On a generalization of the expected discounted penalty function in a discrete‐time insurance risk model
Copyright policy )On a generalization of the expected discounted penalty function in a discrete‐time insurance risk model
AbstractIn this paper, we propose a generalization of the expected discounted penalty function and analyze the proposed analytic tool in the framework of the compound binomial model with a general premium rate c (c ∈ ℕ+) received per period. We derive an explicit expression for this generalized analytic tool in terms of the zeros of a matrix determinant. We then examine the original expected discounted penalty function in the compound binomial model with a general premium rate c, generalizing the results of Cheng et al. (Insur. Math. Econ. 2000; 26:239–250) in the framework of the compound binomial model with a unit premium rate. A numerical example is then considered to compare the original expected discounted penalty function with its generalized analytic tool. Copyright © 2008 John Wiley & Sons, Ltd.
- University of Waterloo Canada
Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.), general premium rate, generating function, Risk theory, insurance, expected discounted penalty function, risk theory, compound binomial model, polynomial matrix
Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.), general premium rate, generating function, Risk theory, insurance, expected discounted penalty function, risk theory, compound binomial model, polynomial matrix
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).16 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!