scholarly journals Utility functions predict variance and skewness risk preferences in monkeys

2016 ◽  
Vol 113 (30) ◽  
pp. 8402-8407 ◽  
Author(s):  
Wilfried Genest ◽  
William R. Stauffer ◽  
Wolfram Schultz

Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals’ preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals’ preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys’ choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences.

Author(s):  
Miloš Kopa ◽  
Audrius Kabašinskas ◽  
Kristina Šutienė

Abstract This paper contributes to the research on multi-pillar pension systems with main focus on private pension funds (PFs). In this context, the specific objective of this study is to determine which second-pillar private fund is the best for participants in such systems on the basis of their risk profile. Based on the assumptions on utility functions of the participants in a pension scheme, four types of stochastic dominance (SD) relations are considered, specifically first order, second order, third order and SD generated by utility functions with decreasing absolute risk aversion. We conduct an analysis under two distributional assumptions: empirical and stable distribution of returns. Moreover, the investors for which non-dominated funds are the optimal choices are identified. Allowing for diversification, the efficiency of the PFs with respect to several types of SD is tested. Then, the observed behaviour of participants in the last quarter/year is compared to the results of SD analysis. Finally, the identified SD relations are stress-tested using data originating from a period of turmoil. Despite the focus on Lithuanian PFs, the methodology developed in this work can be employed by participants or PF managers in similar markets of other countries.


Author(s):  
Ana Belén Ramos-Guajardo

AbstractA new clustering method for random intervals that are measured in the same units over the same group of individuals is provided. It takes into account the similarity degree between the expected values of the random intervals that can be analyzed by means of a two-sample similarity bootstrap test. Thus, the expectations of each pair of random intervals are compared through that test and a p-value matrix is finally obtained. The suggested clustering algorithm considers such a matrix where each p-value can be seen at the same time as a kind of similarity between the random intervals. The algorithm is iterative and includes an objective stopping criterion that leads to statistically similar clusters that are different from each other. Some simulations to show the empirical performance of the proposal are developed and the approach is applied to two real-life situations.


2005 ◽  
Vol 50 (164) ◽  
pp. 135-149
Author(s):  
Dejan Trifunovic

In order to rank investments under uncertainty, the most widely used method is mean variance analysis. Stochastic dominance is an alternative concept which ranks investments by using the whole distribution function. There exist three models: first-order stochastic dominance is used when the distribution functions do not intersect, second-order stochastic dominance is applied to situations where the distribution functions intersect only once, while third-order stochastic dominance solves the ranking problem in the case of double intersection. Almost stochastic dominance is a special model. Finally we show that the existence of arbitrage opportunities implies the existence of stochastic dominance, while the reverse does not hold.


2012 ◽  
Vol 07 (01) ◽  
pp. 1250005 ◽  
Author(s):  
DOMINIC GASBARRO ◽  
WING-KEUNG WONG ◽  
J. KENTON ZUMWALT

Prospect theory suggests that risk seeking can occur when investors face losses and thus an S-shaped utility function can be useful in explaining investor behavior. Using stochastic dominance procedures, Post and Levy (2015) find evidence of reverse S-shaped utility functions. This is consistent with investors exhibiting risk-seeking tendencies in bull markets and risk aversion in bear markets. We use both ascending and descending stochastic dominance procedures to test for risk-averse and risk-seeking behavior. By partitioning iShares' return distributions into negative and positive return regions, we find evidence of all four utility functions: concave, convex, S-shaped and reverse S-shaped.


Metamorphosis ◽  
2014 ◽  
Vol 13 (1) ◽  
pp. 26-32
Author(s):  
Afreen Arif H. ◽  
T.P.M. Pakkala

Most of the utility functions studied earlier concentrated on properties of risk aversion. In this article, the authors have introduced a new class of utility function called the Power Law with Exponential Cut-off (PLEC) utility function, which exhibits all the absolute and relative risk aversion and risk loving preferences of individuals, under various conditions. It generalises and encompasses other systems of utility functions like that of exponential power. Certain properties of this utility function are discussed. Sensitivity analysis exhibits different portfolio allocations for various risk preferences. The analysis also shows that arbitrary risk preferences may lead to biased risk response estimates. Performance of PLEC utility function in portfolio allocation problem is demonstrated through numerical examples. This is evaluated through optimal solutions.


2021 ◽  
Author(s):  
Kaname Miyagishima

AbstractIn a simple model where agents’ monetary payoffs are uncertain, this paper examines the aggregation of subjective expected utility functions which are interpersonally noncomparable. A maximin social welfare criterion is derived from axioms of efficiency, ex post equity, and social rationality, combined with the independence of beliefs and risk preferences in riskless situations (Chambers and Echenique in Games Econ Behav 76:582–595, 2012). The criterion compares allocations by the values of the prospects composed of the statewise minimum payoffs evaluated by the certainty equivalents. Because of this construction, the criterion is egalitarian and risk averse.


Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5565 ◽  
Author(s):  
Remigiusz Wisniewski ◽  
Iwona Grobelna ◽  
Andrei Karatkevich

In this paper, we study selected aspects of determinism in the control part of a cyber-physical system (CPS) that is specified by a Petri net-based model. In particular, the control interpreted Petri nets (CIPNs) are applied, which are an extension of the ordinary Petri nets, supplemented by signals (related to sensors and actuators) that permit communication with the environment. The notions of weak and strong determinism in a system described by a CIPN are introduced in the paper. The proposed concepts are supported by formal definitions and theorems. Moreover, a novel modelling methodology for a deterministic system specified by a CIPN is proposed. The presented solutions are illustrated by a case study example of a real-life cyber-physical system. Finally, the results of experimental verification of the proposed determinism-based techniques are demonstrated and discussed.


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