It is a challenging task to read the balance sheet of an insurance company. This derives from the fact that different positions are often measured by different yardsticks. Assets, for example, are mostly valued at market prices whereas liabilities are often measured by established actuarial methods. However, there is a general agreement that the balance sheet of an insurance company should be measured in a consistent way. Market-Consistent Actuarial Valuation presents powerful methods to measure liabilities and assets in a consistent way. The mathematical framework that leads to market-consistent values for insurance liabilities is explained in detail by the authors. Topics covered are stochastic discounting with deflators, valuation portfolio in life and non-life insurance, probability distortions, asset and liability management, financial risks, insurance technical risks, and solvency.
Arbitrage Theory provides the foundation for the pricing of financial derivatives and has become indispensable in both financial theory and financial practice. This textbook offers a rigorous and comprehensive introduction to the mathematics of arbitrage pricing in a discrete-time, finite-state economy in which a finite number of securities are traded. In a first step, various versions of the Fundamental Theorem of Asset Pricing, i.e., characterizations of when a market does not admit arbitrage opportunities, are proved. The book then focuses on incomplete markets where the main concern is to obtain a precise description of the set of “market-consistent” prices for nontraded financial contracts, i.e. the set of prices at which such contracts could be transacted between rational agents. Both European-type and American-type contracts are considered. A distinguishing feature of this book is its emphasis on market-consistent prices and a systematic description of pricing rules, also at intermediate dates. The benefits of this approach are most evident in the treatment of American options, which is novel in terms of both the presentation and the scope, while also presenting new results. The focus on discrete-time, finite-state models makes it possible to cover all relevant topics while requiring only a moderate mathematical background on the part of the reader. The book will appeal to mathematical finance and financial economics students seeking an elementary but rigorous introduction to the subject; mathematics and physics students looking for an opportunity to get acquainted with a modern applied topic; and mathematicians, physicists and quantitatively inclined economists working or planning to work in the financial industry.
Over the last decade, stress testing has become a central aspect of the Fund’s bilateral and multilateral surveillance work. Recently, more emphasis has also been placed on the role of insurance for financial stability analysis. This paper reviews the current state of system-wide solvency stress tests for insurance based on a comparative review of national practices and the experiences from Fund’s FSAP program with the aim of providing practical guidelines for the coherent and consistent implementation of such exercises. The paper also offers recommendations on improving the current insurance stress testing approaches and presentation of results.
Quantitative models are omnipresent –but often controversially discussed– in todays risk management practice. New regulations, innovative financial products, and advances in valuation techniques provide a continuous flow of challenging problems for financial engineers and risk managers alike. Designing a sound stochastic model requires finding a careful balance between parsimonious model assumptions, mathematical viability, and interpretability of the output. Moreover, data requirements and the end-user training are to be considered as well. The KPMG Center of Excellence in Risk Management conference Risk Management Reloaded and this proceedings volume contribute to bridging the gap between academia –providing methodological advances– and practice –having a firm understanding of the economic conditions in which a given model is used. Discussed fields of application range from asset management, credit risk, and energy to risk management issues in insurance. Methodologically, dependence modeling, multiple-curve interest rate-models, and model risk are addressed. Finally, regulatory developments and possible limits of mathematical modeling are discussed.
Presents powerful methods to measure liabilities and assets in the same way. The mathematical framework that leads to market-consistent values for insurance liabilities is explained in detail by the authors.
This is the third edition of this well-received textbook, presenting powerful methods for measuring insurance liabilities and assets in a consistent way, with detailed mathematical frameworks that lead to market-consistent values for liabilities. Topics covered are stochastic discounting with deflators, valuation portfolio in life and non-life insurance, probability distortions, asset and liability management, financial risks, insurance technical risks, and solvency. Including updates on recent developments and regulatory changes under Solvency II, this new edition of Market-Consistent Actuarial Valuation also elaborates on different risk measures, providing a revised definition of solvency based on industry practice, and presents an adapted valuation framework which takes a dynamic view of non-life insurance reserving risk.
This book explores theoretical and practical implications of reflecting the fair value of liabilities for insurance companies. In addition, the contributions discuss the disclosure of these values to the financial and regulatory communities and auditing firms which are actually calculating this illusive but important variable. It combines contributions by distinguished practitioners from the insurance, accounting and finance fields, with those of prominent academics. One of the central themes of the collection is that adequate disclosure of the true economic value of insurance company liabilities is both possible and desirable. Wherever possible, the insurance valuation process is wedded with modern financial theory. For example, the use of option pricing theory is applied to insurance companies, where the true value of the firm's liabilities is a critical variable. Methods such as cash flow, earned profit and indirect discount are explored.
The aim of the book is to provide an overview of risk management in life insurance companies. The focus is twofold: (1) to provide a broad view of the different topics needed for risk management and (2) to provide the necessary tools and techniques to concretely apply them in practice. Much emphasis has been put into the presentation of the book so that it presents the theory in a simple but sound manner. The first chapters deal with valuation concepts which are defined and analysed, the emphasis is on understanding the risks in corresponding assets and liabilities such as bonds, shares and also insurance liabilities. In the following chapters risk appetite and key insurance processes and their risks are presented and analysed. This more general treatment is followed by chapters describing asset risks, insurance risks and operational risks - the application of models and reporting of the corresponding risks is central. Next, the risks of insurance companies and of special insurance products are looked at. The aim is to show the intrinsic risks in some particular products and the way they can be analysed. The book finishes with emerging risks and risk management from a regulatory point of view, the standard model of Solvency II and the Swiss Solvency Test are analysed and explained. The book has several mathematical appendices which deal with the basic mathematical tools, e.g. probability theory, stochastic processes, Markov chains and a stochastic life insurance model based on Markov chains. Moreover, the appendices look at the mathematical formulation of abstract valuation concepts such as replicating portfolios, state space deflators, arbitrage free pricing and the valuation of unit linked products with guarantees. The various concepts in the book are supported by tables and figures.
Over the past two decades, the United States has successfully deregulated prices and restrictions on most previously-regulated industries, including airlines, trucking, railroads, telecommunications, and banking. Only a few industries remain regulated, the largest being the property-liability insurance business. In light of recent sweeping financial modernization legislation in other sectors of the insurance industry, this timely volume examines the basis for continued regulation of rates and forms of the U.S. property-liability insurance market. The book focuses on private passenger automobile insurance—the most important personal line of property-liability coverage, with annual premiums of about $120 billion. The authors analyze five state case studies: California, Massachusetts, and New Jersey—three of the most heavily regulated states—as well as Illinois, which has been deregulated for about 30 years, and South Carolina, which began to deregulate in 1997. The study also includes an econometric analysis based on all fifty states over a 25-year period that gauges the impact of regulation on insurance price levels, price volatility, and the proportion of automobiles insured in residual markets. The authors conclude that regulation does not significantly reduce long-run prices for consumers, and generally limits availability of coverage, reduces the quality and variety of services available in the market, inhibits productivity growth, and increases price volatility. Contributors include Dwight Jaffee (University of California, Berkeley), Thomas Russell (Santa Clara University ), Laureen Regan (Temple University), Sharon Tennyson (Cornell University), Mary Weiss (Temple University), John Worrall (Rutgers University), Stephen D'Arcy (University of Illinois, Urbana-Champaign), Martin Grace (Georgia State University), Robert Klein (Georgia State University), Richard Phillips (Georgia State University), Georges Dionne (University of Montreal), and Richard Butler (Brigham Young University).
Achieving market consistency can be challenging, even for the most established finance practitioners. In Market Consistency: Model Calibration in Imperfect Markets, leading expert Malcolm Kemp shows readers how they can best incorporate market consistency across all disciplines. Building on the author's experience as a practitioner, writer and speaker on the topic, the book explores how risk management and related disciplines might develop as fair valuation principles become more entrenched in finance and regulatory practice. This is the only text that clearly illustrates how to calibrate risk, pricing and portfolio construction models to a market consistent level, carefully explaining in a logical sequence when and how market consistency should be used, what it means for different financial disciplines and how it can be achieved for both liquid and illiquid positions. It explains why market consistency is intrinsically difficult to achieve with certainty in some types of activities, including computation of hedging parameters, and provides solutions to even the most complex problems. The book also shows how to best mark-to-market illiquid assets and liabilities and to incorporate these valuations into solvency and other types of financial analysis; it indicates how to define and identify risk-free interest rates, even when the creditworthiness of governments is no longer undoubted; and it explores when practitioners should focus most on market consistency and when their clients or employers might have less desire for such an emphasis. Finally, the book analyses the intrinsic role of regulation and risk management within different parts of the financial services industry, identifying how and why market consistency is key to these topics, and highlights why ideal regulatory solvency approaches for long term investors like insurers and pension funds may not be the same as for other financial market participants such as banks and asset managers.
