Department of Finance, University of Melbourne, Melbourne, 3010, Australia.
Sci Data. 2023 Apr 26;10(1):237. doi: 10.1038/s41597-023-02147-6.
This paper describes a dataset capturing insider trading activity at publicly traded companies. Investors and investment analysts demand this information because executives, directors and large shareholders are expected to have more intimate knowledge of their company's prospects than outsiders. Insider stock sales and purchases may reveal information about the firm's business not disclosed in financial statements. They may also convey new information predictive of stock price movements if insiders can better interpret public information about the firm. Since mid-2003, the Securities and Exchange Commission has made these insider trading reports available to the public in a structured format; however, most academic papers use proprietary commercial databases instead of regulatory filings directly. This makes replication challenging as the data manipulation and aggregation processes are opaque and historical records could be altered by the database provider over time. To overcome these limitations, the presented dataset is created from original regulatory filings; it is updated daily and includes all information reported by insiders without alteration.
本文档描述了一个捕获上市公司内幕交易活动的数据集。投资者和投资分析师需要这些信息，因为高管、董事和大股东对公司前景的了解预计比外部人士更深入。内幕股票买卖可能会揭示财务报表中未披露的有关公司业务的信息。如果内部人士能够更好地解释有关公司的公开信息，它们也可能传达有关股票价格走势的新信息。自 2003 年年中以来，美国证券交易委员会 (SEC) 已以结构化格式向公众提供这些内幕交易报告；然而，大多数学术论文使用专有的商业数据库，而不是直接使用监管备案文件。这使得复制变得具有挑战性，因为数据处理和聚合过程不透明，并且历史记录可能会随着时间的推移而被数据库提供商更改。为了克服这些限制，本文档创建的数据集是从原始监管备案文件中创建的；它每天更新，包括内部人士报告的所有信息，没有任何更改。
