喻园管理论坛2023年第26期(总第849期)

演讲主题: Uncommon Factors for Bayesian Asset Clusters

主 讲 人: 冯冠豪，香港城市大学商学院助理教授

主 持 人: 李安泰，管理学院财务金融系讲师

活动时间: 2023年4月25日（周二）15:00-16:30

活动地点: 管理大楼110教室

主讲人简介：

冯冠豪是香港城市大学商业统计的助理教授，他同时是商业数据分析硕士项目主任和金融科技实验室(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，和金融科技。他已在Journal of Finance和Journal of Econometrics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。

活动简介：

Asset returns exhibit grouped heterogeneity, and a “one-size-fits-all” model has been elusive empirically. This paper proposes a Bayesian Clustering Model (BCM) combining Bayesian factor selection and panel tree for asset clustering. The Bayesian model marginal likelihood guides the tree growth for clustering assets, where each leaf cluster fits heterogeneous model selection and estimation. We apply BCM to split the cross section of U.S. individual stock returns, and find MktRF, SMB, and STR (short-term reversal) as common factors. We also identify several uncommon factors that are partially useful to some leaf clusters when splitting the cross section. The tree visualizes individual stock clustering with important splitting characteristics, such as stock variance and market equity. By considering different prior beliefs for factor usefulness, we further discover that factor models with more skeptic beliefs produce more accurate interval coverage. Beyond asset pricing, our framework generally applies to modeling grouped heterogeneity through jointly clustering panel data and variable selection.

【备注：讲座时间有变，原定活动时间为10:00-11:30，请以最新时间为准】