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Devoted to the problem of fitting parametric probability distributions to data, this treatment uniquely unifies loss modeling in one book. Data sets used are related to the insurance industry, but can be applied to other distributions. Emphasis is on the distribution of single losses related to claims made against various types of insurance policies. Includes five sets of insurance data as examples.
An update of one of the most trusted books on constructing and analyzing actuarial models Written by three renowned authorities in the actuarial field, Loss Models, Third Edition upholds the reputation for excellence that has made this book required reading for the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) qualification examinations. This update serves as a complete presentation of statistical methods for measuring risk and building models to measure loss in real-world events. This book maintains an approach to modeling and forecasting that utilizes tools related to risk theory, loss distributions, and survival models. Random variables, basic distributional quantities, the recursive method, and techniques for classifying and creating distributions are also discussed. Both parametric and non-parametric estimation methods are thoroughly covered along with advice for choosing an appropriate model. Features of the Third Edition include: Extended discussion of risk management and risk measures, including Tail-Value-at-Risk (TVaR) New sections on extreme value distributions and their estimation Inclusion of homogeneous, nonhomogeneous, and mixed Poisson processes Expanded coverage of copula models and their estimation Additional treatment of methods for constructing confidence regions when there is more than one parameter The book continues to distinguish itself by providing over 400 exercises that have appeared on previous SOA and CAS examinations. Intriguing examples from the fields of insurance and business are discussed throughout, and all data sets are available on the book's FTP site, along with programs that assist with conducting loss model analysis. Loss Models, Third Edition is an essential resource for students and aspiring actuaries who are preparing to take the SOA and CAS preliminary examinations. It is also a must-have reference for professional actuaries, graduate students in the actuarial field, and anyone who works with loss and risk models in their everyday work. To explore our additional offerings in actuarial exam preparation visit www.wiley.com/go/actuarialexamprep.
Statistical Tools in Finance and Insurance presents ready-to-use solutions, theoretical developments and method construction for many practical problems in quantitative finance and insurance. Written by practitioners and leading academics in the field, this book offers a unique combination of topics from which every market analyst and risk manager will benefit. Covering topics such as heavy tailed distributions, implied trinomial trees, support vector machines, valuation of mortgage-backed securities, pricing of CAT bonds, simulation of risk processes and ruin probability approximation, the book does not only offer practitioners insight into new methods for their applications, but it also gives theoreticians insight into the applicability of the stochastic technology. Additionally, the book provides the tools, instruments and (online) algorithms for recent techniques in quantitative finance and modern treatments in insurance calculations. Written in an accessible and engaging style, this self-instructional book makes a good use of extensive examples and full explanations. Thenbsp;design of the text links theory and computational tools in an innovative way. All Quantlets for the calculation of examples given in the text are supported by the academic edition of XploRe and may be executed via XploRe Quantlet Server (XQS). The downloadable electronic edition of the book enables one to run, modify, and enhance all Quantlets on the spot.
This class-tested undergraduate textbook covers the entire syllabus for Exam C of the Society of Actuaries (SOA).
This book constitutes the proceedings of the 17th International Conference on Quantitative Evaluation Systems, QEST 2020, held in Vienna, Austria, in August/September 2020. The 12 full papers presented together with 7 short papers were carefully reviewed and selected from 42 submissions. The papers cover topics such as classic measures involving performance and reliability, quantification of properties that are classically qualitative, such as safety, correctness, and security as well as analytic studies, diversity in the model formalisms and methodologies employed, and development of new formalisms and methodologies.
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.
Understanding Credit Derivatives and Related Instruments, Second Edition is an intuitive, rigorous overview that links the practices of valuing and trading credit derivatives with academic theory. Rather than presenting highly technical explorations, the book offers summaries of major subjects and the principal perspectives associated with them. The book's centerpiece is pricing and valuation issues, especially valuation tools and their uses in credit models. Five new chapters cover practices that have become commonplace as a result of the 2008 financial crisis, including standardized premiums and upfront payments. Analyses of regulatory responses to the crisis for the credit derivatives market (Basel III, Dodd-Frank, etc.) include all the necessary statistical and mathematical background for readers to easily follow the pricing topics. Every reader familiar with mid-level mathematics who wants to understand the functioning of the derivatives markets (in both practical and academic contexts) can fully satisfy his or her interests with the comprehensive assessments in this book. - Explores the role that credit derivatives played during the economic crisis, both as hedging instruments and as vehicles that potentially magnified losses for some investors - Comprehensive overview of single-name and multi-name credit derivatives in terms of market specifications, pricing techniques, and regulatory treatment - Updated edition uses current market statistics (market size, market participants, and uses of credit derivatives), covers the application of CDS technology to other asset classes (CMBX, ABX, etc.), and expands the treatment of individual instruments to cover index products, and more
A valuable reference for understanding operational risk Operational Risk with Excel and VBA is a practical guide that only discusses statistical methods that have been shown to work in an operational risk management context. It brings together a wide variety of statistical methods and models that have proven their worth, and contains a concise treatment of the topic. This book provides readers with clear explanations, relevant information, and comprehensive examples of statistical methods for operational risk management in the real world. Nigel Da Costa Lewis (Stamford, CT) is president and CEO of StatMetrics, a quantitative research boutique. He received his PhD from Cambridge University.
Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk.*Risk model validation is a requirement of Basel I and II *The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk
The remarkable growth of financial markets over the past decades has been accompanied by an equally remarkable explosion in financial engineering, the interdisciplinary field focusing on applications of mathematical and statistical modeling and computational technology to problems in the financial services industry. The goals of financial engineering research are to develop empirically realistic stochastic models describing dynamics of financial risk variables, such as asset prices, foreign exchange rates, and interest rates, and to develop analytical, computational and statistical methods and tools to implement the models and employ them to design and evaluate financial products and processes to manage risk and to meet financial goals. This handbook describes the latest developments in this rapidly evolving field in the areas of modeling and pricing financial derivatives, building models of interest rates and credit risk, pricing and hedging in incomplete markets, risk management, and portfolio optimization. Leading researchers in each of these areas provide their perspective on the state of the art in terms of analysis, computation, and practical relevance. The authors describe essential results to date, fundamental methods and tools, as well as new views of the existing literature, opportunities, and challenges for future research.