Algorithmic trading has sharply increased over the past decade. Equity market liquidity has improved as well. Are the two trends related? For a recent five-year panel of New York Stock Exchange (NYSE) stocks, we use a normalized measure of electronic message traffic (order submissions,...

Using the adoption of the Arrowhead trading platform in January 2010 as an exogenous event, we investigate the effects of algorithmic trading on stock market liquidity and commonality in liquidity under different market conditions on the Tokyo Stock Exchange. After controlling for endogeneity,...

Using the adoption of the Arrowhead trading platform in January 2010 as an exogenous event, we investigate the effects of algorithmic trading on stock market liquidity and commonality in liquidity under different market conditions on the Tokyo Stock Exchange. After controlling for endogeneity,...

This paper examines unique data on dark pool activity for a large cross-section of US stocks in 2009. Dark pool activity is concentrated in liquid stocks. Nasdaq (AMEX) stocks have significantly higher (lower) dark pool activity than NYSE stocks controlling for liquidity. For a given stock, dark...

We develop a model of limit order trading in which some traders have better information on future price volatility. As limit orders have option-like features, this information is valuable for limit order traders. We solve for informed and uninformed limit order traders' bidding strategies in...

Abstract I demonstrate an important tension between acquiring information and incorporating it into asset prices. As a salient case, I analyze the rise of algorithmic trading (AT), which is typically associated with improved price efficiency. Using a new measure of the information content of...

We analyze the impact of high frequency (HF) trading in financial markets based on a model with three types of traders: liquidity traders (LTs), professional traders (PTs), and high frequency traders (HFTs). Our four main findings are: i) The price impact of liquidity trades is higher in the...

We analyze the impact of high frequency (HF) trading in financial markets based on a model with three types of traders: liquidity traders (LTs), professional traders (PTs), and high frequency traders (HFTs). Our four main findings are: i) The price impact of liquidity trades is higher in the...

This paper examines the role of algorithmic trading in modern financial markets. Additionally, order types, characteristics, and special features of algorithmic trading are described under the lens provided by the large development of high frequency trading technology. Special order types are...

We show that the excessive use of hidden orders causes artificial price pressures and abnormal asset returns. Using a simple game-theoretical setting, we demonstrate that this effect naturally arises from mis-coordination in trading schedules between traders, when suppliers of liquidity do not...