scholarly journals Calculation of Price Equilibria for Utility Functions of the HARA Class

1986 ◽  
Vol 16 (S1) ◽  
pp. S91-S97 ◽  
Author(s):  
Markus Lienhard

AbstractWe explicitly calculate price equilibria for power and logarithmic utility functions which—together with the exponential utility functions—form the so-called HARA (Hyperbolic Absolute Risk Aversion) class.A price equilibrium is economically admissible in the market which is a closed system. Furthermore it is on the one side individually optimal for each participant of the market (in the sense of maximal expected utility), on the other side it is a Pareto optimum and thus collectively optimal for the market as a whole.

Author(s):  
Kerry E. Back

Expected utility is introduced. Risk aversion and its equivalence with concavity of the utility function (Jensen’s inequality) are explained. The concepts of relative risk aversion, absolute risk aversion, and risk tolerance are introduced. Certainty equivalents are defined. Expected utility is shown to imply second‐order risk aversion. Linear risk tolerance (hyperbolic absolute risk aversion), cautiousness parameters, constant relative risk aversion, and constant absolute risk aversion are described. Decreasing absolute risk aversion is shown to imply a preference for positive skewness. Preferences for kurtosis are discussed. Conditional expectations are introduced, and the law of iterated expectations is explained. Risk averse investors are shown to dislike mean‐independent noise.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Honglian Guo ◽  
Zhenzhen Wu ◽  
Han Li

Based on principal-agent theory, this paper establishes an incentive contract mechanism between government and NPO under asymmetric information, and analyzes the impact of absolute risk aversion and output level on the expected utility of government, NPO and society. Research shows that risk aversion is negatively correlated with the expected utility of government, NPO and society. The output coefficient is positively correlated with the expected utility of government, NPO and society. Reducing absolute risk aversion, increasing output coefficient and increasing government incentives can effectively motivate NPO to actively participate in social rescue activities.


1980 ◽  
Vol 53 (3) ◽  
pp. 285 ◽  
Author(s):  
Steven A. Lippman ◽  
John J. McCall ◽  
Wayne L. Winston

2006 ◽  
Vol 29 (2) ◽  
pp. 155-160 ◽  
Author(s):  
Mario A. Maggi ◽  
Umberto Magnani ◽  
Mario Menegatti

2009 ◽  
Vol 25 (2) ◽  
pp. 153-159
Author(s):  
Joseph B. Kadane ◽  
Gaia Bellone

According to Mark Rubinstein (2006) ‘In 1952, anticipating Kenneth Arrow and John Pratt by over a decade, he [de Finetti] formulated the notion of absolute risk aversion, used it in connection with risk premia for small bets, and discussed the special case of constant absolute risk aversion.’ The purpose of this note is to ascertain the extent to which this is true, and at the same time, to correct certain minor errors that appear in de Finetti's work.


2020 ◽  
Vol 66 (10) ◽  
pp. 4630-4647 ◽  
Author(s):  
Rachel J. Huang ◽  
Larry Y. Tzeng ◽  
Lin Zhao

We develop a continuum of stochastic dominance rules for expected utility maximizers. The new rules encompass the traditional integer-degree stochastic dominance; between adjacent integer degrees, they formulate the consensus of individuals whose absolute risk aversion at the corresponding integer degree has a negative lower bound. By extending the concept of “uniform risk aversion” previously proposed in the literature to high-order risk preferences, we interpret the fractionalized degree parameter as a benchmark individual relative to whom all considered individuals are uniformly no less risk averse in the lottery choices. The equivalent distribution conditions for the new rules are provided, and the fractional degree “increase in risk” is defined. We generalize the previously defined notion of “risk apportionment” and demonstrate its usefulness in characterizing comparative statics of risk changes in fractional degrees. This paper was accepted by David Simchi-Levi, decision analysis.


Econometrica ◽  
1983 ◽  
Vol 51 (1) ◽  
pp. 223 ◽  
Author(s):  
Philip H. Dybvig ◽  
Steven A. Lippman

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