The Causal impact of algorithmic trading on market quality

dc.contributor.author	Aggarwal, Nidhi
dc.contributor.author	Thomas, Susan
dc.date.accessioned	2015-08-14T10:21:12Z
dc.date.available	2015-08-14T10:21:12Z
dc.date.issued	2014-07
dc.identifier.uri	http://hdl.handle.net/2275/323
dc.description.abstract	The causal impact of algorithmic trading on market quality has been difficult to establish due to endogeneity bias. We address this problem by using the introduction of co-location, an exogenous event after which algorithmic trading is known to increase. Matching procedures are used to identify a matched set of firms and set of dates that are used in a difference-in-difference regression to estimate causal impact. We find that securities with higher algorithmic trading have lower liquidity costs, order imbalance, and order volatility. There is new evidence that higher algorithmic trading leads to lower intraday liquidity risk and a lower incidence of extreme intraday price movements.	en_US
dc.language.iso	en	en_US
dc.relation.ispartofseries	WP;WP-2014-023
dc.subject	Electronic limit order book markets	en_US
dc.subject	matching	en_US
dc.subject	difference-in-difference	en_US
dc.subject	efficiency	en_US
dc.subject	liquidity	en_US
dc.subject	volatility	en_US
dc.subject	flash crashes	en_US
dc.title	The Causal impact of algorithmic trading on market quality	en_US
dc.type	Working Paper	en_US