The Causal impact of algorithmic trading on market quality

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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

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