科学研究
报告题目：Measuring Firm Quality Using Machine Learning
报告人：柯滨
报告时间：2021年10月18日（周一）10:00
报告地点：腾讯会议
主办单位：东北财经大学会计学院
【报告摘要】
This study uses machine learning to construct a measure of firm quality based on fundamental analysis. Traditional fundamental analysis in the accounting and finance literature typically uses simple heuristics to construct firm quality based on multiple fundamental ratios. In contrast, this study uses machine learning to determine the optimal relationships between firm quality and fundamental ratios. We show that our machine learning model outperforms a benchmark model from the recent accounting literature in predicting firm quality. We also find that the surprise component of the machine learning-based firm quality can predict abnormal return.
【报告人简介】
柯滨，自2015年起担任新加坡国立大学商学院会计学教授兼教务长，教育部“长江学者”讲座教授，曾任北美华人会计教授会（CAPANA）会长。近期主要关注新兴市场（尤其是中国）的财务报告、管理层激励和投资者保护等问题。他的研究成果发表在各大顶级会计学术期刊，包括The Accounting Review、Journal of Accounting and Economics、Journal of Accounting Research、Review of Accounting Studies、Contemporary Accounting Research等。柯教授担任China Journal of Accounting Research的顾问编辑，Journal of American Taxation Association、The Accounting Review、The International Journal of Accounting的现任或前任编委会成员。曾任The Accounting Review编辑（2011.6-2014.5）。
