Refine your search
31 - 40 of 225 results (0.24 seconds)
Sort By:
  • A Stochastic Investment Model

    A Stochastic Investment Model The purpose of this paper is to provide a method for calculating special contingency reserves for investment losses. The method is derived by first building a ...

    View Description

    • 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
  • An Overview of Probabilistic Fuzzy Systems -- Some Preliminary

    An Overview of Probabilistic Fuzzy Systems -- Some Preliminary This abstract describes a paper that presents preliminary observations with respect to probabilistic fuzzy systems. modeling; ...

    View Description

    • Authors: Arnold Shapiro, Dabuxilatu Wang
    • Date: Apr 2018
    • Competency: External Forces & Industry Knowledge
    • Topics: Modeling & Statistical Methods>Stochastic models
  • Implementation of Arbitrage-free Discretization of Interest Rate Dynamics and Calibration via Swaptions and Caps in Excel VBA

    Implementation of Arbitrage-free Discretization of Interest Rate Dynamics and Calibration via Swaptions and Caps in Excel VBA We consider Libor market model and calibration process. We estimate ...

    View Description

    • Authors: Ohoe Kim, Swathi D Gaddam
    • Date: Jan 2007
    • Competency: Technical Skills & Analytical Problem Solving>Process and technique refinement
    • Topics: Economics>Financial economics; Finance & Investments>Derivatives; Modeling & Statistical Methods>Asset modeling; Modeling & Statistical Methods>Stochastic models
  • The Distribution of Discounted Compound Renewal Sums

    The Distribution of Discounted Compound Renewal Sums This is a presentation from 43rd Actuarial Research Conference ARC, Regina, August 14–16, 2008. This talk will present the moment generating ...

    View Description

    • Authors: José Garrido, GHISLAIN LEVEILLE, Ya Fang Wang
    • Date: Nov 2008
    • Competency: External Forces & Industry Knowledge>Actuarial theory in business context
    • Topics: Finance & Investments>Risk measurement - Finance & Investments; Modeling & Statistical Methods>Stochastic models
  • A Loss Reserving Model within the framework of Generalized Linear Models

    A Loss Reserving Model within the framework of Generalized Linear Models This research was funded by the Natural Sciences and Engineering Research Council of Canada [NSERC] Discovery Grant ...

    View Description

    • Authors: José Garrido, JUN ZHOU
    • Date: May 2009
    • Competency: External Forces & Industry Knowledge>Actuarial theory in business context
    • Topics: Finance & Investments>Risk measurement - Finance & Investments; Modeling & Statistical Methods>Estimation methods; Modeling & Statistical Methods>Stochastic models
  • A Multi-Stakeholder Approach to Capital Adequacy

    A Multi-Stakeholder Approach to Capital Adequacy This paper is Part 1 of a two-part submission. Part 2, “An Alternative Approach to Capital Allocation,” discusses using risk-replicating ...

    View Description

    • Authors: Robert Painter, Dan Isaac
    • Date: May 2007
    • Competency: Technical Skills & Analytical Problem Solving>Incorporate risk management; Technical Skills & Analytical Problem Solving>Innovative solutions
    • Publication Name: Actuarial Practice Forum
    • Topics: Enterprise Risk Management>Capital management - ERM; Enterprise Risk Management>Risk measurement - ERM; Finance & Investments>Economic capital; Modeling & Statistical Methods>Stochastic models
  • Development of a Simulation-based Model to Quantify the Degree of a Bank’s Liquidity Risk

    Development of a Simulation-based Model to Quantify the Degree of a Bank’s Liquidity Risk 2011 Enterprise Risk Management Symposium, Chicago. This study investigates whether simulation-based ...

    View Description

    • Authors: Sadi Bin Asad Farooqui
    • Date: Mar 2011
    • Competency: External Forces & Industry Knowledge; Results-Oriented Solutions; Technical Skills & Analytical Problem Solving
    • Topics: Enterprise Risk Management; Global Perspectives; Modeling & Statistical Methods>Stochastic models; Public Policy
  • RILA GLWB Designs and Market Risk Analysis

    RILA GLWB Designs and Market Risk Analysis An overview of guaranteed lifetime withdrawal benefits (GLWB) on registered index-linkedannuity (RILA) products and a stochastic analysis of market ...

    View Description

    • Authors: Matthew Kevin Heaphy, Nicholas Carbo, David J Elliott
    • Date: May 2023
    • Competency: Results-Oriented Solutions; Technical Skills & Analytical Problem Solving
    • Publication Name: Product Matters!
    • Topics: Annuities; Annuities>Equity-indexed annuities; Annuities>Guaranteed living benefits; Modeling & Statistical Methods; Modeling & Statistical Methods>Sensitivity testing; Modeling & Statistical Methods>Stochastic models; Annuities>Deferred annuities; Annuities>Living / Death benefit riders
  • Actuarial Sciences and Uncertainties

    Actuarial Sciences and Uncertainties In this article the author cautions against the temptation to extend stochastic modeling into areas of unpredictable parameters and probabilities. He ...

    View Description

    • Authors: Francisco Bayo
    • Date: May 1988
    • Competency: Technical Skills & Analytical Problem Solving
    • Publication Name: The Actuary Magazine
    • Topics: Actuarial Profession; Modeling & Statistical Methods>Stochastic models
  • Generating Stochastic Interest Rate Scenarios

    Generating Stochastic Interest Rate Scenarios This session from the 1995 SOA Boston Meeting covers a general overview of basic interest rate models, the meaning of an arbitrage free model, the ...

    View Description

    • Authors: David N Becker, Michael F Davlin, Gordon E Klein, Mark S Tenney, Craig Merrill
    • Date: Oct 1995
    • Competency: Technical Skills & Analytical Problem Solving
    • Publication Name: Record of the Society of Actuaries
    • Topics: Modeling & Statistical Methods>Stochastic models