This paper develops a continuous-time model to study the widely used investment mandates in the institutional asset management industry. In this paper, just like He and Xiong (2013), we suppose that the asset management industry has a two-layered incentive structure, and fund families charging investors fixed management fees while compensating individual fund managers based on fund performance. Different from He and Xiong (2013), we suppose that the fund family aims to select an optimal incentive strategy to maximize its terminal benefits, while the fund manager needs to select the optimal effort level and the optimal investment portfolio to maximize his terminal net discounted compensation in a continuous-time model. By using dynamic programming principle and stochastic differential game theory, the optimal strategies and value functions of both sides are derived. At last, numerical studies are provided to illustrate the effects of all the parameters on the optimal strategies. The result reveals that the optimal incentive mechanism will redistribute both the benefit of the fund families and the cost of the fund managers’ effort.

中文翻译：

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委托资产管理问题的连续时间版本

本文建立了一个连续时间模型来研究机构资产管理行业中广泛使用的投资指令。在本文中，就像He和Xiong（2013）一样，我们假设资产管理行业具有两层激励结构，基金家族向投资者收取固定的管理费，同时根据基金绩效补偿个别基金经理。与He and Xiong（2013）不同，我们假设基金家族旨在选择最佳激励策略以最大化其最终收益，而基金经理则需要选择最佳努力水平和最优投资组合以最大化其最终净贴现率。连续时间模型中的补偿。利用动态规划原理和随机微分博弈理论，推导出双方的最优策略和价值函数。最后，通过数值研究说明了所有参数对最优策略的影响。结果表明，最优激励机制将重新分配基金家族的利益和基金经理的工作成本。