时 间：2024年4月29日 10:30-12:00
地 点：普陀校区理科大楼A1114
报告人：冯冠豪 香港城市大学 助理教授
主持人：周迎春 华东师范大学教授
摘 要：
In empirical asset pricing, traded candidate factors can be either on the left- or right-hand side of the factor model as an anomaly or true risk factor, because anomalies should be explained by the set of risk factors with zero intercepts --- pricing errors. This unsupervised factor selection is a new statistical problem that cannot be answered by existing model selection studies that rely on test assets. This paper proposes a stepwise evaluation framework that sequentially separates a small set of risk factors from a large number of anomalies, resulting in a robust selection of true factors without (or with) test assets. With the statistical guarantee of selection consistency, our method utilizes the asset pricing duality between the minimal GRS statistic and the maximal Sharpe ratio when approximating the stochastic discount factor. Empirically, we find that seven selected factors can explain the remaining cross section of anomalies, along with exceptional factor investment performance.
报告人简介：
冯冠豪是香港城市大学商业统计的助理教授，他同时是金融科技实验室(HKAIFT)研究员。他2017年从芝加哥大学博士毕业，研究领域包括贝叶斯统计，实证资产定价，机器学习，和时变计量经济学。他已在国际顶刊Journal of Finance，Journal of Financial and Quantitative Analysis，Journal of Econometrics和International Economic Review发表论文，主持香港研资局ECS和GRF基金项目，以及国家自然科学基金青年项目。冯博士也曾多次获业界研究奖，包括AQR Insight Award一等奖，Crowell Prize二等奖，PwC 3535论坛年度最佳论文，INQUIRE Europe，香港货币及金融研究中心等。