Description: The method described in this paper is to allocate surplus to each category of business and reserves in proportion to its estimated effect on an insurer's surplus variation. Risk load for each category of business is then selected so that the return on allocated surplus for each category is equal to the overall return on surplus. From Actuarial Research Clearing House 1993, VOL. 3.

Description: The theme of this presentation relates to solving portfolio selection problems using linear and fractional programming. Two key contributions: 1. Generalization of the CVaR linear optimization framework. 2. Equivalences among four formulations of Coherent Distortion Risk Mearures optimization problems. From Actuarial Research Clearing House, 2012, Vol. 1.

Description: This paper investigates the implications of using the Basel II motivated Advanced Measurement Approaches as a method to assess operational risk capital charges for banks and insurance companies with regard to U.S. regulations. The AMA developed in the paper uses actuarial loss models complemented by the extreme value theory to determine the empirical probability distribution function of the aggregated capital charges in the context of various classes of copulas. From Actuarial Research Clearing House, 2006.

Description: We derive formulas for calculating the premiums that should be charged on policies in a discounted cash flow model with tax reserves and required assets that are determined by regulation. We also determine the unique division of required assets into “reserves” and “capital” that allows the product profitability to be correctly evaluated. That is, the profit after capital charges is zero if the product achieves the return assumed in pricing. We illustrate the concepts using whole life insurance and guaranteed minimum death benefit examples.

Description: Option bounds are obtained in a discrete-time framework with transaction costs. The model represents an extension of the Cox-Ross-Rubinstein binomial option pricing model to cover the case of proportional transaction costs. The method proceeds by constructing the appropriate replicating portfolio at each trading interval. From Actuarial Research Clearing House 1991, VOL. 1.

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: This paper presents a proof on the subject of uniqueness of interest rates in a borrowing/lending model for possible student use in undergraduate classes in the theory of interest. From Actuarial Research Clearing House 1993, VOL. 3.

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: This paper analyzes the U. S. Treasury monthly interest rates from 1953 to 1992, and the daily rates from 1981 to 1992 for various forms of chaotic behavior. The primary analysis was in determining the Burst Exponent by the use of Rescaled Range Analysis. This paper also discusses other possible uses of Fractional Brownian Motion in Finance Theory, Macroeconomics, and Actuarial Science. From Actuarial Research Clearing House 1994 VOL. 1.

Description: Constant maturity credit default swaps [CMCDS] are useful as hedging tools. In intensity model approach, the default time is defined as the first arrival time of the Poisson process. From the market quotes of CDS forward rates and bonds, we are able to numerically compute the default probabilities. Approximating CMCDS price depends largely on CDS forward rates’ volatilities and their correlations. This paper implements the price algorithm based on Brigo’s work [2006]. Starting with current market data such as CDS forward rates and nondefaultable bond prices, the paper describes steps involved to obtain the price CMCDS. The paper demonstrates the impact of convexity on the CMCDS price structure.