Does Algorithmic Trading Improve Liquidity?

• 成果类型: Article
• 署名作者: Hendershott, Terrence; Jones, Charles M.; Menkveld, Albert J.
• 署名单位: University of California System; University of California Berkeley; Columbia University; Vrije Universiteit Amsterdam
• 刊物名称: JOURNAL OF FINANCE
• ISSN/ISSBN: 0022-1082
• DOI: 10.1111/j.1540-6261.2010.01624.x
• 发表日期: 2011
• 页码: 1-33
• 关键词: panel-data; INFORMATION; BEHAVIOR; components; MARKET

摘要

Algorithmic trading (AT) has increased sharply over the past decade. Does it improve market quality, and should it be encouraged? We provide the first analysis of this question. The New York Stock Exchange automated quote dissemination in 2003, and we use this change in market structure that increases AT as an exogenous instrument to measure the causal effect of AT on liquidity. For large stocks in particular, AT narrows spreads, reduces adverse selection, and reduces trade-related price discovery. The findings indicate that AT improves liquidity and enhances the informativeness of quotes.