EconPapers    
Economics at your fingertips  
 

Probability of ruin in discrete insurance risk model with dependent Pareto claims

Constantinescu Corina D., Kozubowski Tomasz J. and Qian Haoyu H.
Additional contact information
Constantinescu Corina D.: Institute for Financial and Actuarial Sciences, Department of Mathematical Sciences, University of Liverpool, L69 7ZL Liverpool, United Kingdom
Kozubowski Tomasz J.: Department of Mathematics & Statistics, University of Nevada, Reno, NV 89557, USA
Qian Haoyu H.: Institute for Financial and Actuarial Sciences, Department of Mathematical Sciences, University of Liverpool, L69 7ZL Liverpool, United Kingdom

Dependence Modeling, 2019, vol. 7, issue 1, 215-233

Abstract: We present basic properties and discuss potential insurance applications of a new class of probability distributions on positive integers with power law tails. The distributions in this class are zero-inflated discrete counterparts of the Pareto distribution. In particular, we obtain the probability of ruin in the compound binomial risk model where the claims are zero-inflated discrete Pareto distributed and correlated by mixture.

Keywords: Actuarial science; compound binomial risk model; dependence by mixture; discrete Pareto distribution; geometric distribution; heavy tail; mixture; power law; ruin probability; zero-altered distribution; zero-inflated distribution; zero-modified distribution (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/demo-2019-0011 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:demode:v:7:y:2019:i:1:p:215-233:n:11

DOI: 10.1515/demo-2019-0011

Access Statistics for this article

Dependence Modeling is currently edited by Giovanni Puccetti

More articles in Dependence Modeling from De Gruyter
Bibliographic data for series maintained by Peter Golla ().

 
Page updated 2025-03-20
Handle: RePEc:vrs:demode:v:7:y:2019:i:1:p:215-233:n:11