Description: The main purpose of this paper is to study the ruin probabilities of insurance surplus process over an extended period of time. The traditional large deviation techniques are used to obtain asymptotic exponential bound for the probability of ruin occurring at time t when the aggregate claim process is compound Poisson. The exponential bound is naturally expressed in terms of the large deviation rate function.

Description: Using data from a large insurance company, we construct a parametric model for the joint survival function based on a Hougaard copula function.

Description: Because actuaries fit models for a variety of situations, particularly with regard to data modifications, it is useful to have a single approach. Though not optimal or exact for a particular model or data structure, the method should be reasonable for most all settings. Such a method is proposed in this article. Actuarial Research Clearing House 2003, VOL. 1

Description: This paper develops and discusses various relations between the Uniform Death Distribution and the Balducci curve. From ACTUARIAL RESEARCH CLEARING HOUSE 1980, VOL. 2.

Description: In this paper the author proposes a proof for new formulas that derive exposure formulas of the valuation-schedule type on the basis of the Balducci assumption. In addition he provides a short cut for the coefficients of the terms involving deaths. Then he derives a general exposure formula of the valuation-schedule type that may be used for all mortality studies with an observation period covering an integral number of consecutive years. From ACTUARIAL RESEARCH CLEARING HOUSE, 1980 VOL. 2.

Description: It is the purpose of this paper to demonstrate in a mathematically rigorous manner that compound interest as usually understood is uniquely given by [l+i]^t for all real t.

Description: In classical collective risk theory, the aggregate claims process is assumed to be compound Poisson. In this paper the authors examine a more general model for the aggregate claims process: processes with independent, stationary and non-negative increments. From Actuarial Research Clearing House 1991, VOL. 1.

Description: This paper describes a method to determine confidence intervals for trend involving resampling - with replacement but without random numbers - of numerical convolutions for sums and quotients, and the estimating of confidence intervals for trend in average size major medical claims.

Description: This paper discusses a mixed lognormal estimator of a risk distribution. Using the observed claim frequencies of a portfolio, the author presents a continuous nonparametric estimator of the risk distribution that reproduces some of the empirical moments and converges uniformly. The estimator that is investigated is a mixture of log-normal distributions whose parameters are calculated by considering the determinants of certain moment matrices. From Actuarial Research Clearing House 1993, VOL. 1.

Description: Describes purpose of ARCH and editorial policy.