Probability and Statistics for Actuaries, Natalia A. Humphreys, Yuly Koshevnik

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: Wai-Sum Chan, Yiu-Kuen Tse
Название: Financial Mathematics for Actuaries: 3rd Edition
ISBN: 9811243271 ISBN-13(EAN): 9789811243271
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 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: 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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Цена: 6986.00 р.
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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 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: Frees
Название: Predictive Modeling Applications in Actuarial Science
ISBN: 1107029880 ISBN-13(EAN): 9781107029880
Издательство: Cambridge Academ
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Описание: Predictive modeling involves the use of data to forecast future events. Building on the foundations developed in the first volume, Volume 2 examines applications of predictive modeling, focusing on property and casualty insurance, exposing readers to a variety of techniques in real-life contexts that demonstrate the value of predictive modeling.

Автор: Feng
Название: An Introduction To Computational Ri
ISBN: 1498742165 ISBN-13(EAN): 9781498742160
Издательство: Taylor&Francis
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Описание: The quantitative modeling of complex systems of interacting risks is a fairly recent development in the financial and insurance industries. Over the past decades, there has been tremendous innovation and development in the actuarial field. In addition to undertaking mortality and longevity risks in traditional life and annuity products, insurers face unprecedented financial risks since the introduction of equity-linking insurance in 1960s. As the industry moves into the new territory of managing many intertwined financial and insurance risks, non-traditional problems and challenges arise, presenting great opportunities for technology development. Today's computational power and technology make it possible for the life insurance industry to develop highly sophisticated models, which were impossible just a decade ago. Nonetheless, as more industrial practices and regulations move towards dependence on stochastic models, the demand for computational power continues to grow. While the industry continues to rely heavily on hardware innovations, trying to make brute force methods faster and more palatable, we are approaching a crossroads about how to proceed. An Introduction to Computational Risk Management of Equity-Linked Insurance provides a resource for students and entry-level professionals to understand the fundamentals of industrial modeling practice, but also to give a glimpse of software methodologies for modeling and computational efficiency. Features Provides a comprehensive and self-contained introduction to quantitative risk management of equity-linked insurance with exercises and programming samples Includes a collection of mathematical formulations of risk management problems presenting opportunities and challenges to applied mathematicians Summarizes state-of-arts computational techniques for risk management professionals Bridges the gap between the latest developments in finance and actuarial literature and the practice of risk management for investment-combined life insurance Gives a comprehensive review of both Monte Carlo simulation methods and non-simulation numerical methods Runhuan Feng is an Associate Professor of Mathematics and the Director of Actuarial Science at the University of Illinois at Urbana-Champaign. He is a Fellow of the Society of Actuaries and a Chartered Enterprise Risk Analyst. He is a Helen Corley Petit Professorial Scholar and the State Farm Companies Foundation Scholar in Actuarial Science. Runhuan received a Ph.D. degree in Actuarial Science from the University of Waterloo, Canada. Prior to joining Illinois, he held a tenure-track position at the University of Wisconsin-Milwaukee, where he was named a Research Fellow. Runhuan received numerous grants and research contracts from the Actuarial Foundation and the Society of Actuaries in the past. He has published a series of papers on top-tier actuarial and applied probability journals on stochastic analytic approaches in risk theory and quantitative risk management of equity-linked insurance. Over the recent years, he has dedicated his efforts to developing computational methods for managing market innovations in areas of investment combined insurance and retirement planning.

Автор: Frees
Название: Predictive Modeling Applications in Actuarial Science
ISBN: 1107029872 ISBN-13(EAN): 9781107029873
Издательство: Cambridge Academ
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Описание: This book is for actuaries and financial analysts developing their expertise in statistics and who wish to become familiar with concrete examples of predictive modeling.

Автор: Adam Prugel-Bennett
Название: The Probability Companion for Engineering and Computer Science
ISBN: 1108480535 ISBN-13(EAN): 9781108480536
Издательство: Cambridge Academ
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Цена: 18216.00 р.
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Описание: This guide helps undergraduate and graduate students convert pure mathematics into understanding and facility with a host of probabilistic tools. From the basic rules of probability it expands to the most sophisticated modern techniques, equipping those starting their careers and providing a handy reference for professionals and researchers.

Автор: B?lviken
Название: Computation and Modelling in Insurance and Finance
ISBN: 0521830486 ISBN-13(EAN): 9780521830485
Издательство: Cambridge Academ
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Цена: 18691.00 р.
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Описание: This practical introduction outlines methods for analysing actuarial and financial risk at a fairly elementary mathematical level suitable for graduate students, actuaries and other analysts in the industry who could use simulation as a problem solver. Numerous exercises with R-code illustrate the text.

Автор: Joshi
Название: Introduction to Mathematical Portfolio Theory
ISBN: 1107042313 ISBN-13(EAN): 9781107042315
Издательство: Cambridge Academ
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Описание: A concise yet comprehensive guide to the mathematics of portfolio theory from a modelling perspective, with discussion of the assumptions, limitations and implementations of the models as well as the theory underlying them. Aimed at advanced undergraduates, this book can be used for self-study or as a course text.

Автор: Barrieu Pauline
Название: Risk And Stochastics: Ragnar Norberg
ISBN: 1786341948 ISBN-13(EAN): 9781786341945
Издательство: World Scientific Publishing
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Цена: 16632.00 р.
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Описание: with an autobiography from Ragnar NorbergThe Risk and Stochastics Conference, held at the Royal Statistical Society in April 2015, brought together academics from the worlds of actuarial science, stochastic calculus, finance and statistics to celebrate the achievements of Professor Ragnar Norberg as he turned 70. After the conference, Ragnar Norberg suddenly fell very ill and passed away; this book honours his life and work.This collection of articles is written by speakers of the conference, themselves respected academics who have influenced and been influenced by the life and work of Professor Norberg. His professional and academic achievements are celebrated here, most significantly the instrumental work he put into setting up the world-renowned Risk and Stochastics Enterprise at the London School of Economics (LSE). Subjects covered include discussion of risk measurements, ruin constraint, supporting stable pensions, filtration in discrete time, Riesz means and Beurling moving averages and orthonormal polynomial expansions. Also featured are notes from contributors giving account of their personal relations with Professor Norberg, as well as an autobiographical chapter from the man himself.Aimed at graduate level students and researchers interested in the life and work of Ragnar Norberg, this book provides a unique opportunity to reflect on and understand key findings and ground-breaking research in modern actuarial and financial mathematics and their interface, while giving intimate insights into the life of a leading academic mind.