Do financial professionals behave according to prospect theory? An experimental study
TL;DR: In this article, the authors investigated whether and to what extent this support generalizes to more naturally occurring circumstances and found that financial professionals behave according to prospect theory and violate expected utility maximization.
Abstract: Prospect theory is increasingly used to explain deviations from the traditional paradigm of rational agents. Empirical support for prospect theory comes mainly from laboratory experiments using student samples. It is obviously important to know whether and to what extent this support generalizes to more naturally occurring circumstances. This article explores this question and measures prospect theory for a sample of private bankers and fund managers. We obtained clear support for prospect theory. Our financial professionals behaved according to prospect theory and violated expected utility maximization. They were risk averse for gains and risk seeking for losses and their utility was concave for gains and (slightly) convex for losses. They were also averse to losses, but less so than commonly observed in laboratory studies and assumed in behavioral finance. A substantial minority focused on gains and largely ignored losses, behavior reminiscent of what caused the current financial crisis.
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TL;DR: This article found that both rankings and tournament incentives increase risk-taking among underperforming professionals, but not among students, and that rank-driven risk taking is robust to various experimental settings, including private identity priming and framing, and related to preferences for relative per-formance.
Abstract: Rankings are pervasive in the finance industry, yet there is no research how they impact financial professionals? behavior. We run lab-in-the-field experiments with 657 profession- als, lab experiments with 432 students and collect survey evidence from 1,349 respondents to investigate how rank incentives affect investment decisions. We find that both rankings and tournament incentives increase risk-taking among underperforming professionals, but not among students. Rank-driven risk-taking is robust to various experimental settings, including private identity priming and framing, and related to preferences for relative per- formance, which we find to be stronger for professionals than for the general population and other competitive professions.
59 citations
TL;DR: In this article, the effect of key audit matters (KAM) in the auditor's report as required by the new ISA 701 is investigated, considering investment professionals and non-professional investors.
Abstract: We investigate the effect of key audit matters (KAM) in the auditor’s report as required by the new ISA 701. We consider investment professionals and non-professional investors in our experiments, ...
47 citations
TL;DR: In this paper, a large-scale empirical analysis of 28.5 million trades made by 81.3 thousand traders of an online financial trading community over 28 months was conducted to explore the large scale empirical aspect of prospect theory.
Abstract: Prospect theory is widely viewed as the best available descriptive model of how people evaluate risk in experimental settings. According to prospect theory, people are typically risk-averse with respect to gains and risk-seeking with respect to losses, known as the “reflection effect”. People are much more sensitive to losses than to gains of the same magnitude, a phenomenon called “loss aversion”. Despite of the fact that prospect theory has been well developed in behavioral economics at the theoretical level, there exist very few large-scale empirical studies and most of the previous studies have been undertaken with micro-panel data. Here we analyze over 28.5 million trades made by 81.3 thousand traders of an online financial trading community over 28 months, aiming to explore the large-scale empirical aspect of prospect theory. By analyzing and comparing the behavior of winning and losing trades and traders, we find clear evidence of the reflection effect and the loss aversion phenomenon, which are essential in prospect theory. This work hence demonstrates an unprecedented large-scale empirical evidence of prospect theory, which has immediate implication in financial trading, e.g., developing new trading strategies by minimizing the impact of the reflection effect and the loss aversion phenomenon. Moreover, we introduce three novel behavioral metrics to differentiate winning and losing traders based on their historical trading behavior. This offers us potential opportunities to augment online social trading where traders are allowed to watch and follow the trading activities of others, by predicting potential winners based on their historical trading behavior.
41 citations
TL;DR: To measure framing effects in engineering decisions, the Envision rating system for sustainable infrastructure is used, which aims to help the authors better understand how choice structures influence engineering decisions.
Abstract: Decision aids, ranging from rating systems to design software to regulatory standards, guide the design and evaluation of infrastructure projects. To present the information in these decision aids, there must first be some options such as, attributes are or are not presented, and, just as in other domains, these factors are likely to influence decisions in infrastructure development. The authors of this paper seek to better understand how choice structures influence engineering decisions. Prospect theory, which is well established in the behavioral sciences, asserts that people tend to think of possible outcomes relative to their starting point, not the resulting end point. For instance, framing a decision outcome as a loss in value (rather than a gain) can reduce the decision makers’ acceptance of risk and, in turn, lead to more conservative outcomes. To measure framing effects in engineering decisions, this paper uses the Envision rating system for sustainable infrastructure, which aims to help ...
36 citations
TL;DR: The task of automatically predicting human decision-making and its use in designing intelligent human-aware automated computer systems of varying natures is explored—from purely conflicting interaction settings to fully cooperative interaction settings.
Abstract: Human decision-making often transcends our formal models of "rationality." Designing intelligent agents that interact proficiently with people necessitates the modeling of human behavior and the prediction of their decisions. In this book, we explore the task of automatically predicting human decision-making and its use in designing intelligent human-aware automated computer systems of varying natures—from purely conflicting interaction settings (e.g., security and games) to fully cooperative interaction settings (e.g., autonomous driving and personal robotic assistants). We explore the techniques, algorithms, and empirical methodologies for meeting the challenges that arise from the above tasks and illustrate major benefits from the use of these computational solutions in real-world application domains such as security, negotiations, argumentative interactions, voting systems, autonomous driving, and games. The book presents both the traditional and classical methods as well as the most recent a...
35 citations
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TL;DR: In this paper, the authors examined the complete pattern of 256 model variants that can be constructed from twenty functions, and their explanatory power was assessed, and the best model has a power value function, a risky weighting function due to Prelec (1998), and a Logit function.
Abstract: Many different functional forms have been suggested for both the value function and probability weighting function of Cumulative Prospect Theory (Tversky and Kahneman, 1992). There are also many stochastic choice functions available. Since these three components only make predictions when considered in combination, this paper examines the complete pattern of 256 model variants that can be constructed from twenty functions. All these variants are fit to experimental data and their explanatory power assessed. Significant interaction effects are observed. The best model has a power value function, a risky weighting function due to Prelec (1998), and a Logit function.
439 citations
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01 Nov 2009
TL;DR: Experimental economics as mentioned in this paper explores the history of experiments in economics, provides examples of different types of experiments, and shows that the growing use of experimental methods is transforming economics into a genuinely empirical science.
Abstract: Since the 1980s, there has been explosive growth in the use of experimental methods in economics, leading to exciting developments in economic theory and policy. Despite this, the status of experimental economics remains controversial. In Experimental Economics, the authors draw on their experience and expertise in experimental economics, economic theory, the methodology of economics, philosophy of science, and the econometrics of experimental data to offer a balanced and integrated look at the nature and reliability of claims based on experimental research.
The authors explore the history of experiments in economics, provide examples of different types of experiments, and show that the growing use of experimental methods is transforming economics into a genuinely empirical science. They explain that progress is being held back by an uncritical acceptance of folk wisdom regarding how experiments should be conducted, a failure to acknowledge that different objectives call for different approaches to experimental design, and a misplaced assumption that principles of good practice in theoretical modeling can be transferred directly to experimental design. Experimental Economics debates how such limitations might be overcome, and will interest practicing experimental economists, nonexperimental economists wanting to interpret experimental research, and philosophers of science concerned with the status of knowledge claims in economics.
342 citations
TL;DR: The authors explored a pair of methods for determining money indifference points that are procedurally closer than is common in this research to the choice phase of the preference reversal experiment, and found that these methods reduced the number of reversals, as compared to JIPs, to the point with PEST that the remaining ones may be due primarily to chance fluctuations in choices between gambles.
Abstract: Preference reversal appears to be non-transitive choice behavior, inasmuch as subjects choosing between two gambles with similar expected values typically select the one with a larger chance of winning (a P-bet), yet they place a higher certainty equivalent, or judged indifference point (JIP), on the one with the larger amount to win (the $-bet). In the present experiments, we explore a pair of methods for determining money indifference points that are procedurally closer than is common in this research to the choice phase of the preference reversal experiment. The two new approaches for determining money indifference points for gambles (called choice indifference points, or CIP) are as follows: a version of the classical psychophysical up-down method and a variant called PEST (i.e., Parameter Estimation by Sequential Testing). With both methods, CIPs reduced the number of reversals, as compared to JIPs, to the point with PEST that the remaining ones may be due primarily to chance fluctuations in choices between gambles. Subjects who reversed frequently usually judged the gambles to have similar values; those who did not reverse at all, judged them as different. The typical subjects exhibits JIP>CIP for $-bets, but not for P-bets. This bias appears to underlie the observed intransitivity when JIP is used.
238 citations
TL;DR: In this paper, the authors test whether the frequency of feedback information about the performance of an investment portfolio and the flexibility with which the investor can change it influence her risk attitude in markets.
Abstract: We test whether the frequency of feedback information about the performance of an investment portfolio and the flexibility with which the investor can change it influence her risk attitude in markets.In line with the prediction of Myopic Loss Aversion (Benartzi and Thaler, 1995), we find that more information and more flexibility result in less risk taking.Market prices of risky assets are significantly higher if feedback frequency and decision flexibility are reduced.This result supports the findings from individual decision making, and shows that markets do not eliminate such behavior.
203 citations
TL;DR: In this article, the authors present an experiment that completely measures the utility and loss aversion component of risk attitudes, using a representative sample of N = 1935 respondents from the general public, in a parameter free way.
203 citations