Random walks with non-convolution equivalent increments and their applications

• Published in: Journal of mathematical analysis and applications 2011-02, Vol.374 (1), p.88-105
• Main Authors: Wang, Yuebao, Wang, Kaiyong
• Format: Article
• Language: English
• Subjects: Asymptotics; Exact sciences and technology; Infinitely divisible law; Mathematical analysis; Mathematics; Non-convolution equivalent distribution class; Overshoot; Random walks; Renewal risk model; Sciences and techniques of general use; Supremum; γ-transform
• ISSN: 0022-247X; 1096-0813
• DOI: 10.1016/j.jmaa.2010.08.040

This paper mainly presents some global and local asymptotic estimates for the tail probabilities of the supremum and overshoot of a random walk in “the intermediate case”, where the related distributions of the increments of the random walk may not belong to the convolution equivalent distribution class. Some of the obtained results can include the classical results. For this, the paper first introduces some new distribution classes using the γ-transform of distributions, and investigates their properties and relations with some other existing distribution classes. Based on the above results, some equivalent conditions for the global and local asymptotics of the γ-transform of the distribution of the supremum of the above random walk are given. Applying these results to risk theory and infinitely divisible laws, the paper obtains some asymptotic estimates for the ruin probability and the local ruin probability of the renewal risk model with non-convolution equivalent claims, and the global and local asymptotics of an infinitely divisible law with a non-convolution equivalent Lévy measure.