一、 主题：A Comparison of Factor Models in China 

二、 汇报人：王瑾喆 2021级金融工程直博生 

三、 时间地点：2024年4月29日下午14：30，沙河校区3号楼302会议室 

四、 报告简介：随着大数据、云计算、人工智能和区块链等新兴技术的蓬勃发展，金融和会计领域的研究内容和研究方法都在发生巨大变化。为了进一步推动中国智能金融与会计研究的发展，同时为学者提供一个交流平台，促进理论创新和实践创新，2024年（第二届）中国智能金融与会计国际会议由合肥工业大学经济学院联合国际知名金融与会计学期刊《Journal of Accounting Literature》于2024年4月19-21日在合肥工业大学宣城校区举办。我司博士研究生王瑾喆与朱一峰副教授合作的论文《A Comparison of Factor Models in China》经过评审应邀参会。王瑾喆同学将在校内就该参会论文做出学术报告。 

五、 报告摘要：We apply various test portfolios and alternative statistical methodologies to evaluate the performance of eleven asset pricing models. To compile the test portfolios, we construct 105 anomalies in China and apply the 23 significant anomalies as test assets for model comparison. The results indicate that in the time-series test and anomalies explanation, the Hou et al. (2019) five-factor q model exhibits the best overall performance. The pairwise cross-sectional s and the multiple model comparison tests affirm that the Hou et al. (2019) five-factor q model, the Fama and French (2018) six-factor (FF6) model and the Kelly et al. (2019) five-factor Instrumented Principal Component Analysis (IPCA5) model stand out as the top performers. Notably, the performance of the five-factor q model is insensitive to variations in experimental design.

撰稿：王瑾喆

初审：位锦

终审：魏旭