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Does Algorithmic Trading Improve Liquidity?
Author(s) -
HENDERSHOTT TERRENCE,
JONES CHARLES M.,
MENKVELD ALBERT J.
Publication year - 2011
Publication title -
the journal of finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 18.151
H-Index - 299
eISSN - 1540-6261
pISSN - 0022-1082
DOI - 10.1111/j.1540-6261.2010.01624.x
Subject(s) - market liquidity , price discovery , dark liquidity , adverse selection , algorithmic trading , high frequency trading , flash trading , stock exchange , monetary economics , market maker , financial economics , business , economics , quality (philosophy) , measure (data warehouse) , stock (firearms) , stock market , computer science , actuarial science , finance , data mining , futures contract , horse , engineering , biology , paleontology , mechanical engineering , philosophy , epistemology
ABSTRACT 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.