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Author : Erik Bølviken
Publisher : Unknown
Page : 685 pages
File Size : 51,9 Mb
Release : 2014
Category : Insurance
ISBN : 1107779170
Author : Erik Bølviken
Publisher : Cambridge University Press
Page : 713 pages
File Size : 40,9 Mb
Release : 2014-04-10
Category : Business & Economics
ISBN : 9780521830485
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.
Author : Runhuan Feng
Publisher : CRC Press
Page : 382 pages
File Size : 40,7 Mb
Release : 2018-06-13
Category : Business & Economics
ISBN : 9781498742184
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.
Author : Arthur Charpentier
Publisher : CRC Press
Page : 652 pages
File Size : 42,9 Mb
Release : 2014-08-26
Category : Business & Economics
ISBN : 9781466592599
A Hands-On Approach to Understanding and Using Actuarial Models Computational 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/C++ embedded codes. After an introduction to the R language, the book is divided into four parts. The first one addresses methodology and statistical modeling issues. The second part discusses the computational facets of life insurance, including life contingencies calculations and prospective life tables. Focusing on finance from an actuarial perspective, the next part presents techniques for modeling stock prices, nonlinear time series, yield curves, interest rates, and portfolio optimization. The last part explains how to use R to deal with computational issues of nonlife insurance. Taking a do-it-yourself approach to understanding algorithms, this book demystifies the computational aspects of actuarial science. It shows that even complex computations can usually be done without too much trouble. Datasets used in the text are available in an R package (CASdatasets).
Author : Jean-Paul Laurent,Ragnar Norberg,Frédéric Planchet
Publisher : Springer
Page : 263 pages
File Size : 54,7 Mb
Release : 2016-05-02
Category : Mathematics
ISBN : 9783319297767
Focusing on life insurance and pensions, this book addresses various aspects of modelling in modern insurance: insurance liabilities; asset-liability management; securitization, hedging, and investment strategies. With contributions from internationally renowned academics in actuarial science, finance, and management science and key people in major life insurance and reinsurance companies, there is expert coverage of a wide range of topics, for example: models in life insurance and their roles in decision making; an account of the contemporary history of insurance and life insurance mathematics; choice, calibration, and evaluation of models; documentation and quality checks of data; new insurance regulations and accounting rules; cash flow projection models; economic scenario generators; model uncertainty and model risk; model-based decision-making at line management level; models and behaviour of stakeholders. With author profiles ranging from highly specialized model builders to decision makers at chief executive level, this book should prove a useful resource to students and academics of actuarial science as well as practitioners.
Author : Ralf Korn,Elke Korn,Gerald Kroisandt
Publisher : CRC Press
Page : 485 pages
File Size : 50,9 Mb
Release : 2010-02-26
Category : Business & Economics
ISBN : 9781420076196
Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Rom
Author : Erricos Kontoghiorghes,Berc Rustem,Peter Winker
Publisher : Springer Science & Business Media
Page : 425 pages
File Size : 41,9 Mb
Release : 2008-02-26
Category : Business & Economics
ISBN : 9783540779582
Computational models and methods are central to the analysis of economic and financial decisions. Simulation and optimisation are widely used as tools of analysis, modelling and testing. The focus of this book is the development of computational methods and analytical models in financial engineering that rely on computation. The book contains eighteen chapters written by leading researchers in the area on portfolio optimization and option pricing; estimation and classification; banking; risk and macroeconomic modelling. It explores and brings together current research tools and will be of interest to researchers, analysts and practitioners in policy and investment decisions in economics and finance.
Author : Paul Embrechts,Claudia Klüppelberg,Thomas Mikosch
Publisher : Springer Science & Business Media
Page : 648 pages
File Size : 40,7 Mb
Release : 2013-03-14
Category : Business & Economics
ISBN : 9783642334832
"A reader's first impression on leafing through this book is of the large number of graphs and diagrams, used to illustrate shapes of distributions...and to show real data examples in various ways. A closer reading reveals a nice mix of theory and applications, with the copious graphical illustrations alluded to. Such a mixture is of course dear to the heart of the applied probabilist/statistician, and should impress even the most ardent theorists." --MATHEMATICAL REVIEWS
Author : Hansjörg Albrecher
Publisher : Unknown
Page : 453 pages
File Size : 43,5 Mb
Release : 2009-12-15
Category : Finance
ISBN : 3111731855
This book is a collection of state-of-the-art surveys on various topics in mathematical finance, with an emphasis on recent modelling and computational approaches. The volume is related to a Special Semester on Stochastics with Emphasis on Finance that took place from September to December 2008 at the Johann Radon Institute for Computational and Applied Mathematics of the Austrian Academy of Sciences in Linz, Austria."
Author : Santiago Moreno-Bromberg,Jean-Charles Rochet
Publisher : Princeton University Press
Page : 223 pages
File Size : 49,7 Mb
Release : 2018-01-08
Category : Business & Economics
ISBN : 9780691176529
Continuous-Time Models in Corporate Finance synthesizes four decades of research to show how stochastic calculus can be used in corporate finance. Combining mathematical rigor with economic intuition, Santiago Moreno-Bromberg and Jean-Charles Rochet analyze corporate decisions such as dividend distribution, the issuance of securities, and capital structure and default. They pay particular attention to financial intermediaries, including banks and insurance companies. The authors begin by recalling the ways that option-pricing techniques can be employed for the pricing of corporate debt and equity. They then present the dynamic model of the trade-off between taxes and bankruptcy costs and derive implications for optimal capital structure. The core chapter introduces the workhorse liquidity-management model—where liquidity and risk management decisions are made in order to minimize the costs of external finance. This model is used to study corporate finance decisions and specific features of banks and insurance companies. The book concludes by presenting the dynamic agency model, where financial frictions stem from the lack of interest alignment between a firm's manager and its financiers. The appendix contains an overview of the main mathematical tools used throughout the book. Requiring some familiarity with stochastic calculus methods, Continuous-Time Models in Corporate Finance will be useful for students, researchers, and professionals who want to develop dynamic models of firms' financial decisions.
Author : X. Sheldon Lin,Society of Actuaries
Publisher : John Wiley & Sons
Page : 224 pages
File Size : 48,6 Mb
Release : 2006-04-21
Category : Mathematics
ISBN : 9780471793205
Incorporates the many tools needed for modeling and pricing infinance and insurance Introductory Stochastic Analysis for Finance and Insuranceintroduces readers to the topics needed to master and use basicstochastic analysis techniques for mathematical finance. The authorpresents the theories of stochastic processes and stochasticcalculus and provides the necessary tools for modeling and pricingin finance and insurance. Practical in focus, the book's emphasisis on application, intuition, and computation, rather thantheory. Consequently, the text is of interest to graduate students,researchers, and practitioners interested in these areas. While thetext is self-contained, an introductory course in probabilitytheory is beneficial to prospective readers. This book evolved from the author's experience as an instructor andhas been thoroughly classroom-tested. Following an introduction,the author sets forth the fundamental information and tools neededby researchers and practitioners working in the financial andinsurance 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 andApplications in Insurance, are devoted to more advanced topics.Readers learn the Feynman-Kac formula, the Girsanov's theorem, andcomplex barrier hitting times distributions. Finally, readersdiscover how stochastic analysis and principles are applied inpractice through two insurance examples: valuation of equity-linkedannuities under a stochastic interest rate environment andcalculation of reserves for universal life insurance. Throughout the text, figures and tables are used to help simplifycomplex theory and pro-cesses. An extensive bibliography opens upadditional avenues of research to specialized topics. Ideal for upper-level undergraduate and graduate students, thistext is recommended for one-semester courses in stochastic financeand calculus. It is also recommended as a study guide forprofessionals taking Causality Actuarial Society (CAS) and Societyof Actuaries (SOA) actuarial examinations.
Author : Vsevolod Malinovskii
Publisher : World Scientific
Page : 355 pages
File Size : 45,5 Mb
Release : 2021-08-13
Category : Business & Economics
ISBN : 9789811204678
Insurance Planning Models: Price Competition and Regulation of Financial Stability is an exciting new book that takes readers inside the secrets of internal organization of the modern general insurance business. Many people know that it is subject to intensive state regulation, whereby the purpose is to maintain long-term efficiency, honesty, security and stability in the interest and for the protection of policyholders. However, except for knowing that the insurance system is regulated by intensive calculations, that the insurance companies have different positions on the market, that they pursue different goals and even compete with each other, and that one of the tools of this competition is the policy price, not so many people know how to achieve these deserving goals.In developing quantitative recommendations and directives to competing insurers, regulators rely on certain models. In the 1900s, such models were proposed. They were useful for an insight into the probabilistic nature of the insurance process, but not for direct application to practically meaningful problems of insurance regulation. This book is your guide to the rigorously constructed long-term dynamic models with the aim to improve regulatory methods and develop quantitative recommendations using both analytical calculations and computer simulation. It is addressed to a wide range of readers, including interested policyholders, economists whose interest lies in insurance management and regulation, and mathematicians wishing to expand the scope of application for their knowledge.This book is devoted to certain issues that are either not sufficiently presented, or even absent in the literature. It is an attempt to penetrate from the standpoint of mathematical modeling into the goals which face insurance regulators and contending company managers for preventing insolvencies, or even crises pertinent to badly regulated complex reflexive systems.It offers rigorous probabilistic models of long-term insurance business based on the laws of mass phenomena. They mitigate deficiencies of oversimplified risk models. The book presents advances in probabilistic techniques designed to seek quantitative, rather than qualitative, directives and recommendations regarding safe control aiming to achieve different business goals.
Author : A F Shapiro,L C Jain
Publisher : World Scientific
Page : 688 pages
File Size : 41,9 Mb
Release : 2003-12-23
Category : Business & Economics
ISBN : 9789814483490
This book presents recent advances in the theory and implementation of intelligent and other computational techniques in the insurance industry. The paradigms covered encompass artificial neural networks and fuzzy systems, including clustering versions, optimization and resampling methods, algebraic and Bayesian models, decision trees and regression splines. Thus, the focus is not just on intelligent techniques, although these constitute a major component; the book also deals with other current computational paradigms that are likely to impact on the industry. The application areas include asset allocation, asset and liability management, cash-flow analysis, claim costs, classification, fraud detection, insolvency, investments, loss distributions, marketing, pricing and premiums, rate-making, retention, survival analysis, and underwriting. Contents:Insurance Applications of Neural Networks, Fuzzy Logic, and Genetic AlgorithmsPractical Applications of Neural Networks in Property and Casualty InsuranceAn Integrated Data Mining Approach to Premium Pricing for the Automobile Insurance IndustryPopulation Risk Management: Reducing Costs and Managing Risk in Health InsuranceUsing Neural Networks to Predict in the MarketplaceMerging Soft Computing Technologies in Insurance-Related ApplicationsRobustness in Bayesian Models for Bonus–Malus SystemsUsing Data Mining for Modeling Insurance Risk and Comparison of Data Mining and Linear Modeling ApproachesSystem Intelligence and Active Stock TradingThe Algebra of Cash Flows: Theory and Applicationand other papers Readership: Graduate students, academics, researchers and practitioners involved with actuarial science, insurance, statistics and management science. Keywords:Insurance;Actuarial Science;Neural Networks;Fuzzy Systems;Computational Intelligence;Computational Techniques;Life and Health Insurance;Property and Casualty Insurance
Author : Ricardas Zitikis,Jiandong Ren,Kristina Sendova
Publisher : MDPI
Page : 210 pages
File Size : 51,7 Mb
Release : 2020-04-02
Category : Business & Economics
ISBN : 9783039285167
Developing techniques for assessing various risks and calculating probabilities of ruin and survival are exciting topics for mathematically-inclined academics. For practicing actuaries and financial engineers, the resulting insights have provided enormous opportunities but also created serious challenges to overcome, thus facilitating closer cooperation between industries and academic institutions. In this book, several renown researchers with extensive interdisciplinary research experiences share their thoughts that, in one way or another, contribute to the betterment of practice and theory of decision making under uncertainty. Behavioral, cultural, mathematical, and statistical aspects of risk assessment and modelling have been explored, and have been often illustrated using real and simulated data. Topics range from financial and insurance risks to security-type risks, from one-dimensional to multi- and even infinite-dimensional risks. The articles in the book were written with a broad audience in mind and should provide enjoyable reading for those with university level degrees and/or those who have studied for accreditation by various actuarial and financial societies.
Author : J. David Cummins,Richard A. Derrig
Publisher : Springer Science & Business Media
Page : 408 pages
File Size : 45,6 Mb
Release : 1989-08-31
Category : Business & Economics
ISBN : 0792390180
The First International Conference on Insurance Solvency was held at the Wharton School, University of Pennsylvania from June 18th through June 20th, 1986. The conference was the inaugural event for Wharton's Center for Research on Risk and Insurance. In atten dance were thirty-nine representatives from Australia, Canada, France, Germany, Israel, the United Kingdom, and the United States. The papers presented at the Conference are published in two volumes, this book and a companion volume, Classical Insurance Solvency Theory, J. D. Cummins and R. A. Derrig, eds. (Norwell, MA: Kluwer Academic Publishers, 1988). The first volume presented two papers reflecting important advances in actuarial solvency theory. The current volume goes beyond the actuarial approach to encom pass papers applying the insights and techniques of financial economics. The papers fall into two groups. The first group con sists of papers that adopt an essentially actuarial or statistical ap proach to solvency modelling. These papers represent methodology advances over prior efforts at operational modelling of insurance companies. The emphasis is on cash flow analysis and many of the models incorporate investment income, inflation, taxation, and other economic variables. The papers in second group bring financial economics to bear on various aspects of solvency analysis. These papers discuss insurance applications of asset pricing models, capital structure theory, and the economic theory of agency.