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  • Mitigating Volatility of Retiree Health Valuation Results
    Mitigating Volatility of Retiree Health Valuation Results Exploration of sources of volatility in retiree health valuations, noting how volatility arises and might be mitigated, with discussion ...

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    • Authors: Jeffrey Petertil, Justin Petertil
    • Date: Sep 2012
    • Competency: External Forces & Industry Knowledge>Actuarial theory in business context; Professional Values>Practice expertise; Professional Values>Public interest representation; Technical Skills & Analytical Problem Solving>Innovative solutions; Technical Skills & Analytical Problem Solving>Process and technique refinement
    • Topics: Economics>Financial economics; Finance & Investments>Economic value; Health & Disability>Health insurance; Modeling & Statistical Methods>Deterministic models; Pensions & Retirement>Assumptions and methods; Pensions & Retirement>Retiree medical
  • An Actuarial Layman's Guide to Building Stochastic Interest Rate Generators
    An Actuarial Layman's Guide to Building Stochastic Interest Rate Generators This paper, originally published in 1992 in the Transactions of Society of Actuaries Vol. 44, deals with a topic ...

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    • Authors: Michael F Davlin, Merlin F Jetton, James A Tilley, Hal Warren Pedersen
    • Date: Oct 1992
    • Competency: External Forces & Industry Knowledge>Actuarial theory in business context
    • Topics: Economics>Financial economics; Modeling & Statistical Methods>Stochastic models
  • Bayesian Reserving Models Inspired by Chain Ladder Methods and Implemented Using WinBUGS
    Bayesian Reserving Models Inspired by Chain Ladder Methods and Implemented Using WinBUGS This paper examines some new Bayesian models for loss reserving inspired by a consideration of some of the ...

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    • Authors: David Scollnik
    • Date: Sep 2008
    • Competency: External Forces & Industry Knowledge>Actuarial theory in business context
    • Topics: Economics>Financial economics; Modeling & Statistical Methods>Bayesian methods; Modeling & Statistical Methods>Stochastic models