Abstract

In this paper we examine the large deviations principle (LDP) for sequences of classic Cramer-Lundberg risk processes under suitable time and scale modifications, and also for a wide class of claim distributions including (the non-super- exponential) exponential claims. We prove two large deviations principles: first, we obtain the LDP for risk processes on D∈[0,1] with the Skorohod topology. In this case, we provide an explicit form for the rate function, in which the safety loading condition appears naturally. The second theorem allows us to obtain the LDP for Aggregate Claims processes on D∈[0,∞) with a different time-scale modification. As an application of the first result we estimate the ruin probability, and for the second result we work explicit calculations for the case of exponential claims.

Highlights

  • In this paper we examine the large deviations principle (LDP) for sequences of classic Cramér-Lundberg risk processes under suitable time and scale modifications, and for a wide class of claim distributions including exponential claims

  • We prove two large deviations principles: first, we obtain the LDP for risk processes on D 0,1 with the Skorohod topology

  • There is a wide literature on Large Deviation Techniques and Applications

Read more

Summary

Introduction

There is a wide literature on Large Deviation Techniques and Applications. Relevant to this paper are results by Mogulskii (1993), [1] who proved a Large Deviations result for independent, identically distributed (i.i.d.) random variables with generating functions finite on a neighborhood of the origin. Layed claims) risk process was studied by Ganesh, Massi and Torrisi (2007) [7,8] They proved the LDP with respect to the uniform topology in the case of superexponential claims i.e., claims for which the moment generating function is finite for every 0. On a generalization of the model, Asmussen, Klüppelberg, and Mikosch, in [11,12], studied asymptotic results for the compound Poisson process when the size of the jumps has a heavy tail (the moment generating function of the claims is on the positive real numbers) In this case, the large deviations theory does not apply, the results are quite different, and that is not the subject of this paper.

A Remark on the Rate Function
Statement of Hypotheses
Large Deviations for the Risk Process on
LZ 1 is finite as long as
Large Deviations for the Aggregate
Nn nt
Exponential Claims
Estimating the Ruin Probability of the Process Rn
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call