Actuarial Exam Tactics
Author | : Mike Jennings |
Publisher | : |
Total Pages | : |
Release | : 2017 |
Genre | : Actuarial science |
ISBN | : 9781635880397 |
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Author | : Mike Jennings |
Publisher | : |
Total Pages | : |
Release | : 2017 |
Genre | : Actuarial science |
ISBN | : 9781635880397 |
Author | : Michel Denuit |
Publisher | : Springer Nature |
Total Pages | : 228 |
Release | : 2020-11-16 |
Genre | : Business & Economics |
ISBN | : 303057556X |
This book summarizes the state of the art in tree-based methods for insurance: regression trees, random forests and boosting methods. It also exhibits the tools which make it possible to assess the predictive performance of tree-based models. Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and numerical illustrations or case studies. All numerical illustrations are performed with the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. In particular, master's students in actuarial sciences and actuaries wishing to update their skills in machine learning will find the book useful. This is the second of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance.
Author | : Michel Denuit |
Publisher | : Springer Nature |
Total Pages | : 452 |
Release | : 2019-09-03 |
Genre | : Business & Economics |
ISBN | : 3030258203 |
This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and case studies, providing numerical illustrations using the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. This is the first of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. Although closely related to the other two volumes, this volume can be read independently.
Author | : Edward W. Frees |
Publisher | : Cambridge University Press |
Total Pages | : 585 |
Release | : 2010 |
Genre | : Business & Economics |
ISBN | : 0521760119 |
This book teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.
Author | : Mario V. Wüthrich |
Publisher | : Springer Nature |
Total Pages | : 611 |
Release | : 2022-11-22 |
Genre | : Mathematics |
ISBN | : 303112409X |
This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus.
Author | : Samuel A. Broverman |
Publisher | : |
Total Pages | : |
Release | : 2004 |
Genre | : Actuaries |
ISBN | : 9781566985024 |
Author | : United States. Social Security Administration. Office of the Actuary |
Publisher | : |
Total Pages | : 558 |
Release | : 1937 |
Genre | : Old age pensions |
ISBN | : |
Author | : Fred Szabo |
Publisher | : Academic Press |
Total Pages | : 297 |
Release | : 2012-06-25 |
Genre | : Mathematics |
ISBN | : 0123869897 |
What would you like to do with your life? What career would allow you to fulfill your dreams of success? If you like mathematics—and the prospect of a highly mobile, international profession—consider becoming an actuary. Szabo's Actuaries' Survival Guide, Second Edition explains what actuaries are, what they do, and where they do it. It describes exciting combinations of ideas, techniques, and skills involved in the day-to-day work of actuaries. This second edition has been updated to reflect the rise of social networking and the internet, the progress toward a global knowledge-based economy, and the global expansion of the actuarial field that has occurred since the first edition. - Includes details on the new structures of the Society of Actuaries' (SOA) and Casualty Actuarial Society (CAS) examinations, as well as sample questions and answers - Presents an overview of career options, includes profiles of companies & agencies that employ actuaries. - Provides a link between theory and practice and helps readers understand the blend of qualitative and quantitative skills and knowledge required to succeed in actuarial exams - Includes insights provided by over 50 actuaries and actuarial students about the actuarial profession - Author Fred Szabo has directed the Actuarial Co-op Program at Concordia for over fifteen years
Author | : United States. Social Security Administration. Office of the Actuary |
Publisher | : |
Total Pages | : 920 |
Release | : 1966 |
Genre | : Social security |
ISBN | : |
Author | : David C. M. Dickson |
Publisher | : Cambridge University Press |
Total Pages | : 180 |
Release | : 2012-03-26 |
Genre | : Business & Economics |
ISBN | : 1107608449 |
"This manual presents solutions to all exercises from Actuarial Mathematics for Life Contingent Risks (AMLCR) by David C.M. Dickson, Mary R. Hardy, Howard Waters; Cambridge University Press, 2009. ISBN 9780521118255"--Pref.