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Conditional Stochastic Interest Rate Models in Life Contingencies
the determination of values of insurances and annuity functions. None of these papers consider the current ... evaluation of moments of interest, insurance and annuity functions. Numerical results are also given.- Authors: Harry H Panjer, UNKNOWN David Bellhouse
- Date: Jan 1981
- Competency: Technical Skills & Analytical Problem Solving>Process and technique refinement
- Publication Name: Actuarial Research Clearing House
- Topics: Modeling & Statistical Methods>Stochastic models
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An Actuarial Layman's Guide to Building Stochastic Interest Rate Generators
An Actuarial Layman's Guide to Building Stochastic Interest Rate Generators Without ... An Actuarial Layman's Guide to Building Stochastic Interest Rate Generators Without relying on formulas ...- Authors: James A Tilley
- Date: Oct 1992
- Competency: Technical Skills & Analytical Problem Solving>Process and technique refinement
- Publication Name: Transactions of the SOA
- Topics: Modeling & Statistical Methods>Stochastic models
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An Introduction to Collective Risk Theory and its Application to Stop-Loss Reinsurance
two kinds, external risks such as heavy excess mortality resulting from wars and epidemics, and the risk ... completely, and the values of G(y, t) are shown in Table 1 by way of example. The details are left to the ...- Authors: Ernest A Arvanitis, Russell M Collins, Paul H Jackson, Robert C Tookey, Paul Markham Kahn, Herbert L Feay
- Date: Oct 1962
- 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; Reinsurance>Stop-loss insurance
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Optimal Ruin Calculations Using Partial Stochastic Information
at time t is defined to be U(t) = u + ct - S(t), t>-O. Here U(0) = u is the initial surplus, c is ... fund in dollars per year, and S is the stochastic claims process: S(t) = X l + . . . + Xu(o, where ...- Authors: Samuel Cox, Patrick L Brockett
- Date: Oct 1984
- Competency: Technical Skills & Analytical Problem Solving>Process and technique refinement
- 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
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Esscher Approximations for Maximum Likelihood Estimates - Exploratory Ideas
Esscher Approximations for Maximum Likelihood Estimates - Exploratory Ideas The series ... density function, known to actuaries by Esscher's name and to statisticians as the saddlepoint approximation ...- Authors: James Bridgeman
- Date: Aug 2011
- Competency: Technical Skills & Analytical Problem Solving>Process and technique refinement
- Topics: Modeling & Statistical Methods>Dynamic simulation models; Modeling & Statistical Methods>Stochastic models
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CSTEP: a HPC Platform for Scenario Reduction Research on Efficient Stochastic Modeling - Representative Scenario Approach
CSTEP: a HPC Platform for Scenario Reduction Research on Efficient Stochastic Modeling - Representative ... modeled and projected by the stochastic modeler(s). Samples: The final outputs of CSTEP from the ...- Authors: Paul H Johnson, Yvonne Chueh
- Date: Aug 2011
- Competency: Technical Skills & Analytical Problem Solving>Process and technique refinement
- Topics: Modeling & Statistical Methods>Stochastic models; Technology & Applications>Analytics and informatics