Generalized Linear Models for Insurance Rating

Generalized Linear Models for Insurance Rating PDF Author: Mark Goldburd
Publisher:
ISBN: 9780996889728
Category :
Languages : en
Pages : 106

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Book Description

Generalized Linear Models for Insurance Rating

Generalized Linear Models for Insurance Rating PDF Author: Mark Goldburd
Publisher:
ISBN: 9780996889728
Category :
Languages : en
Pages : 106

Get Book Here

Book Description


Generalized Linear Models for Insurance Data

Generalized Linear Models for Insurance Data PDF Author: Piet de Jong
Publisher: Cambridge University Press
ISBN: 1139470477
Category : Business & Economics
Languages : en
Pages : 207

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Book Description
This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are provided on the website.

Non-Life Insurance Pricing with Generalized Linear Models

Non-Life Insurance Pricing with Generalized Linear Models PDF Author: Esbjörn Ohlsson
Publisher: Springer Science & Business Media
ISBN: 3642107915
Category : Mathematics
Languages : en
Pages : 181

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Book Description
Non-life insurance pricing is the art of setting the price of an insurance policy, taking into consideration varoius properties of the insured object and the policy holder. Introduced by British actuaries generalized linear models (GLMs) have become today a the standard aproach for tariff analysis. The book focuses on methods based on GLMs that have been found useful in actuarial practice and provides a set of tools for a tariff analysis. Basic theory of GLMs in a tariff analysis setting is presented with useful extensions of standarde GLM theory that are not in common use. The book meets the European Core Syllabus for actuarial education and is written for actuarial students as well as practicing actuaries. To support reader real data of some complexity are provided at www.math.su.se/GLMbook.

Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance

Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance PDF Author: Edward W. Frees
Publisher: Cambridge University Press
ISBN: 1316720527
Category : Business & Economics
Languages : en
Pages : 337

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Book Description
Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries routinely apply in insurance and other risk-management applications. Predictive Modeling Applications in Actuarial Science emphasizes life-long learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used to gain a competitive advantage in situations with complex data. Volume 2 examines applications of predictive modeling. Where Volume 1 developed the foundations of predictive modeling, Volume 2 explores practical uses for techniques, focusing on property and casualty insurance. Readers are exposed to a variety of techniques in concrete, real-life contexts that demonstrate their value and the overall value of predictive modeling, for seasoned practicing analysts as well as those just starting out.

Modern Actuarial Risk Theory

Modern Actuarial Risk Theory PDF Author: Rob Kaas
Publisher: Springer Science & Business Media
ISBN: 3540867368
Category : Business & Economics
Languages : en
Pages : 394

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Book Description
Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics. This second and.

Pricing in General Insurance

Pricing in General Insurance PDF Author: Pietro Parodi
Publisher: CRC Press
ISBN: 1466581441
Category : Business & Economics
Languages : en
Pages : 590

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Book Description
Based on the syllabus of the actuarial industry course on general insurance pricing — with additional material inspired by the author’s own experience as a practitioner and lecturer — Pricing in General Insurance presents pricing as a formalised process that starts with collecting information about a particular policyholder or risk and ends with a commercially informed rate. The main strength of this approach is that it imposes a reasonably linear narrative on the material and allows the reader to see pricing as a story and go back to the big picture at any time, putting things into context. Written with both the student and the practicing actuary in mind, this pragmatic textbook and professional reference: Complements the standard pricing methods with a description of techniques devised for pricing specific products (e.g., non-proportional reinsurance and property insurance) Discusses methods applied in personal lines when there is a large amount of data and policyholders can be charged depending on many rating factors Addresses related topics such as how to measure uncertainty, incorporate external information, model dependency, and optimize the insurance structure Provides case studies, worked-out examples, exercises inspired by past exam questions, and step-by-step methods for dealing concretely with specific situations Pricing in General Insurance delivers a practical introduction to all aspects of general insurance pricing, covering data preparation, frequency analysis, severity analysis, Monte Carlo simulation for the calculation of aggregate losses, burning cost analysis, and more.

Generalized Linear Models With Examples in R

Generalized Linear Models With Examples in R PDF Author: Peter K. Dunn
Publisher: Springer
ISBN: 1441901183
Category : Mathematics
Languages : en
Pages : 573

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Book Description
This textbook presents an introduction to generalized linear models, complete with real-world data sets and practice problems, making it applicable for both beginning and advanced students of applied statistics. Generalized linear models (GLMs) are powerful tools in applied statistics that extend the ideas of multiple linear regression and analysis of variance to include response variables that are not normally distributed. As such, GLMs can model a wide variety of data types including counts, proportions, and binary outcomes or positive quantities. The book is designed with the student in mind, making it suitable for self-study or a structured course. Beginning with an introduction to linear regression, the book also devotes time to advanced topics not typically included in introductory textbooks. It features chapter introductions and summaries, clear examples, and many practice problems, all carefully designed to balance theory and practice. The text also provides a working knowledge of applied statistical practice through the extensive use of R, which is integrated into the text. Other features include: • Advanced topics such as power variance functions, saddlepoint approximations, likelihood score tests, modified profile likelihood, small-dispersion asymptotics, and randomized quantile residuals • Nearly 100 data sets in the companion R package GLMsData • Examples that are cross-referenced to the companion data set, allowing readers to load the data and follow the analysis in their own R session

Computational Actuarial Science with R

Computational Actuarial Science with R PDF Author: Arthur Charpentier
Publisher: CRC Press
ISBN: 1498759823
Category : Business & Economics
Languages : en
Pages : 652

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Book Description
A Hands-On Approach to Understanding and Using Actuarial ModelsComputational Actuarial Science with R provides an introduction to the computational aspects of actuarial science. Using simple R code, the book helps you understand the algorithms involved in actuarial computations. It also covers more advanced topics, such as parallel computing and C/

Statistical and Probabilistic Methods in Actuarial Science

Statistical and Probabilistic Methods in Actuarial Science PDF Author: Philip J. Boland
Publisher: CRC Press
ISBN: 158488696X
Category : Business & Economics
Languages : en
Pages : 368

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Book Description
Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science, and finance. The book builds on students' existing knowledge of probability and statistics by establishing a solid and thorough understanding of

Generalized Linear Models

Generalized Linear Models PDF Author: P. McCullagh
Publisher: Routledge
ISBN: 1351445855
Category : Mathematics
Languages : en
Pages : 532

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Book Description
The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural, biological, health, engineering, and ot