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[10月15日] 计量金融与大数据分析workshop

发布日期:2021-10-11 09:28    来源:

时间:20211015日(周五)10:00 AM -- 11:30 AM

主讲人:陈齐辉(香港中文大学(深圳))

题目:Semiparametric Conditional Factor Models: Estimation and Inference (with Nikolai Roussanov and Xiaoliang Wang) (半参数条件因子模型:估计和推断)

地点:经院107

主持人:(国发院)沈艳、黄卓、孙振庭、张俊妮

              (北大新结构经济学研究院)胡博

              (经济学院)王一鸣、王熙、刘蕴霆、王法

报告摘This paper introduces a simple and tractable sieve estimation for semiparametric conditional factor models, and develops a simple bootstrap procedure for inference on nullity of intercept function and linearity of intercept and factor loadings functions. We establish large-$N$-asymptotic properties of the estimators and the tests without requiring large $T$. We additionally provide two consistent estimators for the number of factors.  The results enable us to estimate conditional (dynamic) behavior of a large set of individual assets from a number of characteristics exhibiting nonlinearity without the need to pre-specify factors, while allowing us to disentangle the alpha versus beta explanations. We apply the methods to explain the cross-sectional differences of individual stock returns in the US market, and find strong evidence of nonzero pricing error and nonlinearity in both alpha and beta functions.

主讲人简介:

陈齐辉:香港中文大学(深圳)经管学院助理教授,加利福尼亚大学圣地亚哥分校经济学博士,新加坡管理大学经济学硕士,厦门大学经济学学士和硕士,以及厦门大学数学学士,近年来从事计量经济学理论和应用计量经济学的研究。