This paper documents that speed is crucially important for high frequency trading strategies based on U.S. macroeconomic news releases. Using order level data of the highly liquid S&P500 ETF traded on NASDAQ from January 6, 2009, to December 12, 2011, we find that a delay of 300 milliseconds (1...

In this study, we investigate ordering patterns of different types of market participants in Tokyo Stock Exchange (TSE) by examining order records of the listed stocks. Firstly, we categorize the virtual servers in the trading system of TSE, each of which is linked to a single trading...

We develop a two period model of trade where a common value asset is traded against a numeraire in two parallel markets. An insider who knows the final value of the asset exploits his private information in both markets. Some traders, called high frequency (HF) traders, observe the total orders...

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...

Liquidity suppliers lean against the wind. We analyze whether high-frequency traders (HFTs) lean against large institutional orders that execute through a series of child orders. The alternative is HFTs trading "with the wind," that is, in the same direction. We find that HFTs initially lean...

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,...

We analyze price discovery dynamics for Canadian companies cross-listed on the NYSE from January 2004 to January 2011. We employ a structural vector autoregression to assess the interactions between price discovery, liquidity and algorithmic trading activity. We observe that over time, the U.S....

We investigate the effects of algorithmic trading and dark venues on U.S. security market quality. Market quality refers to the nearly universal mandate of securities regulators to ensure that all market design changes should not detract from efficiency or fairness which we define as less market...

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,...