-05-24 Yi Shen

For a spectrally negative L\'evy process $X$, we study the following distribution: $$ \mathbb{E}_x \left[ \mathrm{e}^{- q \int_0^t \mathbf{1}_{(a,b)} (X_s) \mathrm{d}s } ; X_t \in \mathrm{d}y \right], $$ where $-\infty \leq a < b < \infty$,…

Probability · Mathematics 2014-06-13 Hélène Guérin , Jean-François Renaud

In this article we derive formulas for the probability $P(\sup_{t\leq T} X(t)>u)$ $T>0$ and $P(\sup_{t<\infty} X(t)>u)$ where $X$ is a spectrally positive L\'evy process with infinite variation. The formulas are generalizations of the…

Probability · Mathematics 2014-10-20 Zbigniew Michna , Zbigniew Palmowski , Martijn Pistorius

Last passage times arise in a number of areas of applied probability, including risk theory and degradation models. Such times are obviously not stopping times since they depend on the whole path of the underlying process. We consider the…

Probability · Mathematics 2018-06-01 Erik J. Baurdoux , J. M. Pedraza

We develop new representations for the Levy measures of the beta and gamma processes. These representations are manifested in terms of an infinite sum of well-behaved (proper) beta and gamma distributions. Further, we demonstrate how these…

Methodology · Statistics 2012-06-22 Yingjian Wang , Lawrence Carin

We recall four open problems concerning constructing high-order matrix-exponential approximations for the infimum of a spectrally negative Levy process (with applications to first-passage/ruin probabilities, the waiting time distribution in…

Probability · Mathematics 2012-10-10 Florin Avram , Andras Horvath , M. R. Pistorius

We consider a L\'evy process $Y(t)$ that is not permanently observed, but rather inspected at Poisson($\omega$) moments only, over an exponentially distributed time $T_\beta$ with parameter $\beta$. The focus lies on the analysis of the…

Probability · Mathematics 2021-10-26 Onno Boxma , Michel Mandjes

Using a new approach, for spectrally negative L\'evy processes we find joint Laplace transforms involving the last exit time (from a semi-infinite interval), the value of the process at the last exit time and the associated occupation time,…

Probability · Mathematics 2016-10-05 Yingqiu Lia , Chuancun Yin , Xiaowen Zhou

We discuss the Gamma Levy process, including path properties, the inverse process, integrability, and its spin-offs obtained by compounding, exponentiation, and other operations; further extendable to arbitrary sigma-finite continuous Borel…

Probability · Mathematics 2024-05-24 Jerzy Szulga

A new decomposition optimization algorithm, called \textit{path-following gradient-based decomposition}, is proposed to solve separable convex optimization problems. Unlike path-following Newton methods considered in the literature, this…

Optimization and Control · Mathematics 2012-09-21 Quoc Tran Dinh , Ion Necoara , Moritz Diehl

In this article we derive formula for probability $\Prob(\sup_{t\leq T} (X(t)-ct)>u)$ where $X=\{X(t)\}$ is a spectrally positive L\'evy process and $c\in\RL$. As an example we investigate the inverse Gaussian L\'evy process.

Probability · Mathematics 2012-05-30 Zbigniew Michna

The purpose of this review article is to give an up to date account of the theory and application of scale functions for spectrally negative Levy processes. Our review also includes the first extensive overview of how to work numerically…

Probability · Mathematics 2015-03-19 Alexey Kuznetsov , Andreas E. Kyprianou , Victor Rivero

The path decomposition expansion is a path integral technique for decomposing sums over paths in configuration space into sums over paths in different spatial regions. It leads to a decomposition of the configuration space propagator across…

Quantum Physics · Physics 2011-09-15 J. J. Halliwell

We consider a process $Z$ on the real line composed from a L\'evy process and its exponentially tilted version killed with arbitrary rates and give an expression for the joint law of $Z$ seen from its supremum, the supremum $\overline Z$…

Probability · Mathematics 2014-05-15 Sebastian Engelke , Jevgenijs Ivanovs

We consider the spectrally negative Levy processes and determine the joint laws for the quantities such as the first and last passage times over a fixed level, the overshoots and undershoots at first passage, the minimum, the maximum and…

Probability · Mathematics 2014-02-26 Chuancun Yin , Kam Chuen Yuen

In this paper we study a spectrally negative L\'{e}vy process that is reflected at its draw-down level whenever a draw-down time from the running supremum arrives. Using an excursion-theoretical approach, for such a reflected process we…

Probability · Mathematics 2019-11-26 Wenyuan Wang , Xiaowen Zhou
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