Modern mortality modelling for actuaries and actuarial students, with example R code, to unlock the potential of individual data.

This book presents the latest theories and methods of reliability and quality, with emphasis on reliability and quality in design and modelling. Each chapter is written by active researchers and professionals with international reputations, providing material which bridges the gap between theory and practice to trigger new practices and research challenges. The book therefore provides a state-of-the-art survey of reliability and quality in design and practices.

Regional Model Life Tables and Stable Populations, Second Edition maintains the tradition of research on the analysis of fertility and mortality as related to population growth and composition. The tables presented are two principal forms: model life tables and model stable populations. The included models are models of mortality and age composition; "west" model life tables and stable populations; "north" model life tables and stable populations; "east" model life tables and stable populations; and "south" model life tables and stable populations. People involved in the study of population growth and composition will find the book useful.

This book describes a novel method for mortality modeling applying the shifting feature of the mortality curve. In Japan, the increase and pace of the extension in life expectancy have been quite remarkable. Therefore, existing mortality models often cannot capture the peculiarities of Japanese mortality, nor can the Lee–Carter model, which is now regarded internationally as a standard model. One of the important concepts to model recent Japanese mortality is a shifting feature. In this book, the linear difference model, which has many advantages for modeling and analyzing Japanese mortality, is introduced. The book shows applications of the model to mortality projection with a tangent vector field approach and decomposition of the change of modal age at death. The models introduced here are useful tools for modeling mortality with strong shifting features, as in Japan.

Actuarial Principles: Lifetables and Mortality Models explores the core of actuarial science: the study of mortality and other risks and applications. Including the CT4 and CT5 UK courses, but applicable to a global audience, this work lightly covers the mathematical and theoretical background of the subject to focus on real life practice. It offers a brief history of the field, why actuarial notation has become universal, and how theory can be applied to many situations. Uniquely covering both life contingency risks and survival models, the text provides numerous exercises (and their solutions), along with complete self-contained real-world assignments. Provides detailed coverage of life contingency risks and survival models Presents self-contained chapters with coverage of key topics from both practitioner and theoretical viewpoints Includes numerous real world exercises that are accompanied by enlightening solutions Covers useful background information on how and why the subject has evolved and developed

Information on future mortality trends is essential for population forecasts, public health policy, actuarial studies, and many other purposes. Realising the importance of such needs, this volume contains contributions to the theory and practice of forecasting mortality in the relatively favourable circumstances in developed countries of Western Europe. In this context techniques from mathematical statistics and econometrics can provide useful descriptions of past mortality. The naive forecast obtained by extrapolating a fitted model may give as good a forecast as any but forecasting by extrapolation requires careful justification since it assumes the prolongation of historical conditions. On the other hand, whilst it is generally accepted that scientific and other advances will continue to impact on mortality, perhaps dramatically so, it is impossible to quantify more than the outline of future consequences with a strong degree of confidence. The decision to modify an extrapolation of a model fitted to historical data (or conversely choosing not to modify it) in order to obtain a forecast is therefore strongly influenced by subjective and judgmental elements, with the quality of the latter dependent on demographic, epidemiological and indeed perhaps more general considerations. The thread running through the book reflects therefore the necessity of integrating demographic, epidemiological, and statistical factors to obtain an improvement in the prediction of mortality.

This open access book collects expert contributions on actuarial modelling and related topics, from machine learning to legal aspects, and reflects on possible insurance designs during an epidemic/pandemic. Starting by considering the impulse given by COVID-19 to the insurance industry and to actuarial research, the text covers compartment models, mortality changes during a pandemic, risk-sharing in the presence of low probability events, group testing, compositional data analysis for detecting data inconsistencies, behaviouristic aspects in fighting a pandemic, and insurers' legal problems, amongst others. Concluding with an essay by a practicing actuary on the applicability of the methods proposed, this interdisciplinary book is aimed at actuaries as well as readers with a background in mathematics, economics, statistics, finance, epidemiology, or sociology.

During the past twenty years, there has been a rapid growth in life expectancy and an increased attention on funding for old age. Attempts to forecast improving life expectancy have been boosted the development of stochastic mortality modeling, for example the Cairns-Blake-Dowd (CBD) 2006 model. For those stochastic models, the maximum likelihood estimation (MLE) is the most popular and widely used estimation method. This method relies on one important assumption which is that the number of deaths follows a Poisson distribution. However, several recent studies have found that the true underlying distribution of death data is overdispersed in nature (see Cairns et al. 2009 and Dowd et al. 2010). Semiparametric models have been applied to many areas in economics but have never been used to model mortality. In this paper we propose a local linear panel fitting methodology to the CBD model which would free the Poisson assumption on number of deaths. The parameters in the CBD model will be considered as smooth functions of time instead of being treated as a bivariate random walk with drift process in the current literature. Using the mortality data of several developed countries, we find that the proposed estimation methods provides comparable fitting results with the MLE method but without the need of additional assumptions on number of deaths. Further, the 5-year-ahead forecasting results show that our method significantly improves the accuracy of the forecast.

This work covers various important issues in life table construction and use. It. includes a non-technical overview, compares various methods of decomposing the difference in life expectancies, discusses the finding of suitable indicators and models, and deals with age, period, and cohort effects in mortality.

"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.