讲座主题：A New Method for EstimatingSharpe Ratio Function via Local Maximum Likelihood

报告人：林红梅（上海对外经贸大学科研处副处长）

时间：2022年11月16日上午09：00-11：30

线上会议：腾讯会议号：180-246-291

报告人简介：林红梅，上海对外经贸大学副教授，硕士生导师，科研处副处长。2016年在华东师范大学获得统计学博士学位，主要从事非参半参回归分析、纵向数据分析、函数型数据分析以及分布式统计方法等相关内容的研究，在<Journal ofMultivariate Analysis>、<Computational Statisticsand Data Analysis>等国内外知名学术期刊已发表SCI检索论文二十余篇。主持国家自然科学基金面上项目、青年基金项目各1项，上海市自然科学基金面上项目1项，教育部重点实验室项目1项。

内容摘要：The Sharpe ratio function isa commonly used risk/return measure in financial econometrics. To estimate thisfunction, most existing methods take a two-step procedure that first estimatesthe mean and volatility functions separately and then applies the plug-inmethod. In this paper, we propose a direct local maximum likelihood method tosimultaneously estimate the Sharpe ratio function and the negative log-volatilityfunction or their derivatives. We establish the joint limiting distribution ofthe proposed estimators, and we further extend the proposed method to estimatethe multivariate Sharpe ratio function and establish its asymptotic normality.We evaluate the numerical performance of the proposed estimators throughsimulation studies, and compare them with existing methods. Finally, we applythe proposed method to analyze the three-month US Treasury bill interest ratedatasets and capture a well-known covariate-dependent effect on the Sharperatio.