Financial Mathematics for Actuaries: 3rd Edition, Wai-Sum Chan, Yiu-Kuen Tse

Автор: Wai-Sum Chan, Yiu-Kuen Tse
Название: Financial Mathematics for Actuaries: 3rd Edition
ISBN: 9811245673 ISBN-13(EAN): 9789811245671
Издательство: World Scientific Publishing
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Описание: This book provides a thorough understanding of the fundamental concepts of financial mathematics essential for the evaluation of any financial product and instrument. Mastering concepts of present and future values of streams of cash flows under different interest rate environments is core for actuaries and financial economists. This book covers the body of knowledge required by the Society of Actuaries (SOA) for its Financial Mathematics (FM) Exam.The third edition includes major changes such as an addition of an 'R Laboratory' section in each chapter, except for Chapter 9. These sections provide R codes to do various computations, which will facilitate students to apply conceptual knowledge. Additionally, key definitions have been revised and the theme structure has been altered. Students studying undergraduate courses on financial mathematics for actuaries will find this book useful. This book offers numerous examples and exercises, some of which are adapted from previous SOA FM Exams. It is also useful for students preparing for the actuarial professional exams through self-study.

Автор: Michel Denuit; Donatien Hainaut; Julien Trufin
Название: Effective Statistical Learning Methods for Actuaries III
ISBN: 3030258262 ISBN-13(EAN): 9783030258269
Издательство: Springer
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Описание: This book reviews some of the most recent developments in neural networks, with a focus on applications in actuarial sciences and finance. It simultaneously introduces the relevant tools for developing and analyzing neural networks, in a style that is mathematically rigorous yet accessible.Artificial intelligence and neural networks offer a powerful alternative to statistical methods for analyzing data. Various topics are covered from feed-forward networks to deep learning, such as Bayesian learning, boosting methods and Long Short Term Memory models. All methods are applied to claims, mortality or time-series forecasting.Requiring only a basic knowledge of statistics, this book is written for masters students in the actuarial sciences and for actuaries wishing to update their skills in machine learning.This is the third 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.

Автор: Denuit, Michel Hainaut, Donatien Trufin, Julien
Название: Effective statistical learning methods for actuaries ii
ISBN: 3030575551 ISBN-13(EAN): 9783030575557
Издательство: Springer
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Описание: This book summarizes the state of the art in tree-based methods for insurance: regression trees, random forests and boosting methods.

Автор: Michel Denuit; Donatien Hainaut; Julien Trufin
Название: Effective Statistical Learning Methods for Actuaries I
ISBN: 303025819X ISBN-13(EAN): 9783030258191
Издательство: Springer
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Описание: 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). Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS).

Автор: Wilders, Richard James (north Central College, Naperville, Usa)
Название: Financial mathematics for actuarial science
ISBN: 0367253089 ISBN-13(EAN): 9780367253080
Издательство: Taylor&Francis
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Описание: Financial Mathematics for Actuarial Science: The Theory of Interest is concerned with the measurement of interest and the various ways interest affects time value of money (TVM).