We study the intra-day impact of algorithmic trading on the futures market to increase our understanding of algorithmic trading and its role in the price formation process. First, we find that algorithmic trading provides liquidity when the spread is wide and that algorithms enter the market at...

Two important characteristics of current equity markets are the large number of competing trading venues with publicly displayed order books and the substantial fraction of dark trading, which takes place outside such visible order books. This paper evaluates the impact on liquidity of dark...

Two important characteristics of current equity markets are the large number of competing trading venues with publicly displayed order books and the substantial fraction of dark trading, which takes place outside such visible order books. This paper evaluates the impact on liquidity of dark...

We investigate whether market makers with inventory concerns are compensated with subsequent monthly returns in the cross-section. We find a significant negative relation between order flows and monthly returns, “the order flow effect”, suggesting that market makers lower prices for stocks...

We develop a new likelihood-based approach to sign trades in the absence of quotes. It is equally efficient as existing MCMC methods, but more than 10 times faster. It can deal with the occurrence of multiple trades at the same time, and noisily observed trade times. We apply this method to a...

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 use a comprehensive panel of NYSE order book data to show that the liquidity and quoting efficiency improvements associated with algorithmic trading (AT) are attributable to enhanced monitoring by liquidity providers. We find that variation in liquidity provider monitoring uniquely explains...

This paper aims to analyze the dynamics of information asymmetry in market microstructure through the Easley et al. (2002)'s PIN framework in two segments. Firstly, we test to see if factors such as size, value and illiquidity can be used to explain PIN. Secondly, we extend beyond the...

This paper combines dimensional analysis, leverage neutrality, and a principle of market microstructure invariance to derive scaling laws expressing transaction costs functions, bid-ask spreads, bet sizes, number of bets, and other financial variables in terms of dollar trading volume and...