An actuarial Layman's guide to building stochastic interest rate generators.

74

Abstracts and

061036 (ElO, E50) Rates of return. O’Neill J.E., U.K., Proceedings pp. 157-168.

I.C.A.,

Vol. I, 1992,

The paper considers two aspects of the Financial Management of a long term insurance venture. The first of these is the rate of return as a solution to an equation. The conclusion drawn in the paper is that attention should also be focused on yield differentials and liquidity. The second aspect is concerned with matching assets and liabilities, particularly during the initial period of the venture. The conclusion drawn here is that the exposure can be monitored by reference to long term yields. (Author) Keywords:

Financial

Management,

Matching,

Return.

Reviews

arbitrage-free pricing of interest rate contingent cash flows: absence of opportunities for riskless arbitrage; completeness of markets; relative prices that do not depend on individual investors’ subjective views or risk preferences; and, expected-value pricing in the riskneutral world. Using these concepts, the paper then showed in detail how to build a continuous stochastic model of interest rates. After studying the paper, actuaries should be able to comprehend better some of the literature in this important subject area, and should be in a position to build their own practical models. (Author) Keywords:

Interest Rate, Arbitrage

Stochastic

Model.

Aspects of interest rate models. Sharp K.P., Canada, Proceedings

I.C.A.,

Vol. I, 1992,

pp. I8 7-205.

Interest rate modelling is discussed, with special emphasis on the long and short rate model of Brennan and Schwartz (1979). Comment is made on an unexpected aspect of the solution of the resulting partial differential equation. In addition, an analysis is made of a related matter; the predictive power of the term (Author) structure of interest rates. Keywords: Partial

Interest

Rate

Model,

Diffusion

Process,

Equation.

061038 (ElO, MlO) An actuarial Layman’s

Guide to building

interest rate generators. Tilley J.A., U.S.A., Proceedings

bubbles.

Yamauchi T., Japan, Proceedings pp. 261-263.

(ElO)

I.C.A.,

stochastic

Vol. I, 1992,

pp. 20 7-228.

A stochastic interest rate generator is a valuable actuarial tool. The parameters that specify a stochastic model of interest rates can be adjusted to make the model arbitrage free or can be adjusted to accommodate an individual investor’s subjective views. The arbitragefree settings of the parameters must be used when pricing streams of interest rate contingent cash flows: for example, when establishing the risk-neutral position for asset/liability management. The real-world settings of the parameters should be used when evaluating the risk/reward tradeoffs inherent in deviating from the riskneutral position. Without relying on formulas, this paper has presented the important concepts underlying the theory of

Model,

061039 (ElO) A note on the semi-forecasted

061037

Free Pricing

ICA.,

Vol. I, 1992,

In this article, under the certain condition, which is called semi-forecasted bubbles, the relationship between dividend and speculative bubbles are studied. (Author) Keywords:

Bubbles,

Dividend,

Rational

expectations.

061040 (ElO, E13) Nonparallel yield curve shifts and convexity. Reitano XL/v,

R.R., Transactions

Society

of Actuaries,

Vol.

1992, pp. 479-499.

The conventional wisdom about convexity is that positive convexity is good, and more is better. Paradoxically, while defensible in theory, this maxim has been found to fail in practice. In this paper, the relationship of convexity to the assumption of parallel shifts is explored, and new convexity measures are developed to reflect nonparallel shifts. These new measures can differ dramatically from the traditional values, providing insight into when convexity does not have to be good and when it does. (Author) Keywords:

Convexity,

Parallel

Shifts.

061041 (ElO, B24) Modeling flexible benefit selection. Fuhrer C.S., Shapiro A.F., Transactions Actuaries, Vol. XLIV, 1992, pp. 135-155.

Society

of

A mathematical framework for benefits and choices must be created to model benefit selection. This paper creates such a framework by defining benefit plans as reimbursement functions. These are then used with a defined choice function to calculate the cost deviation due to selection. Finally, utility functions can be applied