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Predictive Modeling Applications in Actuarial Science

Volume 1. Predictive Modeling Techniques

$84.99

Part of International Series on Actuarial Science

Edward W. Frees, Richard A. Derrig, Marjorie Rosenberg, Montserrat Guillen, Jean-Philippe Boucher, Curtis Gary Dean, Katrien Antonio, Yanwei Zhang, Vytaras Brazauskas, Harald Dornheim, Ponmalar Ratnam, Peng Shi, Eike Brechmann, Claudia Czado, Louise Francis, Brian Hartman, Luis Nieto-Barajas, Enrique de Alba, Patrick L. Brockett, Shuo-Li Chuang, Utai Pitaktong, Katrien Antonio, Piet de Jong, Greg Taylor, Jim Robinson, Bruce Jones, Weijia Wu
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  • Date Published: July 2014
  • availability: Available
  • format: Hardback
  • isbn: 9781107029873

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  • Predictive modeling involves the use of data to forecast future events. It relies on capturing relationships between explanatory variables and the predicted variables from past occurrences and exploiting this to predict future outcomes. Forecasting future financial events is a core actuarial skill - actuaries routinely apply predictive-modeling techniques in insurance and other risk-management applications. This book is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples of predictive modeling. The book also addresses the needs of more seasoned practising analysts who would like an overview of advanced statistical topics that are particularly relevant in actuarial practice. Predictive Modeling Applications in Actuarial Science emphasizes lifelong learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used by analysts to gain a competitive advantage in situations with complex data.

    • Provides a link between data analysis and data modeling by explaining the role of a model
    • Introduces advanced statistical techniques that can be used by analysts to gain a competitive advantage in situations with complex data
    • Aimed at both novice and seasoned practising analysts who would like an overview of advanced statistical topics that are particularly relevant in actuarial practice
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    Reviews & endorsements

    'With contributions coming from a wide variety of researchers, professors, and actuaries - including several CAS Fellows - it's clear that this book will be valuable for any P and C actuary whose main concern is using predictive modeling in his or her own work.' David Zornek, Actuarial Review

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    Product details

    • Date Published: July 2014
    • format: Hardback
    • isbn: 9781107029873
    • length: 563 pages
    • dimensions: 255 x 179 x 37 mm
    • weight: 1.12kg
    • contains: 120 b/w illus. 94 tables 26 exercises
    • availability: Available
  • Table of Contents

    1. Predictive modeling in actuarial science Edward W. Frees and Richard A. Derrig
    Part I. Predictive Modeling Foundations:
    2. Overview of linear models Marjorie Rosenberg
    3. Regression with categorical dependent variables Montserrat Guillen
    4. Regression with count-dependent variables Jean-Philippe Boucher
    5. Generalized linear models Curtis Gary Dean
    6. Frequency and severity models Edward W. Frees
    Part II. Predictive Modeling Methods:
    7. Longitudinal and panel data models Edward W. Frees
    8. Linear mixed models Katrien Antonio and Yanwei Zhang
    9. Credibility and regression modeling Vytaras Brazauskas, Harald Dornheim and Ponmalar Ratnam
    10. Fat-tailed regression models Peng Shi
    11. Spatial modeling Eike Brechmann and Claudia Czado
    12. Unsupervised learning Louise Francis
    Part III. Bayesian and Mixed Modeling:
    13. Bayesian computational methods Brian Hartman
    14. Bayesian regression models Luis Nieto-Barajas and Enrique de Alba
    15. Generalized additive models and nonparametric regression Patrick L. Brockett, Shuo-Li Chuang and Utai Pitaktong
    16. Non-linear mixed models Katrien Antonio and Yanwei Zhang
    Part IV. Longitudinal Modeling:
    17. Time series analysis Piet de Jong
    18. Claims triangles/loss reserves Greg Taylor
    19. Survival models Jim Robinson
    20. Transition modeling Bruce Jones and Weijia Wu.

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    Predictive Modeling Applications in Actuarial Science

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  • Editors

    Edward W. Frees, University of Wisconsin, Madison

    Richard A. Derrig, Temple University, Philadelphia

    Glenn Meyers, ISO Innovative Analytics, New Jersey

    Contributors

    Edward W. Frees, Richard A. Derrig, Marjorie Rosenberg, Montserrat Guillen, Jean-Philippe Boucher, Curtis Gary Dean, Katrien Antonio, Yanwei Zhang, Vytaras Brazauskas, Harald Dornheim, Ponmalar Ratnam, Peng Shi, Eike Brechmann, Claudia Czado, Louise Francis, Brian Hartman, Luis Nieto-Barajas, Enrique de Alba, Patrick L. Brockett, Shuo-Li Chuang, Utai Pitaktong, Katrien Antonio, Piet de Jong, Greg Taylor, Jim Robinson, Bruce Jones, Weijia Wu

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