Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market

• 成果类型: Article
• 署名作者: Chaboud, Alain P.; Chiquoine, Benjamin; Hjalmarsson, Erik; Vega, Clara
• 署名单位: Federal Reserve System - USA; Federal Reserve System Board of Governors; University of Gothenburg; University of London
• 刊物名称: JOURNAL OF FINANCE
• ISSN/ISSBN: 0022-1082
• DOI: 10.1111/jofi.12186
• 发表日期: 2014
• 页码: 2045-2084
• 关键词: monetary-policy

摘要

We study the impact of algorithmic trading (AT) in the foreign exchange market using a long time series of high-frequency data that identify computer-generated trading activity. We find that AT causes an improvement in two measures of price efficiency: the frequency of triangular arbitrage opportunities and the autocorrelation of high-frequency returns. We show that the reduction in arbitrage opportunities is associated primarily with computers taking liquidity. This result is consistent with the view that AT improves informational efficiency by speeding up price discovery, but that it may also impose higher adverse selection costs on slower traders. In contrast, the reduction in the autocorrelation of returns owes more to the algorithmic provision of liquidity. We also find evidence consistent with the strategies of algorithmic traders being highly correlated. This correlation, however, does not appear to cause a degradation in market quality, at least not on average.