Reevaluating evidence on myopic loss aversion: aggregate patterns versus individual choices

Investors who are more willing to accept risks when evaluating their investments less frequently are said to exhibit myopic loss aversion (MLA). Several recent experimental studies found that, on average, subjects bet significantly higher amounts on a risky lottery when they observe only a cumulative outcome of several realizations of the lottery (long evaluation period). In this article, we reexamine these empirical findings by analyzing individual rather than aggregate choice patterns. The behavior of the majority of subjects is inconsistent with the hypothesis of MLA: they bet an intermediate fraction of their initial endowment and these bets, on average, are not significantly different across two treatments with short and long evaluation period. We discuss several alternative explanations of this finding, including the Fechner model of random errors and the financial asset pricing model.     

Reverse common ratio effect

The results of a new experimental study reveal highly systematic violations of expected utility theory. The pattern of these violations is exactly the opposite of the classical common ratio effect discovered by Allais (1953). Two recent decision theories—stochastic expected utility theory (Blavatskyy 2007) and perceived relative argument model (Loomes 2008)—predicted the existence of a reverse common ratio effect. However, these theories can rationalize only one part of the new experimental data reported in this paper. The other part appears to be neither predicted by existing theories nor documented in the existing empirical studies.     

Why do young women marry old men?

This paper presents an overlapping generations household model with positive assortative matching (richer individuals marry richer partners), incomplete information about partner’s type (it takes time to reveal income-earning capabilities of individuals) and a gender pay gap on the labor market (men are more likely to end up with a high-paying job). In equilibrium, a gender pay gap creates an excess supply of desirable husbands and women marry early to increase their chance of being matched with an ideal partner, which results in a gender age gap on the marriage market. A modified model with asymmetric information yields a similar result. An extended model where individuals have an option to remain single (the marriage market does not necessarily clear in equilibrium) yields a similar result as well.     

Risk Aversion when Gains are Likely and Unlikely: Evidence from a Natural Experiment with Large Stakes

In the television show Deal or No Deal a contestant is endowed with a sealed box, which potentially contains a large monetary prize. In the course of the show the contestant learns more information about the distribution of possible monetary prizes inside her box. Consider two groups of contestants, who learned that the chances of their boxes containing a large prize are 20% and 80% correspondingly. Contestants in both groups receive qualitatively similar price offers for selling the content of their boxes. If contestants are less risk averse when facing unlikely gains, the price offer is likely to be more frequently rejected in the first group than in the second group. However, the fraction of rejections is virtually identical across two groups. Thus, contestants appear to have identical risk attitudes over (large) gains of low and high probability.      

Dual choice axiom and probabilistic choice

Journal of Risk and Uncertainty - A decision maker chooses in a probabilistic manner if she does not necessarily prefer the same choice alternative when repeatedly presented with the same choice...     

On risk-averse maximum weighted subgraph problems

In this work, we consider a class of risk-averse maximum weighted subgraph problems (R-MWSP). Namely, assuming that each vertex of the graph is associated with a stochastic weight, such that the joint distribution is known, the goal is to obtain a subgraph of minimum risk satisfying a given hereditary property. We employ a stochastic programming framework that is based on the formalism of modern theory of risk measures in order to find minimum-risk hereditary structures in graphs with stochastic vertex weights. The introduced form of risk function for measuring the risk of subgraphs ensures that optimal solutions of R-MWS problems represent maximal subgraphs. A graph-based branch-and-bound (BnB) algorithm for solving the proposed problems is developed and illustrated on a special case of risk-averse maximum weighted clique problem. Numerical experiments on randomly generated Erdös-Rényi graphs demonstrate the computational performance of the developed BnB.     

On the number of local minima for the multidimensional assignment problem

The Multidimensional Assignment Problem (MAP) is an NP-hard combinatorial optimization problem occurring in many applications, such as data association, target tracking, and resource planning. As many solution approaches to this problem rely, at least partly, on local neighborhood search algorithms, the number of local minima affects solution difficulty for these algorithms. This paper investigates the expected number of local minima in randomly generated instances of the MAP. Lower and upper bounds are developed for the expected number of local minima, E[M], in an MAP with iid standard normal coefficients. In a special case of the MAP, a closed-form expression for E[M] is obtained when costs are iid continuous random variables. These results imply that the expected number of local minima is exponential in the number of dimensions of the MAP. Our numerical experiments indicate that larger numbers of local minima have a statistically significant negative effect on the quality of solutions produced by several heuristic algorithms that involve local neighborhood search.Partially supported by the NSF grant DMI-0457473.     

Error Propagation in the Elicitation of Utility and Probability Weighting Functions

Elicitation methods in decision-making under risk allow us to infer the utilities of outcomes as well as the probability weights from the observed preferences of an individual. An optimally efficient elicitation method is proposed, which takes the inevitable distortion of preferences by random errors into account and minimizes the effect of such errors on the inferred utility and probability weighting functions. Under mild assumptions, the optimally efficient method for eliciting utilities and probability weights is the following three-stage procedure. First, a probability is elicited whose subjective weight is one half. Second, the utility function is elicited through the midpoint chaining certainty equivalent method using the probability elicited at the first stage. Finally, the probability weighting function is elicited through the probability equivalent method.     

Risk preferences of Australian academics: where retirement funds are invested tells the story

Risk preferences of Australian academics are elicited by analyzing the aggregate distribution of their retirement funds (superannuation) across available investment options. Not more than 10 % of retirement funds are invested as if their owners maximize expected utility under the assumption of constant relative risk aversion with an empirically plausible level of risk aversion. An implausibly high level of risk aversion is required to rationalize any investment into bonds when stocks are available. Not more than 36.54 % of all investments can be rationalized by a model of loss averse preferences. Moreover, the levels of loss aversion typically reported in the experimental studies imply overinvestment in bonds, which is not observed in the data. Up to 67.18 % of all investments can be rationalized by rank-dependent utility or Yaari’s (Econometrica 55:95–115 1987) dual model with empirically plausible parameters. A median Australian academic behaves as if maximizing rank-dependent utility with parameter \(\gamma \in [0.76, 0.79]\) in a Tversky and Kahneman (J Risk Uncertain 5:297–323 1992) probability weighting function.     

Betting on own knowledge: Experimental test of overconfidence

This paper presents a new incentive compatible method for measuring confidence in own knowledge. This method consists of two parts. First, an individual answers several general knowledge questions. Second, the individual chooses among three alternatives: (1) one question is selected at random and the individual receives a payoff if he or she has answered this question correctly; (2) the individual receives the same payoff with a probability equal to the percentage of correctly answered questions; (3) either the first or the second alternative is selected. The choice of the first (second) alternative reveals overconfidence (underconfidence). The individual is well calibrated if he or she chooses the third alternative. Experimental results show that subjects, on average, exhibit underconfidence about their own knowledge when the incentive compatible mechanism is used. Their confidence in own knowledge does not depend on their attitude towards risk/ambiguity.