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"UTILITY THEORY"
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Fuzzy portfolio selection based on three-way decision and cumulative prospect theory
The goal of fuzzy portfolio selection is to make a combination of securities which can maximize the return or minimize the risk. Most of existing studies assumed that the investor has all the cash in hand and no securities position before portfolio optimization, which is sometimes inconsistent to reality. Besides, many studies are based on expected utility theory, which is in conflict with the behavior of some investors and may also lead to over-concentration of capital. Therefore, in this paper, we propose a fuzzy portfolio selection model based on three-way decision and cumulative prospect theory, which can mitigate the two shortcomings mentioned above. In this model, every action in the action set to the candidate securities is assigned to a prospect value and we can construct a tri-partition of the candidate securities according to three-way decision theory. To validate the effectiveness of our approach, we adopted two case studies on the basis of real market data. The experimented results prove that the using of three-way decision and cumulative prospect theory increases the investment return, meanwhile, reduces the risk for the investor.
Journal Article
Multiple Criteria Decision Making, Multiattribute Utility Theory: Recent Accomplishments and What Lies Ahead
This paper is an update of a paper that five of us published in 1992. The areas of multiple criteria decision making (MCDM) and multiattribute utility theory (MAUT) continue to be active areas of management science research and application. This paper extends the history of these areas and discusses topics we believe to be important for the future of these fields.
Journal Article
HETEROGENEOUS CHOICE SETS AND PREFERENCES
We propose a robust method of discrete choice analysis when agents’ choice sets are unobserved. Our core model assumes nothing about agents’ choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between choice sets and preferences. We first characterize the sharp identification region of the model’s parameters by a finite set of conditional moment inequalities. We then apply our theoretical findings to learn about households’ risk preferences and choice sets from data on their deductible choices in auto collision insurance. We find that the data can be explained by expected utility theory with low levels of risk aversion and heterogeneous non-singleton choice sets, and that more than three in four households require limited choice sets to explain their deductible choices. We also provide simulation evidence on the computational tractability of our method in applications with larger feasible sets or higher-dimensional unobserved heterogeneity.
Journal Article
Loss Aversion Under Prospect Theory: A Parameter-Free Measurement
Agrowing body of qualitative evidence shows that loss aversion, a phenomenon formalized in prospect theory, can explain a variety of field and experimental data. Quantifications of loss aversion are, however, hindered by the absence of a general preference-based method to elicit the utility for gains and losses simultaneously. This paper proposes such a method and uses it to measure loss aversion in an experimental study without making any parametric assumptions. Thus, it is the first to obtain a parameter-free elicitation of prospect theory's utility function on the whole domain. Our method also provides an efficient way to elicit utility midpoints, which are important in axiomatizations of utility. Several definitions of loss aversion have been put forward in the literature. According to most definitions we find strong evidence of loss aversion, at both the aggregate and the individual level. The degree of loss aversion varies with the definition used, which underlines the need for a commonly accepted definition of loss aversion.
Journal Article
TIME TO CHANGE WHAT TO SOW: RISK PREFERENCES AND TECHNOLOGY ADOPTION DECISIONS OF COTTON FARMERS IN CHINA
This paper examines the role of individual risk attitudes in the decision to adopt a new form of agricultural biotechnology in China. I conducted a survey and a field experiment to elicit the risk preferences of Chinese farmers, who faced the decision of whether to adopt genetically modified Bt cotton a decade ago. In my analysis, I expand the measurement of risk preferences beyond expected utility theory to incorporate prospect theory. I find that farmers who are more risk averse or more loss averse adopt Bt cotton later. Farmers who overweight small probabilities adopt Bt cotton earlier.
Journal Article
Fantasy and Dread: The Demand for Information and the Consumption Utility of the Future
We present evidence that intrinsic demand for information about the future is increasing in expected future consumption utility. In the first experiment, subjects may resolve a lottery now or later. The information is useless for decision making, but the larger the reward, the more likely subjects are to pay to resolve the lottery early. In the second experiment, subjects may pay to avoid being tested for herpes simplex virus type 1 (HSV-1) and the more highly feared type 2 (HSV-2). Subjects are three times more likely to avoid testing for HSV-2, suggesting that more aversive outcomes lead to more information avoidance. In a third experiment, subjects make choices about when to get tested for a fictional disease. Some subjects behave in a way consistent with expected utility theory, and others exhibit greater delay of information for more severe diseases. We also find that information choice is correlated with positive affect, ambiguity aversion, and time preference, as some theories predict.
Data, as supplemental material, are available at
https://doi.org/10.1287/mnsc.2016.2550
.
This paper was accepted by Teck-Hua Ho, behavioral economics
.
Journal Article
Retrospectives: How Economists Came to Accept Expected Utility Theory: The Case of Samuelson and Savage
Expected utility theory dominated the economic analysis of individual decision-making under risk from the early 1950s to the 1990. Among the early supporters of the expected utility hypothesis in the von Neumann–Morgenstern version were Milton Friedman and Leonard Jimmie Savage, both based at the University of Chicago, and Jacob Marschak, a leading member of the Cowles Commission for Research in Economics. Paul Samuelson of MIT was initially a severe critic of expected utility theory. Between mid-April and early May 1950, Samuelson composed three papers in which he attacked von Neumann and Morgenstern's axiomatic system. By 1952, however, Samuelson had somewhat unexpectedly become a resolute supporter of the expected utility hypothesis. Why did Samuelson change his mind? Based on the correspondence between Samuelson, Savage, Marschak, and Friedman, this article reconstructs the joint intellectual journey that led Samuelson to accept expected utility theory and Savage to revise his motivations for supporting it.
Journal Article
Ellsberg Revisited: An Experimental Study
An extension to Ellsberg's experiment demonstrates that attitudes to ambiguity and compound objective lotteries are tightly associated. The sample is decomposed into three main groups: subjective expected utility subjects, who reduce compound objective lotteries and are ambiguity neutral, and two groups that exhibit different forms of association between preferences over compound lotteries and ambiguity, corresponding to alternative theoretical models that account for ambiguity averse or seeking behavior.
Journal Article
Social Influence Bias: A Randomized Experiment
Our society is increasingly relying on the digitized, aggregated opinions of others to make decisions. We therefore designed and analyzed a large-scale randomized experiment on a social news aggregation Web site to investigate whether knowledge of such aggregates distorts decision-making. Prior ratings created significant bias in individual rating behavior, and positive and negative social influences created asymmetric herding effects. Whereas negative social influence inspired users to correct manipulated ratings, positive social influence increased the likelihood of positive ratings by 32% and created accumulating positive herding that increased final ratings by 25% on average. This positive herding was topic-dependent and affected by whether individuals were viewing the opinions of friends or enemies. A mixture of changing opinion and greater turnout under both manipulations together with a natural tendency to up-vote on the site combined to create the herding effects. Such findings will help interpret collective judgment accurately and avoid social influence bias in collective intelligence in the future.
Journal Article