基于心理契约的基金经理激励机制分类设计

发布时间：2019-03-31 16:48

【摘要】：已有的基金经理激励机制研究多假定激励对象的心理和需求是同质的,忽视了对基金经理异质性特征的分析。这与实际的经济活动并不相符合。本文通过建立数学模型,将心理契约理论引入基金经理激励问题研究。结果表明,在信息对称条件下,即基金经理的不同心理需求能够被辨别时,应依据其心理契约类型,分类设计激励机制;在信息非对称条件下,即基金经理的不同心理需求无法被辨别时,应依据基金经理特征,如风险厌恶程度、工作成本、投资能力,及其所管理基金的风险大小和外部市场环境的变化方向,分类设计激励机制。并且,在多代理人环境下,基金经理间的合作程度也将对激励机制设计产生影响。本研究不仅是对已有基金经理激励机制研究的拓展与完善,使之更接近现实,也从心理契约视角为解决基金经理激励问题提供了新思路。
[Abstract]:The existing research on incentive mechanism of fund managers mostly assumes that the psychology and demand of incentive objects are homogeneous and neglects the analysis of the heterogeneity characteristics of fund managers. This is not in line with actual economic activity. In this paper, the theory of psychological contract is introduced into the study of incentive problem of fund managers by establishing a mathematical model. The results show that under the condition of information symmetry, that is, when the different psychological needs of fund managers can be identified, the incentive mechanism should be designed according to their psychological contract types. Under the condition of asymmetric information, that is, when the different psychological needs of fund managers cannot be distinguished, they should be based on the characteristics of fund managers, such as risk aversion degree, work cost, and investment ability. The risk of the fund and the change direction of the external market environment, classified design incentive mechanism. Moreover, in the multi-agent environment, the level of cooperation among fund managers will also have an impact on the design of incentive mechanism. This research not only expands and consummates the existing research on incentive mechanism of fund manager, makes it closer to reality, but also provides a new way of thinking for solving the incentive problem of fund manager from the perspective of psychological contract.
【作者单位】：东北大学工商管理学院;
【基金】：国家自然科学基金项目(70871022) 中国博士后科学基金项目(20090461188) 教育部博士点(新教师)基金项目(20100042120020),教育部人文社科基金项目(10YJC790253) 中央高校基本科研业务费专项资金资助(N090306003)
【分类号】：F830.91

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