Insurance and Risk Theory

Author: Marc Goovaerts

Publisher: Springer Science & Business Media

ISBN:

Category: Business & Economics

Page: 488

View: 296

Canadian financial institutions have been in rapid change in the past five years. In response to these changes, the Department of Finance issued a discussion paper: The Regulation of Canadian Financial Institutions, in April 1985, and the government intends to introduce legislation in the fall. This paper studi.es the combinantion of financial institutions from the viewpoint of ruin probability. In risk theory developed to describe insurance companies [1,2,3,4,5J, the ruin probability of a company with initial reserve (capital) u is 6 1 -:;-7;;f3 u 1jJ(u) = H6 e H6 (1) Here,we assume that claims arrive as a Poisson process, and the claim amount is distributed as exponential distribution with expectation liS. 6 is the loading, i.e., premium charged is (1+6) times expected claims. Financial institutions are treated as "insurance companies": the difference between interest charged and interest paid is regarded as premiums, loan defaults are treated as claims.

Risk Theory

Author: Hanspeter Schmidli

Publisher: Springer

ISBN:

Category: Business & Economics

Page: 242

View: 353

This book provides an overview of classical actuarial techniques, including material that is not readily accessible elsewhere such as the Ammeter risk model and the Markov-modulated risk model. Other topics covered include utility theory, credibility theory, claims reserving and ruin theory. The author treats both theoretical and practical aspects and also discusses links to Solvency II. Written by one of the leading experts in the field, these lecture notes serve as a valuable introduction to some of the most frequently used methods in non-life insurance. They will be of particular interest to graduate students, researchers and practitioners in insurance, finance and risk management.

Risk Theory and Reinsurance

Author: Griselda Deelstra

Publisher: Springer

ISBN:

Category: Business & Economics

Page: 78

View: 680

Reinsurance is an important production factor of non-life insurance. The efficiency and the capacity of the reinsurance market directly regulate those of insurance markets. The purpose of this book is to provide a concise introduction to risk theory, as well as to its main application procedures to reinsurance. The first part of the book covers risk theory. It presents the most prevalent model of ruin theory, as well as a discussion on insurance premium calculation principles and the mathematical tools that enable portfolios to be ordered according to their risk levels. The second part describes the institutional context of reinsurance. It first strives to clarify the legal nature of reinsurance transactions. It describes the structure of the reinsurance market and then the different legal and technical features of reinsurance contracts, known as reinsurance ‘treaties’ by practitioners. The third part creates a link between the theories presented in the first part and the practice described in the second one. Indeed, it sets out, mostly through examples, some methods for pricing and optimizing reinsurance. The authors aim is to apply the formalism presented in the first part to the institutional framework given in the second part. It is reassuring to find such a relationship between approaches seemingly abstract and solutions adopted by practitioners. Risk Theory and Reinsurance is mainly aimed at master's students in actuarial science but will also be useful for practitioners wishing to revive their knowledge of risk theory or to quickly learn about the main mechanisms of reinsurance.

Lectures on Risk Theory

Author:

Publisher: Springer Science & Business Media

ISBN:

Category: Technology & Engineering

Page: 200

View: 659

Twenty-five years ago, Hans Blihlmann published his famous monograph Mathe matical Methods in Risk Theory in the series Grundlehren der Mathematischen Wis8enschaften and thus established nonlife actuarial mathematics as a recognized subject of probability theory and statistics with a glance towards economics. This book was my guide to the subject when I gave my first course on nonlife actuarial mathematics in Summer 1988, but at the same time I tried to incorporate into my lectures parts of the rapidly growing literature in this area which to a large extent was inspired by Blihlmann's book. The present book is entirely devoted to a single topic of risk theory: Its subject is the development in time of a fixed portfolio of risks. The book thus concentrates on the claim number process and its relatives, the claim arrival process, the aggregate claims process, the risk process, and the reserve process. Particular emphasis is laid on characterizations of various classes of claim number processes, which provide alternative criteria for model selection, and on their relation to the trinity of the binomial, Poisson, and negativebinomial distributions. Special attention is also paid to the mixed Poisson process, which is a useful model in many applications, to the problems of thinning, decomposition, and superposition of risk processe8, which are important with regard to reinsurance, and to the role of martingales, which occur in a natural way in canonical situations.

Risk Theory

The Stochastic Basis of Insurance

Author: R. Beard

Publisher: Springer Science & Business Media

ISBN:

Category: Science

Page: 408

View: 653

The theory of risk already has its traditions. A review of its classical results is contained in Bohlmann (1909). This classical theory was associated with life insurance mathematics, and dealt mainly with deviations which were expected to be produced by random fluctua tions in individual policies. According to this theory, these deviations are discounted to some initial instant; the square root of the sum of the squares of the capital values calculated in this way then gives a measure for the stability of the portfolio. A theory constituted in this manner is not, however, very appropriate for practical purposes. The fact is that it does not give an answer to such questions as, for example, within what limits a company's probable gain or loss will lie during different periods. Further, non-life insurance, to which risk theory has, in fact, its most rewarding applications, was mainly outside the field of interest of the risk theorists. Thus it is quite understandable that this theory did not receive very much attention and that its applications to practical problems of insurance activity remained rather unimportant. A new phase of development began following the studies of Filip Lundberg (1909, 1919), which, thanks to H. Cramer (1926), e.O.

Aspects of Risk Theory

Author: Jan Grandell

Publisher: Springer Science & Business Media

ISBN:

Category: Mathematics

Page: 175

View: 740

Risk theory, which deals with stochastic models of an insurance business, is a classical application of probability theory. The fundamental problem in risk theory is to investigate the ruin possibility of the risk business. Traditionally the occurrence of the claims is described by a Poisson process and the cost of the claims by a sequence of random variables. This book is a treatise of risk theory with emphasis on models where the occurrence of the claims is described by more general point processes than the Poisson process, such as renewal processes, Cox processes and general stationary point processes. In the Cox case the possibility of risk fluctuation is explicitly taken into account. The presentation is based on modern probabilistic methods rather than on analytic methods. The theory is accompanied with discussions on practical evaluation of ruin probabilities and statistical estimation. Many numerical illustrations of the results are given.

Risk Theory

The Stochastic Basis of Insurance

Author: E. Beard

Publisher: Springer Science & Business Media

ISBN:

Category: Science

Page: 195

View: 719

whioh the developments are appropriate in an elementary text book is open to doubt. Fortunately the proceedings of the conference arranged by the Society of Actuaries Research Committee in September 1974 provide an effective review of the ourrent position (Credibility, Theory and Applications, Ed. P. M. Kahn, Academic Press, 1975). It is doubtful if any practical use is now made of the Esscher approximation and the N-P method is much more convenient and of adequate accuracy in most practical work. Thus the first half of Chapter 6 is now largely of historical interest. Chapter 11 dealing with ruin probability during a finite time interval does not give an adequate view of the current importanoe of this topic but the position is fluid because of the considerable effort being expended in the search for practical methods of calcu lation. Formulae are, in general, complicated and involve extensive computer based quadratures or simulation techniques. The paper by Seal in the Scandinavian Actuarial Journal (The Numerical Calculation of U(w,t) the Probability of Non-ruin in an Interval (O,t) 1974) gives a recent treatment and a fairly complete list of relevant references. In many countries studies are currently in progress in the develop ment of models for business planning where the basic operations involve a stochastic process. Not only are insurance companies interested but in many commercial and industrial firms the needs are significant so that a very large field exists for applications.

Risk Theory

Applications in Insurance Business

Author: David Davtian

Publisher:

ISBN:

Category:

Page: 50

View: 143

Modern Actuarial Risk Theory

Using R

Author: Rob Kaas

Publisher: Springer Science & Business Media

ISBN:

Category: Business & Economics

Page: 382

View: 870

Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics. This second and much expanded edition emphasizes the implementation of these techniques through the use of R. This free but incredibly powerful software is rapidly developing into the de facto standard for statistical computation, not just in academic circles but also in practice. With R, one can do simulations, find maximum likelihood estimators, compute distributions by inverting transforms, and much more.