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Interest and Mortality Randomness in Some Annuities
Interest and Mortality Randomness in Some Annuities This paper presents a model is which can be used ... possible adverse interest and mortality experience for collections of life annuity contracts. Certain boundary ...- Authors: John A Beekman, Clinton P Fuelling
- Date: Jan 1991
- Competency: Technical Skills & Analytical Problem Solving
- Publication Name: Actuarial Research Clearing House
- Topics: Annuities>Fixed annuities; Annuities>Individual annuities; Modeling & Statistical Methods>Stochastic models
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A Stochastic Investment Model
integral-valued, stochastic process, independent of the X?s and with N(O) -- O. This process counts the random ... degree than is true even for insurance claims. Let S(t) --- ~N('~ X~ be a random sum of the random variables ...- Authors: John A Beekman
- Date: Jan 1980
- Competency: Results-Oriented Solutions
- Publication Name: Transactions of the SOA
- Topics: Finance & Investments; Modeling & Statistical Methods>Stochastic models
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A Multirisk Stochastic Process
function P(x). Assume that E(X~) = Pl > 0. The X~'s represent the claims, and p, is the expected value ... function (s < t) is 0 P{x(t ) < ylX(s) = x} p(x, s; y, t) = -~y u.n-- {y - • exp [ -~( t - s)l}'-n ...- Authors: John A Beekman, Harry H Panjer, UNKNOWN David Bellhouse, Clinton P Fuelling
- Date: Oct 1978
- Competency: Technical Skills & Analytical Problem Solving
- Publication Name: Transactions of the SOA
- Topics: Modeling & Statistical Methods>Stochastic models
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A New Collective Risk Model
aggregate premiums is greater than the initial reserve u is e, where ~ = 0.001 or some other appropriately ... X, -- t(t,, + X)] > . I = The "initial reserve u" may be considered to be an amount of money which ...- Authors: John A Beekman, Ethan Stroh, Richard W Ziock
- Date: Oct 1973
- Competency: Technical Skills & Analytical Problem Solving>Process and technique refinement
- Publication Name: Transactions of the SOA
- Topics: Modeling & Statistical Methods; Modeling & Statistical Methods>Stochastic models