Optimal Investment Strategy for α-Robust Utility Maximization Problem

报告摘要：In reality, investors are uncertain about the dynamics of risky asset returns. Therefore, investors prefer to make robust investment decisions. In this paper, we propose an α-robust utility maximization problem under uncertain parameters. The investor is allowed to invest in a financial market consisting of a risk-free asset and a risky asset. The uncertainty about the expected return rate is parameterized by a nonempty set. Different from most existing literature on robust utility maximization problems where investors are generally assumed to be extremely ambiguity averse because they tend to consider only expected utility in the worst-case scenario, we pay attention to the investors who are not only ambiguity averse but also ambiguity seeking. Under power utility, we provide the implicit function representations for the precommitted strategy, equilibrium strategy of the open-loop type, and equilibrium strategy of the closed-loop type. Some properties about the optimal trading strategies, the best-case and worst-case parameters under three different kinds of strategies, are provided.

报告人简介：李丹萍，华东师范大学统计学院教授，2017年博士毕业于bat365正版唯一官网，加拿大滑铁卢大学博士后，2018年入选上海市晨光计划。目前担任中国优选法统筹法与经济数学研究会量化金融与保险分会副秘书长、中国运筹学会金融工程与金融风险管理分会理事等。研究方向为保险精算、金融工程、金融数学。在Mathematical Finance、Mathematics of Operations Research、Journal of Economic Dynamics and Control、Insurance: Mathematics and Economics、Scandinavian Actuarial Journal、SIAM Journal on Financial Mathematics等国内外重要学术期刊上发表学术论文40余篇，出版学术专著1部。主持2项国家自然科学基金项目，1项上海市哲学社会科学项目，曾荣获天津市优秀博士学位论文、教育部第八届高等学校科学研究优秀成果（人文社会科学）二等奖（排名2，通讯作者）等奖项。