Judgment Under Uncertainty

Thirty-five chapters describe various judgmental heuristics and the biases they produce, not only in laboratory experiments, but in important social, medical, and political situations as well. Most review multiple studies or entire subareas rather than describing single experimental studies.

This book, first published in 2002, compiles psychologists' best attempts to answer important questions about intuitive judgment.

Amos Tversky and Daniel Kahneman’s 1974 paper ‘Judgement Under Uncertainty: Heuristics and Biases’ is a landmark in the history of psychology. Though a mere seven pages long, it has helped reshape the study of human rationality, and had a particular impact on economics – where Tversky and Kahneman’s work helped shape the entirely new sub discipline of ‘behavioral economics.’ The paper investigates human decision-making, specifically what human brains tend to do when we are forced to deal with uncertainty or complexity. Based on experiments carried out with volunteers, Tversky and Kahneman discovered that humans make predictable errors of judgement when forced to deal with ambiguous evidence or make challenging decisions. These errors stem from ‘heuristics’ and ‘biases’ – mental shortcuts and assumptions that allow us to make swift, automatic decisions, often usefully and correctly, but occasionally to our detriment. The paper’s huge influence is due in no small part to its masterful use of high-level interpretative and analytical skills – expressed in Tversky and Kahneman’s concise and clear definitions of the basic heuristics and biases they discovered. Still providing the foundations of new work in the field 40 years later, the two psychologists’ definitions are a model of how good interpretation underpins incisive critical thinking.

Human decision making involves problems which are being studied with increasing interest and sophistication. They range from controversial political decisions via individual consumer decisions to such simple tasks as signal discriminations. Although it would seem that decisions have to do with choices among available actions of any kind, there is general agreement that decision making research should pertain to choice prob lems which cannot be solved without a predecisional stage of finding choice alternatives, weighing evidence, and judging values. The ultimate objective of scientific research on decision making is two-fold: (a) to develop a theoretically sound technology for the optimal solution of decision problems, and (b) to formulate a descriptive theory of human decision making. The latter may, in tum, protect decision makers from being caught in the traps of their own limitations and biases. Recently, in decision making research the strong emphasis on well defined laboratory tasks is decreasing in favour of more realistic studies in various practical settings. This may well have been caused by a growing awareness of the fact that decision-behaviour is strongly determined by situational factors, which makes it necessary to look into processes of interaction between the decision maker and the relevant task environ ment. Almost inevitably there is a parallel shift of interest towards problems of utility measurement and the evaluation of consequences.

This handbook is an essential, comprehensive resource for students and academics interested in topics in cognitive psychology, including perceptual issues, attention, memory, knowledge representation, language, emotional influences, judgment, problem solving, and the study of individual differences in cognition.

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 2nd edition published in 2006).

This book presents the definitive exposition of 'prospect theory', a compelling alternative to the classical utility theory of choice. Building on the 1982 volume, Judgement Under Uncertainty, this book brings together seminal papers on prospect theory from economists, decision theorists, and psychologists, including the work of the late Amos Tversky, whose contributions are collected here for the first time. While remaining within a rational choice framework, prospect theory delivers more accurate, empirically verified predictions in key test cases, as well as helping to explain many complex, real-world puzzles. In this volume, it is brought to bear on phenomena as diverse as the principles of legal compensation, the equity premium puzzle in financial markets, and the number of hours that New York cab drivers choose to drive on rainy days. Theoretically elegant and empirically robust, this volume shows how prospect theory has matured into a new science of decision making.