Utility-based two-stage models with fairness concern

This paper studies the impact of social comparison and fairness concerns on the efficiency of a two-stage process. The decision maker of each stage cares about not only the absolute score of his efficiency, but also the relative status when comparing with the other. By incorporating the utility theory and the concept of fairness, an efficiency-based Neumann–Morgenstern cardinal utility is defined to compose of basic utility from his self-efficiency and additional utility from the fairness concern of the other’s efficiency. Utility-based two-stage models are proposed to optimize the utilities of the stages rather than only the efficiencies instead. We characterize the concern of fairness as advantageous and disadvantageous inequity based on equitable outcome comparison. By investigating the non-cooperating relationship between two stages, we show that the stage dominating the process has the incentive to optimize his efficiency without ignoring that of the other, which is contrary to the conventional situation. In addition, the coefficients of equitable outcome and inequity significantly affect the efficiencies of both stages. We further investigate the cooperation between two stages and find that the efficiencies of the stages vary with the coefficients of unfairness perceptions. Numerical analysis verifies the validity of the proposed models and identifies the impacts of the coefficients of equitable outcome and inequity on the stages’ and overall efficiencies.     

社会地位、收入税和随机经济增长

在一个具有生产性政府花费的随机增长模型中,把体现社会地位的财富引入消费者效用函数.讨论了社会地位、收入税、随机扰动对经济增长、消费—财富比和消费者福利的影响以及社会地位对税收政策制订的影响;并且确定了最优税率.     

两类不同的效用函数模型及其经济分析

根据参考文献[2],本文通过分析效用函数应具有的性质,首先构造了一类含有预期财富的效用函数模型,并运用该模型对文献[2]中的观点提供了数学解释;进而,从人的价值观角度构建了另一类含社会评价价值的效用函数模型,为人们生活态度的理性选择提供了数学依据。     

HARA frontiers of optimal portfolios in stochastic markets

In this paper, we consider the optimal portfolio selection problem in continuous-time settings where the investor maximizes the expected utility of the terminal wealth in a stochastic market. The utility function has the structure of the HARA family and the market states change according to a Markov process. The states of the market describe the prevailing economic, financial, social and other conditions that affect the deterministic and probabilistic parameters of the model. This includes the distributions of the random asset returns as well as the utility function. We analyzed Black–Scholes type continuous-time models where the market parameters are driven by Markov processes. The Markov process that affects the state of the market is independent of the underlying Brownian motion that drives the stock prices. The problem of maximizing the expected utility of the terminal wealth is investigated and solved by stochastic optimal control methods for exponential, logarithmic and power utility functions. We found explicit solutions for optimal policy and the associated value functions. We also constructed the optimal wealth process explicitly and discussed some of its properties. In particular, it is shown that the optimal policy provides linear frontiers.     

The spirit of capitalism,non-expected utility and asset pricing

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Moments of utility functions and their applications

This paper presents moments and cross-moments of utility functions and measures of utility dependence. We start with an interpretation of the nth moment of a utility function, and describe methods for its assessment in practice and consistency checks that need to be satisfied for any assessed moments. We then show how moments of a utility function (i) provide a new method to determine the parameters of a given functional form of a utility function and (ii) to derive the functional form of a utility function that satisfies some given moment assessments. Next, we derive a fundamental formula that relates the expected utility of a joint distribution to the expected utility of the marginal distributions for multiattribute utility functions. We use this formulation to provide an intuitive interpretation for cross-moments of utility functions and illustrate their use in (i) constructing multiattribute utility functions that incorporate utility dependence and (ii) in providing necessary conditions for utility independence in decisions with multiple attributes. We end with a new measure of utility dependence for multiattribute utility functions and work through several examples to illustrate the approach.     

群体性突发事件发生机理的多阶段动态博弈模型分析

群体性突发事件成为影响我国社会稳定和实现现代化平稳过渡的重要因素.假设弱势群体的效用函数考虑到公平因素的私人信息;不同时期各社会群体的经济收入是动态变化的;经济地位的差异决定了不同社会阶层的划分;冲突中"有限理性"的社会群体采取前向归纳法形成适应性预期,在此基础上构造了多阶段动态博弈模型,得出了弱势群体采取无条件抗争策略、积极妥协策略和积极抗争策略的约束条件,以及群体性突发事件的两种发生机理.除了弱势社会群体对社会分配体制造成的经济收入差距的敏感程度,社会体制(博弈结构)决定的各社会群体采取不同策略的预期收益以外,弱势群体的收益增长情况是影响群体性突发事件产生根源的另一个重要因素.     

Portfolio selection in stochastic markets with HARA utility functions

In this paper, we consider the optimal portfolio selection problem where the investor maximizes the expected utility of the terminal wealth. The utility function belongs to the HARA family which includes exponential, logarithmic, and power utility functions. The main feature of the model is that returns of the risky assets and the utility function all depend on an external process that represents the stochastic market. The states of the market describe the prevailing economic, financial, social, political and other conditions that affect the deterministic and probabilistic parameters of the model. We suppose that the random changes in the market states are depicted by a Markov chain. Dynamic programming is used to obtain an explicit characterization of the optimal policy. In particular, it is shown that optimal portfolios satisfy the separation property and the composition of the risky portfolio does not depend on the wealth of the investor. We also provide an explicit construction of the optimal wealth process and use it to determine various quantities of interest. The return-risk frontiers of the terminal wealth are shown to have linear forms. Special cases are discussed together with numerical illustrations.     

Social utility functions for strategic decisions in probabilistic voting models

This paper studies societies which have probabilistic voting that is smooth, scalable and unbiased. Its results establish that, in such societies, the decisions of vote-seeking candidates who start at a common location (such as the status quo for the society's policies and/or the same allocation of campaign resources) contain implicit rationality properties. In particular, it shows that in every such society there exist social utility functions which simultaneously rationalize the directional Nash behavior of candidates, the stationary electoral equilibria, and the non-degenerate local electoral equilibria which can occur at these locations. This is shown to be true both for unconstrained and for constrained sets of possible candidate locations. An example of such a utility function (which occurs in every one of the societies under consideration) is also provided.     

On minkowski metric and weighted tchebyshev norm in vector optimization ∗

The typical approach in solving vector optimization problems is to scalarize the vector cost function into a single cost function by means of some utility or value function. A very large class of utility function is given by the Minkowski’s metric proposed by Charnes and Cooper in the context of goal programming. This includes the special case of linear scalarization and the weighted Tchebyshev norm. We shall furnish a rigorous justification that there is no equivalent relationship between the general vector optimization problem and scalarized optimization problems using any Minkowski’s metric utility function. Furthermore, we also show that the weighted Tchebyshev norm is, in some sense, the best amongst the class of Minkowski’s metric utility functions since it is the only scalarization method which yields an equivalence relation between the weak vector optimization problem and a set of scalar optimization problems, without any convexity assumption     

On efficient portfolio selection using convex risk measures

In this article we systematically revisit the classic portfolio selection theory in both of its branches, the determination of the efficient financial positions among such a choice set and the selection of the financial position which maximizes some utility function whose functional form involves some ‘measure of risk’. We study these problems by considering certain classes of convex risk measures and we show that for these classes the solution of the utility maximization problems in reflexive spaces take the form of a zero-sum game between the investor and the market.     

不公平厌恶影响下的零售商销售努力自组织演化

构建了制造商通过销售回馈与惩罚契约来对具有不公平厌恶心理偏好的零售商群体的销售努力进行激励的计算实验模型,研究了零售商的不公平厌恶心理偏好对激励效果产生的影响。实验结果表明:零售商的不公平厌恶心理会对激励效果产生负面的影响;制造商设定的销售目标越高,不公平厌恶心理的负面影响就越大;当某零售商的销售量一旦低于目标销售量而遭受惩罚时,其会导致该零售商加剧不公平感知从而降低销售努力水平的路径依赖,导致制造商利润下降的主要原因是被惩罚零售商群体为其所带来的渠道利润降低;制造商在激励过程中应该更加重视被惩罚者的不公平厌恶心理。     

Portfolio Optimization with Stochastic Volatilities and Constraints: An Application in High Dimension

In this paper we are interested in an investment problem with stochastic volatilities and portfolio constraints on amounts. We model the risky assets by jump diffusion processes and we consider an exponential utility function. The objective is to maximize the expected utility from the investor terminal wealth. The value function is known to be a viscosity solution of an integro-differential Hamilton-Jacobi-Bellman (HJB in short) equation which could not be solved when the risky assets number exceeds three. Thanks to an exponential transformation, we reduce the nonlinearity of the HJB equation to a semilinear equation. We prove the existence of a smooth solution to the latter equation and we state a verification theorem which relates this solution to the value function. We present an example that shows the importance of this reduction for numerical study of the optimal portfolio. We then compute the optimal strategy of investment by solving the associated optimization problem.     

A benchmark solution for the risk-averse newsvendor problem

In this paper, we derive the first order conditions for optimality for the problem of a risk-averse expected-utility maximizer newsvendor. We use these conditions to solve a special case where the utility function is any increasing differentiable function, and the random demand is uniformly distributed. This special case has a simple closed form solution and therefore it provides an insightful and practical interpretation to the optimal point. We show some properties of the solution and also demonstrate how it can be used for assessing the newsvendor utility function parameters.     

Zero-Level Pricing and the HARA Utility Functions

In the mathematical economics literature, the zero-level pricing method has been proposed to provide a unique price for a nonmarketable new asset. From the viewpoint of robust pricing theory, its disadvantage is that the method depends on the investor utility function and initial wealth. In some situations, the zero-level price is universal, namely, independent of the utility function and initial wealth. We show that only one parameter of the HARA (hyperbolic absolute risk aversion) utility function affects the zero-level price of a new asset. This implies that, if this parameter is fixed, the zero-level price is identical for all individuals with HARA utility functions and different levels of initial wealth. This research was partially supported by Grant NSC 95-2221-E-155-049.     

Random expected utility theory with a continuum of prizes

This note generalizes Gul and Pesendorfer’s random expected utility theory, a stochastic reformulation of von Neumann–Morgenstern expected utility theory for lotteries over a finite set of prizes, to the circumstances with a continuum of prizes. Let [0, M] denote this continuum of prizes; assume that each utility function is continuous, let \(C_0[0,M]\) be the set of all utility functions which vanish at the origin, and define a random utility function to be a finitely additive probability measure on \(C_0[0,M]\) (associated with an appropriate algebra). It is shown here that a random choice rule is mixture continuous, monotone, linear, and extreme if, and only if, the random choice rule maximizes some regular random utility function. To obtain countable additivity of the random utility function, we further restrict our consideration to those utility functions that are continuously differentiable on [0, M] and vanish at zero. With this restriction, it is shown that a random choice rule is continuous, monotone, linear, and extreme if, and only if, it maximizes some regular, countably additive random utility function. This generalization enables us to make a discussion of risk aversion in the framework of random expected utility theory.     

An analytical framework for aggregating multiattribute utility functions

This paper proposes a procedure for aggregating individual cardinal utility functions into a social utility function that represents the preferences of all the individuals as a whole. The procedure is non-interactive and is based upon the determination of the utility consensus values. This is accomplished by minimizing a distance function model that is transformed into an Archimedean goal programming problem. The procedure is applied to a general group multilinear utility function.     

Formulating an <Emphasis Type="Italic">n</Emphasis>-person noncooperative game as a tensor complementarity problem

In this paper, we consider a class of n-person noncooperative games, where the utility function of every player is given by a homogeneous polynomial defined by the payoff tensor of that player, which is a natural extension of the bimatrix game where the utility function of every player is given by a quadratic form defined by the payoff matrix of that player. We will call such a problem the multilinear game. We reformulate the multilinear game as a tensor complementarity problem, a generalization of the linear complementarity problem; and show that finding a Nash equilibrium point of the multilinear game is equivalent to finding a solution of the resulted tensor complementarity problem. Especially, we present an explicit relationship between the solutions of the multilinear game and the tensor complementarity problem, which builds a bridge between these two classes of problems. We also apply a smoothing-type algorithm to solve the resulted tensor complementarity problem and give some preliminary numerical results for solving the multilinear games.     

Dual control Monte-Carlo method for tight bounds of value function under Heston stochastic volatility model

The aim of this paper is to study the fast computation of the lower and upper bounds on the value function for utility maximization under the Heston stochastic volatility model with general utility functions. It is well known there is a closed form solution to the HJB equation for power utility due to its homothetic property. It is not possible to get closed form solution for general utilities and there is little literature on the numerical scheme to solve the HJB equation for the Heston model. In this paper we propose an efficient dual control Monte-Carlo method for computing tight lower and upper bounds of the value function. We identify a particular form of the dual control which leads to the closed form upper bound for a class of utility functions, including power, non-HARA and Yaari utilities. Finally, we perform some numerical tests to see the efficiency, accuracy, and robustness of the method. The numerical results support strongly our proposed scheme.