【主题】Factor models for asset returns based on transformed factors

【报告人】Jialiang Li , 副教授

National University of Singapore

【时间】 2019年7月5日（星期五）09:30-10:30

【地点】上海财经大学统计与管理学院大楼1208会议室

【摘要】The Fama–French three factor models are commonly used in the description of asset returns in finance. Statistically speaking, the Fama–French three factor models imply that the return of an asset can be accounted for directly by the Fama–French three factors, i.e. market, size and value factor, through a linear function. A natural question is: would some kind of transformed Fama–French three factors work better? If so, what kind of transformation should be imposed on each factor in order to make the transformed three factors better account for asset returns? In this paper, we are going to address these questions through nonparametric modelling. We propose a data driven approach to construct the transformation for each factor concerned. A generalised maximum likelihood ratio based hypothesis test is also proposed to test whether transformations on the Fama–French three factors are needed for a given data set. Asymptotic properties are established to justify the proposed methods. Extensive simulation studies are conducted to show how the proposed methods perform with finite sample size. Finally, we apply the proposed methods to a real data set, which leads to some interesting findings.

【嘉宾简介】栗家量博士于中国科学技术大学获得统计学学士学位，于美国威斯康星大学获得公共健康学硕十学位与统计学博士学位。现在任职于新加坡国立大学统计与应用概率系副教授。栗博士已发表论文120余篇，其中包括Annals of Statistics, JASA, Biometrics等统计学顶级杂志。栗博士著有一本Chapman&Hall CRC Press出版的专著Survival Analysis in Medicine and Genetics.根据Google Scholar上面今年的最新数据，他的引用量超过2000.他的h-index为25.栗博士担当过Biometrics与Lifetime Data Analysis等统计学杂志的副主编。栗家量曾在新加坡作为principal investigator主持了多个国家支持的研究项目。

【主持人】黄涛