An understanding of risk and how to deal with it is an essential part of modern economics. Whether liability litigation for pharmaceutical firms or an individual's having insufficient wealth to retire, risk is something that can be recognized, quantified, analyzed, treated--and incorporated into our decision-making processes. This book represents a concise summary of basic multiperiod decision-making under risk. Its detailed coverage of a broad range of topics is ideally suited for use in advanced undergraduate and introductory graduate courses either as a self-contained text, or the introductory chapters combined with a selection of later chapters can represent core reading in courses on macroeconomics, insurance, portfolio choice, or asset pricing. The authors start with the fundamentals of risk measurement and risk aversion. They then apply these concepts to insurance decisions and portfolio choice in a one-period model. After examining these decisions in their one-period setting, they devote most of the book to a multiperiod context, which adds the long-term perspective most risk management analyses require. Each chapter concludes with a discussion of the relevant literature and a set of problems. The book presents a thoroughly accessible introduction to risk, bridging the gap between the traditionally separate economics and finance literatures.

This handbook in two parts covers key topics of the theory of financial decision making. Some of the papers discuss real applications or case studies as well. There are a number of new papers that have never been published before especially in Part II.Part I is concerned with Decision Making Under Uncertainty. This includes subsections on Arbitrage, Utility Theory, Risk Aversion and Static Portfolio Theory, and Stochastic Dominance. Part II is concerned with Dynamic Modeling that is the transition for static decision making to multiperiod decision making. The analysis starts with Risk Measures and then discusses Dynamic Portfolio Theory, Tactical Asset Allocation and Asset-Liability Management Using Utility and Goal Based Consumption-Investment Decision Models.A comprehensive set of problems both computational and review and mind expanding with many unsolved problems are in an accompanying problems book. The handbook plus the book of problems form a very strong set of materials for PhD and Masters courses both as the main or as supplementary text in finance theory, financial decision making and portfolio theory. For researchers, it is a valuable resource being an up to date treatment of topics in the classic books on these topics by Johnathan Ingersoll in 1988, and William Ziemba and Raymond Vickson in 1975 (updated 2 nd edition published in 2006).

Financial Dec Making under Uncertainty

"The authors start with the fundamentals of risk measurement and risk aversion. They then apply these concepts to insurance decisions and portfolio choice in a one-period model. After examining these decisions in their one-period setting, they devote most of the book to a multiperiod context, which adds the long-term perspective most risk management analyses require. Each chapter concludes with a discussion of the relevant literature and a set of problems."--Jacket.

An introduction to the use of probability models for analyzing risk and economic decisions, using spreadsheets to represent and simulate uncertainty. This textbook offers an introduction to the use of probability models for analyzing risks and economic decisions. It takes a learn-by-doing approach, teaching the student to use spreadsheets to represent and simulate uncertainty and to analyze the effect of such uncertainty on an economic decision. Students in applied business and economics can more easily grasp difficult analytical methods with Excel spreadsheets. The book covers the basic ideas of probability, how to simulate random variables, and how to compute conditional probabilities via Monte Carlo simulation. The first four chapters use a large collection of probability distributions to simulate a range of problems involving worker efficiency, market entry, oil exploration, repeated investment, and subjective belief elicitation. The book then covers correlation and multivariate normal random variables; conditional expectation; optimization of decision variables, with discussions of the strategic value of information, decision trees, game theory, and adverse selection; risk sharing and finance; dynamic models of growth; dynamic models of arrivals; and model risk. New material in this second edition includes two new chapters on additional dynamic models and model risk; new sections in every chapter; many new end-of-chapter exercises; and coverage of such topics as simulation model workflow, models of probabilistic electoral forecasting, and real options. The book comes equipped with Simtools, an open-source, free software used througout the book, which allows students to conduct Monte Carlo simulations seamlessly in Excel.

Today, the judge, the citizen, the politician, and the entrepreneur are concerned with the sustainability of our development.

Individuals and families make key decisions that impact many aspects of financial stability and determine the future of the economy. These decisions involve balancing current sacrifice against future benefits. People have to decide how much to invest in health care, exercise, their diet, and insurance. They must decide how much debt to take on, and how much to save. And they make choices about jobs that determine employment and unemployment levels. Forward-Looking Decision Making is about modeling this individual or family-based decision making using an optimizing dynamic programming model. Robert Hall first reviews ideas about dynamic programs and introduces new ideas about numerical solutions and the representation of solved models as Markov processes. He surveys recent research on the parameters of preferences--the intertemporal elasticity of substitution, the Frisch elasticity of labor supply, and the Frisch cross-elasticity. He then examines dynamic programming models applied to health spending, long-term care insurance, employment, entrepreneurial risk-taking, and consumer debt. Linking theory with data and applying them to real-world problems, Forward-Looking Decision Making uses dynamic optimization programming models to shed light on individual behaviors and their economic implications.

Presenting theoretical foundations and empirical research, this text introduces the reader to the core issues and analytical tools of insurance economics, examining in detail a host of key factors including supply and demand, regulation and social insurance.

This book reviews the latest research from psychology, neuroscience, and behavioral economics evaluating how people make financial choices in real-life circumstances. The volume is divided into three sections investigating financial decision making at the level of the brain, the level of an individual decision maker, and the level of the society, concluding with a discussion of the implications for further research. Among the topics discussed: Neural and hormonal bases of financial decision making Personality, cognitive abilities, emotions, and financial decisions Aging and financial decision making Coping methods for making financial choices under uncertainty Stock market crashes and market bubbles Psychological perspectives on borrowing, paying taxes, gambling, and charitable giving Psychological Perspectives on Financial Decision Making is a useful reference for researchers both in and outside of psychology, including decision-making experts, consumer psychologists, and behavioral economists.