主 题:Return Predictability and Machine Learning 主讲人:周国富(Washington University in St. Louis) 主持人:沈军(暨南大学) 时 间:2021 年 4 月 30 日(周五)10:00-11:30 会议工具:ZOOM( ID: 6607936992;密码:210430)
摘 要:
The seminar presents two projects. The first is to provide a comprehensive analysis of the information content from options markets for predicting the cross-section of stock returns, and show why existing factors fail to pricing assets adequately. The second proposes an employee sentiment index, which complements investor sentiment and manager sentiment indices, and finds that high employee sentiment predicts a subsequent low market return. The economic driving force of the predictability is distinct from those of investor sentiment and manager sentiment: high employee sentiment leads to high contemporaneous wage growth due to immobility, which in turn results in subsequently lower firm cash flow and lower stock return.
★主讲人简介★
周国富,现任圣路易斯华盛顿大学奥林商学院 Frederick Bierman and James E. Spears 金融学教授,曾分别于成都理工大学获得理学学士学位和杜克大学经济学获得博士学位。读博之前他对数学很感兴趣,在数论、函数论和偏微分方程数值解等领域发表了研究成果。博士毕业后,从1990年开始,周教授一直任教于华盛顿大学,研究领域涵盖资产定价的多个领域,已在 JF, JFE, RFS, JFQA 等金融类国际权威期刊上发表论文30余篇,并多次因 MBA, MSF 教学及研究成果优异而获奖。
周教授目前的研究兴趣主要是大数据和机器学习在金融领域的创新应用。他最新的文章(与合著者)包括探索因素模型的局限和扩展,构建宏观因素、趋势因素、彩票因素和信息因素来解释横截面的股票回报和公司债券回报,并提出组合套索法,以选择最优的公司特征来预测预期资产收益。
(支持单位:暨南大学南方高等金融研究院)
|