Algorithms enable investors to locate trading opportunities, which raises gains from trade. Algorithmic traders can also process information on stock values before slow traders, which generates adverse selection. We model trading in this context and show that, for a given level of algorithmic...

This paper presents the most extensive analysis of liquidity in the German equity market so far. We examine the evolution of liquidity over time, the determinants of liquidity, and commonality across liquidity measures and countries. We make use of a new publicly available dataset, the Market...

This paper investigates the importance of speed for technical trading rule performance for three highly liquid ETFs listed on NASDAQ over the period January 6, 2009 up to September 30, 2009. In addition we examine the characteristics of market activity over the day and within subperiods...

This paper examines how individual investors' participation in short sale affects the efficiency of stock pricing using a unique regulatory change in Korea. The change enables individual investors to sell short some -- but not all -- domestic stocks, without affecting the short-selling ability...

The High Frequency Trading evolution underlines three keys questions: -How High Frequency traders could improve risk management tools to manage operational risks (algorithm issues) and market risks (price manipulation, liquidity and volatility)?-How stocks markets (and brokers-dealers) could...

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...

Taking advantage of a trades-and-quotes high-frequency database, we document the main stylized facts and dynamic properties of spot precious metals, i.e. gold, silver, palladium, and platinum. We analyze the behaviors of spot prices, returns, volume, and selected liquidity measures. We find...

We develop spectral volume models to systematically estimate, explain, and exploit the high-frequency periodicity in intraday trading activities using Fourier analysis. The framework consistently recovers periodicities at specific frequencies in three steps, despite their low signal-to-noise...