Antonio Di Crescenzo

Bio: Antonio Di Crescenzo is an academic researcher from University of Salerno. The author has contributed to research in topics: Stochastic process & Telegraph process. The author has an hindex of 22, co-authored 139 publications receiving 1944 citations. Previous affiliations of Antonio Di Crescenzo include University of Basilicata.

Cumulative Measure of Inaccuracy and Mutual Information in k-th Lower Record Values

Abstract: In this paper, we discuss the cumulative measure of inaccuracy in k-lower record values and study characterization results of dynamic cumulative inaccuracy. We also present some properties of the proposed measures, and the empirical cumulative measure of inaccuracy in k-lower record values. We prove a central limit theorem for the empirical cumulative measure of inaccuracy under exponentially distributed populations. Finally, we analyze the mutual information for measuring the degree of dependency between lower record values, and we show that it is distribution-free.

On a fractional jump process with two kinds of jumps and its connection with the Poisson process

Abstract: We consider a fractional jump process with jumps of size 1 and 2, whose probabilities satisfy a fractional extension of the difference-differential equations $$ \dfrac{\mathrm{d}p_{k}(t) }{\mathrm{d}t } =\lambda_{2}p_{k-2}(t)+\lambda_{1}p_{k-1}(t)-(\lambda_{1}+\lambda_{2})p_{k}(t), \quad k\geq 0, \;\; t>0. $$ We obtain the probability law of the resulting process in terms of generalized Mittag-Leffler functions. We also discuss two equivalent representations both in terms of a subordinator governed by a suitable fractional Cauchy problem, and of a compound fractional Poisson process. The first occurrence time of a jump of fixed amplitude is proved to have the same distribution as the waiting time of the first event of a classical fractional Poisson process, this extending a well-known result for the Poisson process. We also express the distribution of the first passage time of the fractional jump process in an integral form that involves the joint distribution of the classical fractional Poisson process. Finally, we show that the ratios given by the powers of the jump process over their means converge in probability to 1.

Piecewise linear processes with Poisson-modulated exponential switching times

Abstract: We consider the jump telegraph process when switching intensities depend on external shocks also accompanying with jumps. The incomplete financial market model based on this process is studied. The Esscher transform, which changes only unobservable parameters, is considered in detail. The financial market model based on this transform can price switching risks as well as jump risks of the model.

Table Of Integrals Series And Products

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Applied Probability and Queues

Abstract: (1987). Applied Probability and Queues. Journal of the Operational Research Society: Vol. 38, No. 11, pp. 1095-1096.