报告题目：Detecting Insider Trading in the Era of Big Data and Machine Learning
报告人：张麒，上海交通大学安泰经济管理学院金融学副教授、博士生导师
时间：11.01星期五（14：00 – 15：30）
地点：新主楼 A618
讲座系列： 融 实
摘要:
Reliably detecting insider trading is a major impediment to both research and regulatory practice. Using account-level transaction data, we propose a novel approach. Specifically, after extracting several key empirical features of typical insider trading cases from existing regulatory actions, we employ a machine learning methodology to identify suspicious insiders across our full sample. Our identified outliers, on average, earn a significantly higher return and use more limit orders relative to a random sample. Further, we find that the trading patterns of selected suspicious insiders exhibit similarities with the changes in a firm’s central decision-makers. We also find that identified outliers are more likely to use multiple accounts to trade around a major information event and have superior performance around earnings announcement events of the same firms. Our approach significantly augments an otherwise elusive ability to detect insider trading.
汇报人简介：
张麒，上海交通大学安泰经济管理学院金融学副教授，博士生导师。曾任教于英国利兹大学和杜伦大学。于2003年和2006年在清华大学经济管理学院获得经济学学士和硕士学位，并于2011年在利兹大学获得金融学博士学位。主要研究领域为金融市场、资产定价、行为金融和银行学。学术研究发表于Review of Financial Studies, Journal of Accounting and Economics, Journal of Financial and Quantitative Analysis 等期刊。曾获得2017、2019、2022年中国金融研究年会最佳论文奖。2022年入选上海市领军人才。
