Description: This paper presents best upper and lower bounds on the expected value of a reinsurance payment under the terms of a contract written on a random loss with known moments. Bounds on the expected exercise value of a financial option are considered also because the mathematical model used for valuing options is similar to that used in reinsurance net premium calculations. From the Actuarial Research Clearing House ARCH 1990 Vol. 1.

Description: Many seniors who own houses in the United States have most of their wealth in their houses. Home Equity Conversion Mortgages are designed to allow seniors to borrow money against their house. This paper describes a stochastic simulation approach used to estimate the amount of a level-payment annuity payable as long as the senior is alive and living in his/her home. From Actuarial Research Clearing House 1990, VOL. 2.

Description: This presentation discussed the Copula Methodology, which is the most popular methodology in multivariate modeling in finance and insurance. The definition, advantages, limitations, and uses of the Copula Methodology were presented. Some other multivariate models were discussed as well. From Actuarial Research Clearing House, 2012, Vol. 1.

Description: A presentation on the principle of equivalent utility from the 2001 ARCH. Contains both the static and dynamic model as well as examples with exponential utility.

Description: This presentation considers the pricing of European derivatives in a Black-Scholes model with stochastic volatility. The presentation shows how Parseval’s theorem may be used to express those prices as Fourier integrals. This is a significant improvement over Monte Carlo simulation in many cases. The main ingredient in this presentation's method is the Laplace transform of the ordinary [constant volatility] price of a put or call in the Black-Scholes model, where the transform is taken with respect to maturity [T]. The presentation derives these formulas and then applies them to the case where volatility is modelled as a Markov chain in continuous time, the so-called 'Markov regime switching model'. This model has been used previously in stochastic volatility modelling, but mostly with only N=2 states. The presentation shows how to use N=3 states without difficulty, and how larger number of states can be handled. Numerical illustrations are given, including the volatility smile in a three-state model.

Description: Interest rate modeling is discussed in this paper with special emphasis on the long and short rate model of Brennan and Schwartz. Comment is made on an unexpected aspect of the solution of the resulting partial differential equation. Also, an analysis is made of the predictive power of the term structure of interest rates. From the Actuarial Research Clearing House 1991 Vol. 1.

Description: This paper introduces the Bond Manager's Method for ALM which allows the impact of a change in interest rate levels on the present value of a stream of cash flows to be directly determined from the coupon rates and prices on benchmark bonds without the intermediate step of determining spot rates. From Actuarial Research Clearing House 1993, VOL. 3.

Description: 1994 SOA Spring Meeting, Orlando. In this session the panelists debated the diversity of professional practice about how companies and regulators can and should measure profit and set standards for profit margins. One panelist spoke of the traditional actuarial perspective, while the other represented the modern theory of finance.

Description: This paper introduces the symbolic valuation, a stochastic valuation which allows flexible interest rate and cash flow assumptions, and provides an illustration which values a simple SPDA product. From Actuarial Research Clearing House 1992, Vol. 1.

Description: This paper evaluates the current practice of operational risk management in the insurance sector. Operational risk is nothing new in insurance, but, because of regulatory requirements, companies have initiated computation of risk capital for their operational losses. The current effort to manage operational risk is not a naturally evolving phenomenon, and operational risk, in the Basel Committee on Banking Supervision’s Basel II definition, is unlikely to be a significant cause of insurers’ failure. In addition, the current Basel II definition of operational risk is not suitable for the insurance sector. Consequently, the invention of models and tools based on the definition is incomplete and illusionary. My findings are based on the analysis of dozens of interviews with insurance industry professionals. I demonstrate the way operational risk is quantified in practice, show that the result obtained from this computation is of littl e use in managerial decision making and propose a set of policy recommendations illustrating the characteristics of operational risk in insurance. This study can be used as a platform for launching dialogues to initiate fresh thinking about operational risk in insurance beyond the current artificial and narrow boundaries.