Book Description
Based on a loss function approach, this comprehensive reference reviews the most recent advances in financial and actuarial modeling, providing a strong statistical background for advanced methods in pension plan structuring, risk estimation, and modeling of investment and options pricing. An authoritative tool supplying every conceptual model and technique required by the modern financial investigator, Financial and Actuarial Statistics offers an analysis of American options models, mortality adjustment factors for increased risk individuals, time trend regression adjustments for mortality tables, and simulation approaches for stochastic models.
Book Description
A modern practical guide to building and using actuarial models.
Loss Models: From Data to Decisions is organized around the principle that actuaries build models in order to analyze risks and make decisions about managing the risks based on conclusions drawn from the analysis. In practice, one begins with data and ends with a business decision. The book flows logically from this principle. It begins with a framework for model building and a description of frequency and severity loss data typically available to actuaries. Parametric models are emphasized throughout.
The frequency and severity models are used in building aggregate loss models, in credibility-based pricing models, and in loss analysis over multiple time periods.
Designed as both an educational text as well as a professional reference, Loss Models:
- Assumes little prior knowledge of insurance systems
- Features many fascinating examples taken from insurance files
- Contains a major instructive case study continued through each chapter
- Covers the classical areas of risk theory and loss distributions
- Gives a practical but rigorous treatment of modern credibility theory
- Uses standard statistical concepts, methods, and notation
- Provides modern computational algorithms for implementing methods
- Includes free companion software available from an FTP site
- Deals with many topics on CAS 4B and SOA 151 and 152 actuarial exams
- Includes many exercises based on past CAS and SOA exams.
Customer Reviews:
Good one but for advance users.......2007-03-01
Nothing else to say. The best book for actuarial mathematics. Also good for risk managers, in particular for operational risk. It does not introduce many concepts but rather take to advance level. Excellent concepts that can be applicable in any topic or situation. A must buy in you want to have your grips on acturial mathematics and concepts
Best Actuarial Book.......2007-02-22
Nothing else to say. The best book for actuarial mathematics. Also good for risk managers, in particular for operational risk.
great introduction to models needed in insurance.......2000-08-09
When I took a job to model prediction of loss reserves for workers compensation insurance, I began to realize that the traditional statistical methods that I generally relied n would not help me (without modification). The required modification would be either to transform variables or to model long-tailed probability distributions. This is because in the insurance business you have to reserve for those big catastrophies. The cost data for workers compensation data generally show a high frequency of low to moderate costs (say in the range of $1000 to $50,000). However occasionally there are a few cases of severe injury causing permanent disability which could run over 1 million dollars. Even though the probability of occurrence is small the cost is so high that it cannot be ignored. Such claims will surely be found when large insurance company cover millions of employees over many years.
The problem occurs when insuring for floods, earthquakes, fires and other disasters. Stuart Klugman and Bob Hogg in 1984 wrote the first introductory text to acquaint statisticians with such probability models that are important in the insurance business. Other books covering the subject were covered in books on risk theory designed for actuaries. This book covers all the topics and assumes mathematical and staistical knowledge at the level of the book by Hogg and Craig (so some calculus is required).
great introduction to models needed in insurance.......2000-08-09
When I took a job to model prediction of loss reserves for workers compensation insurance, I began to realize that the traditional statistical methods that I generally relied n would not help me (without modification). The required modification would be either to transform variables or to model long-tailed probability distributions. This is because in the insurance business you have to reserve for those big catastrophies. The cost data for workers compensation data generally show a high frequency of low to moderate costs... . However occasionally there are a few cases of sever injury causing permanent disability which could run over 1 million dollars. Even though the probability of occurrence is small the cost is so high that it cannot be ignored. Such claims will surely be found when large insurance company cover millions of employees over many years.
The problem occurs when insuring for floods, earthquakes, fires and other disasters. Stuart Klugman and Bob Hogg in 1984 wrote the first introductory text to acquaint statisticians with such probability models that are important in the insurance business. Other books covering the subject were covered in books on risk theory designed for actuaries. This book covers all the topics and assumes mathematical and staistical knowledge at the level of the book by Hogg and Craig (so some calculus is required).
Book Description
Based on the author's experience of teaching final-year actuarial students in Britain and Australia, and suitable for a first course in insurance risk theory, this book focuses on the two major areas of risk theory - aggregate claims distributions and ruin theory. For aggregate claims distributions, detailed descriptions are given of recursive techniques that can be used in the individual and collective risk models. For the collective model, different classes of counting distribution are discussed, and recursion schemes for probability functions and moments presented. For the individual model, the three most commonly applied techniques are discussed and illustrated. Care has been taken to make the book accessible to readers who have a solid understanding of the basic tools of probability theory. Numerous worked examples are included in the text and each chapter concludes with exercises, which have answers in the book and full solutions available for instructors from www.cambridge.org.
Book Description
Revised, updated, and even more useful to students, teachers, and practicing professionals
The First Edition of Loss Models was deemed "worthy of classical status" by the Journal of the International Statistical Institute. While retaining its predecessor's thorough treatment of the concepts and methods of analyzing contingent events, this powerful Second Edition is updated and expanded to offer even more complete and flexible coverage of risk theory, loss distributions, and survival models.
Beginning with a framework for model building and a description of frequency and severity loss data typically available, it shows readers how to combine frequency, severity, and loss models to build aggregate loss models and credibility-based pricing models, and how to analyze loss over multiple time periods. Important features of this new edition include:
* Thorough preparation for relevant parts of preliminary examinations of the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS)
* Exercises based on past SOA and CAS exams
* Examples using actual insurance data
* Practical treatment of modern credibility theory
* Data files and more from an ftp site
Loss Models, Second Edition is an important resource, providing a comprehensive, practically motivated toolkit and an excellent reference, for actuaries preparing for SOA and CAS preliminary examinations, students in actuarial science who need to understand loss and risk models, and practicing professionals involved in loss modeling.
Book Description
Incorporates the many tools needed for modeling and pricing in finance and insurance
Introductory Stochastic Analysis for Finance and Insurance introduces readers to the topics needed to master and use basic stochastic analysis techniques for mathematical finance. The author presents the theories of stochastic processes and stochastic calculus and provides the necessary tools for modeling and pricing in finance and insurance. Practical in focus, the book's emphasis is on application, intuition, and computation, rather than theory.
Consequently, the text is of interest to graduate students, researchers, and practitioners interested in these areas. While the text is self-contained, an introductory course in probability theory is beneficial to prospective readers.
This book evolved from the author's experience as an instructor and has been thoroughly classroom-tested. Following an introduction, the author sets forth the fundamental information and tools needed by researchers and practitioners working in the financial and insurance industries:
* Overview of Probability Theory
* Discrete-Time stochastic processes
* Continuous-time stochastic processes
* Stochastic calculus: basic topics
The final two chapters, Stochastic Calculus: Advanced Topics and Applications in Insurance, are devoted to more advanced topics. Readers learn the Feynman-Kac formula, the Girsanov's theorem, and complex barrier hitting times distributions. Finally, readers discover how stochastic analysis and principles are applied in practice through two insurance examples: valuation of equity-linked annuities under a stochastic interest rate environment and calculation of reserves for universal life insurance.
Throughout the text, figures and tables are used to help simplify complex theory and pro-cesses. An extensive bibliography opens up additional avenues of research to specialized topics.
Ideal for upper-level undergraduate and graduate students, this text is recommended for one-semester courses in stochastic finance and calculus. It is also recommended as a study guide for professionals taking Causality Actuarial Society (CAS) and Society of Actuaries (SOA) actuarial examinations.
Download Description
Incorporates the many tools needed for modeling and pricing in finance and insurance Introductory Stochastic Analysis for Finance and Insurance introduces readers to the topics needed to master and use basic stochastic analysis techniques for mathematical finance. The author presents the theories of stochastic processes and stochastic calculus and provides the necessary tools for modeling and pricing in finance and insurance. Practical in focus, the bok's emphasis is on application, intuition, and computation, rather than theory. Consequently, the text is of interest to graduate students, researchers, and practitioners interested in these areas. While the text is self-contained, an introductory course in probability theory is beneficial to prospective readers. This book evolved from the author's experience as an instructor and has been thoroughly classroom-tested. Following an introduction, the author sets forth the fundamental information and tools needed by researchers and practitioners working in the financial and insurance industries: Overview of Probability Theory Discrete-Time stochastic processes Continuous-time stochastic processes Stochastic calculus: basic topics The final two chapters, Stochastic Calculus: Advanced Topics and Applications in Insurance, are devoted to more advanced topics. Readers learn the Feynman-Kac formula, the Girsanov's theorem, and complex barrier hitting times distributions. Finally, readers discover how stochastic analysis and principles are applied in practice through two insurance examples: valuation of equity-linked annuities under a stochastic interest rate environment and calculation of reserves for universal life insurance. Throughout the text, figures and tables are used to help simplify complex theory and pro-cesses. An extensive bibliography opens up additional avenues of research to specialized topics. Ideal for upper-level undergraduate and graduate students, this text is recommended for one-semester courses in stochastic finance and calculus. It is also recommended as a study guide for professionals taking Causality Actuarial Society (CAS) and Society of Actuaries (SOA) actuarial examinations.
Average customer rating:
|
Actuarial Models for Disability Insurance
Steven Haberman , and
E Pitacco
Manufacturer: Chapman & Hall/CRC
ProductGroup: Book
Binding: Hardcover
 Economics
| Business & Investing
| Subjects
| Books
| Agricultural
| Commercial Policy
| Comparative
| Consolidation & Merger
| Cooperatives
| Debt & Deficits
| Development & Growth
| Econometrics
| Economic Conditions
| Economic History
| Economic Policy & Development
| Exports & Imports
| Free Enterprise
| Inflation
| International
| Labor & Industrial Relations
| Macroeconomics
| Microeconomics
| Money & Monetary Policy
| Natural Resources
| Privatization
| Public Finance
| Statistics
| Sustainable Development
| Theory
| Unemployment
| Urban & Regional
General
| Insurance
| Industries & Professions
| Business & Investing
| Subjects
| Books
Health
| Insurance
| Industries & Professions
| Business & Investing
| Subjects
| Books
Social Services & Welfare
| Poverty
| Current Events
| Nonfiction
| Subjects
| Books
General
| Science
| Subjects
| Books
General
| Mathematics
| Science
| Subjects
| Books
Probability & Statistics
| Applied
| Mathematics
| Science
| Subjects
| Books
Practice Management & Reimbursement
| Administration & Policy
| Medicine
| Subjects
| Books
Medicaid & Medicare
| Administration & Policy
| Medicine
| Subjects
| Books
Insurance Law
| Business
| Law
| Subjects
| Books
General
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
Statistics
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
Insurance Law
| Business
| Law
| Professional & Technical
| Subjects
| Books
Medicaid & Medicare
| Administration & Medicine Economics
| Medical
| Professional & Technical
| Subjects
| Books
Practice Management & Reimbursement
| Administration & Medicine Economics
| Medical
| Professional & Technical
| Subjects
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Similar Items:
-
Loss Models: From Data to Decisions, Second Edition
ASIN: 0849303893 |
Book Description
Disability insurance, long-term care insurance, and critical illness cover are becoming increasingly important in developed countries as the problems of demographic aging come to the fore. The private sector insurance industry is providing solutions to problems resulting from these pressures and other demands of better educated and more prosperous populations. Actuarial Models for Disability Insurance examines the actuarial structure of disability insurance, long-term care insurance, and critical illness cover, including problems encountered in the design and development of such insurances. Actuarial problems such as pricing and reserving are considered within the context of multiple state modeling, providing a vigorous and sound framework for analyzing personal insurances.
Book Description
Ideal for students preparing for level 300 actuarial exams in the US, Actuarial Models: The Mathematics of Insurance provides a comprehensive exposition of insurance process models and presents mathematical setups and methods used in Actuarial Modeling. Divided into three self-contained and explicitly designated parts of different levels of difficulty, this book examines standard as well as advanced topics such as modern utility theory, martingale technique, models with payments of dividends, reinsurance models, and classification of distributions. It provides practical skills in analysis of insurance processes. This text discusses a number of topics not commonly found in existing Actuarial Mathematics textbooks, including achievements of the modern Risk Evaluation theory, premium principles, accuracy of normal and Poisson approximation, and a reinsurance market model. The main text is preceded by introductory chapters containing basic facts from Probability Theory, Calculus, and the Theory of Interest. The reader will not have to refer to outside sources; everything is under one cover and in the same unified notation and style. The book includes many examples, practice problems, and exercises on numerical calculations using Excel®. It includes preliminary examination material for the Society of Actuaries and the Casualty Actuarial Society (CAS), providing, in particular, real problems from past CAS exams.
Average customer rating:
|
Stochastic Processes for Insurance and Finance (Wiley Series in Probability and Statistics)
Tomasz Rolski ,
Hanspeter Schmidli ,
Volker Schmidt , and
Jozef Teugels
Manufacturer: Wiley
ProductGroup: Book
Binding: Hardcover
Public Finance
| Economics
| Business & Investing
| Subjects
| Books
Statistics
| Economics
| Business & Investing
| Subjects
| Books
General
| Business & Investing
| Subjects
| Books
General
| Insurance
| Industries & Professions
| Business & Investing
| Subjects
| Books
Social Services & Welfare
| Poverty
| Current Events
| Nonfiction
| Subjects
| Books
Probability & Statistics
| Applied
| Mathematics
| Science
| Subjects
| Books
Statistics
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
Stochastic Modeling
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
General
| Finance
| Accounting & Finance
| Professional & Technical
| Subjects
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
ASIN: 0471959251 |
Book Description
Stochastic Processes for Insurance and Finance offers a thorough yet accessible reference for researchers and practitioners of insurance mathematics. Building on recent and rapid developments in applied probability, the authors describe in general terms models based on Markov processes, martingales and various types of point processes.
Discussing frequently asked insurance questions, the authors present a coherent overview of the subject and specifically address:
· The principal concepts from insurance and finance
· Practical examples with real life data
· Numerical and algorithmic procedures essential for modern insurance practices
Assuming competence in probability calculus, this book will provide a fairly rigorous treatment of insurance risk theory recommended for researchers and students interested in applied probability as well as practitioners of actuarial sciences.
Wiley Series in Probability and Statistics
Books:
- Financial Management of Health Care Organizations: An Introduction to Fundamental Tools, Concepts, and Applications
- Financial Reporting, Financial Statement Analysis, and Valuation: A Strategic Perspective (with Thomson One Access Code)
- Financial Theory and Corporate Policy (4th Edition) (The Addison-Wesley Series in Finance)
- Food Not Lawns: How to Turn Your Yard into a Garden And Your Neighborhood into a Community
- For One More Day
- Forecasting Financial Markets: Technical Analysis and the Dynamics of Price
- Freakonomics [Revised and Expanded]: A Rogue Economist Explores the Hidden Side of Everything
- Getting Started in Currency Trading: Winning in Todays Hottest Marketplace (Getting Started In.....)
- Harrington on Hold 'em Expert Strategy for No Limit Tournaments, Vol. 1: Strategic Play
- History: Fiction or Science? (Chronology, No. 1)
Books Index
Books Home
Recommended Books
- The Tuskegee Airmen: The Men Who Changed a Nation
- The Dog Listener: Learn How to Communicate with Your Dog for Willing Cooperation
- Macclade 4: Analysis of Phylogeny and Character Evolution
- Molecular Genetics of Bacteria
- Piezoelectric Sensors
- StrengthsFinder 2.0: A New and Upgraded Edition of the Online Test from Gallup's Now, Discover Your
- The Bishop in the West Wing: A Bishop Blackie Ryan Novel
- Cool Restaurants Miami
- Nightmares in the Sky: Gargoyles and Grotesques
- Purgatory Ridge
Fundamentals of Actuarial Mathematics
Modern Actuarial Theory and Practice, Second Edition
The Calculus of Retirement Income: Financial Models for Pension Annuities and Life Insurance
Actuarial Models: The Mathematics of Insurance
