Millicent Chang, John Gould, Yuyun Huang, Sirimon Treepongkaruna, Joey Wenling Yang
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引用次数: 1
Abstract
We examine how algorithmic trading (AT) changes the trading environment for corporate insiders, specifically in terms of motivation to trade and timing of trade. Using SEC Form 4 insider filings and AT computed from the limit order book, we find that AT affects insiders' decisions to buy or sell, depending on whether the trades are information driven, resulting in changes in trading returns. AT reduces returns associated with routine insider sales by 0.9% of a change in AT. However being sophisticated and informed traders, insiders are able to trade strategically, leaving their purchase returns unaffected by AT. The results also show that while AT reduces information acquisition efforts in the pre-earnings announcement period, insider trades counteract this effect by releasing information to the market. Our findings reinforce the important role of insider trading in providing fundamental information and aiding price discovery, especially in an era of computerized financial markets.
期刊介绍：
The International Review of Finance (IRF) publishes high-quality research on all aspects of financial economics, including traditional areas such as asset pricing, corporate finance, market microstructure, financial intermediation and regulation, financial econometrics, financial engineering and risk management, as well as new areas such as markets and institutions of emerging market economies, especially those in the Asia-Pacific region. In addition, the Letters Section in IRF is a premium outlet of letter-length research in all fields of finance. The length of the articles in the Letters Section is limited to a maximum of eight journal pages.
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