基于可信性分布的投资组合问题的一种混合智能方法

研究了模糊环境下基于效用函数的有效资产投资组合的收益率模型,模型建立在可信性分布的基础上,而不是概率分布或可能性分布基础上.给出模糊环境下基于可信性分布的n种资产的最优投资组合问题的混合智能算法以寻找某种效用函数意义下的最优组合.并以实例仿真说明该方法的有效性.     

Stochastic optimal budget decision for advertising considering uncertain sales responses

Firms are faced with uncertain sales responses even though they advertise appropriately. To help marketing managers make optimal budget decisions in this situation, we develop a stochastic model, depicting the problem of advertising budget decision as a special Markov decision process where a new objective, maximizing expected market utility, is proposed. In the model we introduce a two-dimension state variable including accumulative sales, which vary randomly with advertising budget, and the predicted probability that an advertising campaign obtains a full sales response. We make an analysis of the model on the premise of growing infinite market potential, deriving the property of optimal policies and that of optimal value function. These results are successfully used to make advertising budget decisions for a private university in Xi’an, China.     

Ordering fuzzy sets over the real line: An approach based on decision making under uncertainty

The ordering of fuzzy sets over the real line is approached from the point of view of ordering intervals rather than ordering numbers. First, the maximax and maximin criteria which are commonly used for ordering intervals are expressed in terms of characteristic functions. These criteria and the Hurwicz criterion for decision making under complete ignorance are then reformulated in a manner that allows for their generalization to the fuzzy case. Transitivity is established for these ordering rules. A criterion based on the principle of diminishing marginal utility is also presented.     

Portfolio theory for the recourse certainty equivalent maximizing investor

The portfolio selection problem with one safe andn risky assets is analyzed via a new decision theoretic criterion based on the Recourse Certainty Equivalent (RCE). Fundamental results in portfolio theory, previously studied under the Expected Utility criterion (EU), such as separation theorems, comparative static analysis, and threshold values for inclusion or exclusion of risky assets in the optimal portfolio, are obtained here. In contrast to the EU model, our results for the RCE maximizing investor do not impose restrictions on either the utility function or the underlying probability laws. We also derive a dual portfolio selection problem and provide it with a concrete economic interpretation.Research partly supported by ONR Contracts N0014-81-C-0236 and N00014-82-K-0295, and NSF Grant SES-8408134 with the Center for Cybernetic Studies, The University of Texas at Austin.Partly supported by NSF Grant DDM-8896112.Partly supported by AFOSR Grant 0218-88 and NSF Grant ECS-8802239 at the University of Maryland, Baltimore Campus.     

效用函数理论及其应用研究

分析了效用函数理论,提出了图书效用函数,并分析其性质.得出图书最大效用化的约束条件.指导图书馆文献资源建设.     

信息产品在非线性效用函数下的二度价格歧视研究

本中假定消费的效用函数为非线性的效用函数，垄断厂商提供同一种信息产品的两种质量版本，消费根据两类约束做出自己的消费选择。厂商通过消费的两个无差异点来对消费进行二度价格歧视，通过分析我们得出厂商的歧视条件。     

农民科技培训的博弈分析

本构造了一个对农民进行培训的博弈论模型。分析了农民对于普通的农业科技培训和专门培训选择的可能性，并且讨论了家庭收入对于农民参加科技培训积极性的影响。指出为了迅速提高农村劳动力的素质，国家应加大对培训的投入，制定相应的激励机制。     

A new existence result for second-order BSDEs with quadratic growth and their applications

In this paper, we study a class of second-order backward stochastic differential equations with quadratic growth in coefficients. In particular, we provide an existence result for these equations and give their applications by solving robust utility maximization problems and introducing a type of nonlinear evaluations.     

高校收费和招生改革的社会影响的博弈模型分析

针对我国高校近年来不断扩大招生规模,提高收费标准等一系列改革举措,本文用微观经济分析的方法,通过建立相应的博弈模型,具体分析了这一系列改革对学生的影响.主要结论一是高校扩招(或提高学费)增大了学生读书的机会成本,同时降低了读书的效用,但只要学生读书的效用严格大于不读的效用,高校就有动力扩大招生或提高学费);二是扩招和提高学费对学生的影响具有动态相对性,其影响力的大小与现阶段二者的相对水平有关;三是在一定条件下扩大招生规模尤其是提高收费水平会使经济条件不同的学生在是否深造和是否选择名校或热门专业上作出完全不同的抉择,产生了教育公平问题.此外还得到了关于高校改革对其自身收益影响的一些结论.     

Functional ANOVA,ultramodularity and monotonicity: Applications in multiattribute utility theory

Utility function properties as monotonicity and concavity play a fundamental role in reflecting a decision-maker’s preference structure. These properties are usually characterized via partial derivatives. However, elicitation methods do not necessarily lead to twice-differentiable utility functions. Furthermore, while in a single-attribute context concavity fully reflects risk aversion, in multiattribute problems such correspondence is not one-to-one. We show that Tsetlin and Winkler’s multivariate risk attitudes imply ultramodularity of the utility function. We demonstrate that geometric properties of a multivariate utility function can be successfully studied by utilizing an integral function expansion (functional ANOVA). The necessary and sufficient conditions under which monotonicity and/or ultramodularity of single-attribute functions imply the monotonicity and/or ultramodularity of the corresponding multiattribute function under additive, preferential and mutual utility independence are then established without reliance on the utility function differentiability. We also investigate the relationship between the presence of interactions among the attributes of a multiattribute utility function and the decision-maker’s multivariate risk attitudes.