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Accurate assessment of risk propensity is important because risky choices underlie a broad range of behavioral problems. The Balloon Analogue Risk Task (BART) is an assessment that measures propensity to engage in risky choice. While this is a useful assessment, the BART changes two variables that affect risky choice simultaneously, probability of an undesirable outcome and stake size, which cannot be separated within the context of the BART. The goal of this study was to evaluate the separate and combined effects of key factors that are likely to risky choice (Magnitude of payoff, probability of an undesirable outcome, and stake size) in the context of a new analog to risky choice: The Wheel of Choice Task. Adults between the ages of 18 and 25 (N = 23) were recruited to participate in this study. On each trial, participants chose between spinning the wheel or collecting their earnings. Spinning could result in a payoff or a loss of earnings, and as such constituted a risky choice. Risky choices increased as the probability of bankruptcy decreased, as the magnitude of reinforcement for the risky choice increased, and as stake size decreased. Effects of all three independent variables were systematic and robust. In addition to the main effects, interaction effects were observed between probability of a bankruptcy and magnitude, magnitude and stake size, and between all three variables, indicating complex but systematic interplay between these powerful determinants of risky choice. Future directions for this line of research include a further parametric analysis of stake size as well as the Wheel of Choice task's utility as a clinical or experimental tool.
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).
The appeal of expected utility theory as a basis for a descriptive model of risky decision making has diminished is a result of empirical evidence which suggests that individuals do not behave in a manner consistent with the prescriptive tenets of EUT. In this paper, we explore the influence of probability on risky choice. by proposing and estimating a parametric model of risky decision making. Our results suggest that models which provide for probability transformations are most appropriate for the majority of subjects. Further. we find that the transformation differs for most subjects depending upon whether the risky outcomes are gains or losses. Most subjects are considerably less sensitive to changes in mid-range probability than is proposed by the expected utility model and risk-seeking behavior over "long-shot" odds is common
The appeal of expected utility theory as a basis for a descriptive model of risky decision making has diminished is a result of empirical evidence which suggests that individuals do not behave in a manner consistent with the prescriptive tenets of EUT. In this paper, we explore the influence of probability on risky choice. by proposing and estimating a parametric model of risky decision making. Our results suggest that models which provide for probability transformations are most appropriate for the majority of subjects. Further. we find that the transformation differs for most subjects depending upon whether the risky outcomes are gains or losses. Most subjects are considerably less sensitive to changes in mid-range probability than is proposed by the expected utility model and risk-seeking behavior over quot;long-shotquot; odds is common.
Whether we like it or not we all feel that the world is uncertain. From choosing a new technology to selecting a job, we rarely know in advance what outcome will result from our decisions. Unfortunately, the standard theory of choice under uncertainty developed in the early forties and fifties turns out to be too rigid to take many tricky issues of choice under uncertainty into account. The good news is that we have now moved away from the early descriptively inadequate modeling of behavior. This book brings the reader into contact with the accomplished progress in individual decision making through the most recent contributions to uncertainty modeling and behavioral decision making. It also introduces the reader into the many subtle issues to be resolved for rational choice under uncertainty.
Models and Experiments in Risk and Rationality presents original contributions to the areas of individual choice, experimental economics, operations and analysis, multiple criteria decision making, market uncertainty, game theory and social choice. The papers, which were presented at the FUR VI conference, are arranged to appear in order of increasing complexity of the decision environment or social context in which they situate themselves. The first section `Psychological Aspects of Risk-Bearing', considers choice at the purely individual level and for the most part, free of any specific economic or social context. The second section examines individual choice within the classical expected utility approach while the third section works from a perspective that includes non-expected utility preferences over lotteries. Section four, `Multiple Criteria Decision-Making Under Uncertainty', considers the more specialized but crucial context of uncertain choice involving tradeoffs between competing criteria -- a field which is becoming of increasing importance in applied decision analysis. The final two sections examine uncertain choice in social or group contexts.
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
The need to understand the theories and applications of economic and finance risk has been clear to everyone since the financial crisis, and this collection of original essays proffers broad, high-level explanations of risk and uncertainty. The economics of risk and uncertainty is unlike most branches of economics in spanning from the individual decision-maker to the market (and indeed, social decisions), and ranging from purely theoretical analysis through individual experimentation, empirical analysis, and applied and policy decisions. It also has close and sometimes conflicting relationships with theoretical and applied statistics, and psychology. The aim of this volume is to provide an overview of diverse aspects of this field, ranging from classical and foundational work through current developments. - Presents coherent summaries of risk and uncertainty that inform major areas in economics and finance - Divides coverage between theoretical, empirical, and experimental findings - Makes the economics of risk and uncertainty accessible to scholars in fields outside economics
ABSTRACT: In a risky-choice paradigm, pigeons were given repeated choices between variable and fixed numbers of token reinforcers (stimulus lamps arrayed above the response keys), with each earned token exchangeable for food. The average number of tokens provided by the variable option was parametrically manipulated across conditions; the fixed amount was held constant within a phase and was altered across phases, assuming values of 2, 4, 6, or 8 tokens per choice. The variable distribution was either exponential or rectangular and provided between 0 and 12 tokens. Results indicated strong risk-prone behavior: preference for the variable option when the fixed option provided equal or greater numbers of tokens than the variable amount. Only when the alternatives provided widely disparate amounts favoring the fixed option did preference depart from the risk-prone pattern. Preference for the variable option was reduced or eliminated when tokens were removed from the experimental context, suggesting that the token presentation played a key role in maintaining risk-prone choice patterns. Choice latencies varied inversely with preferences, suggesting that local analyses may provide useful ancillary measures of reinforcer value. Overall, the results indicate that systematic risk sensitivity can be attained with respect to reinforcer amount, and that tokens may be critical in the development of such preferences.