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 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...

In this paper, we introduce a Transactionally Efficient Market Model, which evolves from the standard efficient market model, encompassing both transaction costs and bid-ask prices. Hence, we delve into how arbitrage makes its way within this complex setting. The main outgrowth of the analysis...

We propose a state-space modeling approach for decomposing trading volume into its liquidity-driven and information-driven components. Using a set of high-frequency S&P 500 stock data, we show that informed trading is linked with a reduction in volatility, illiquidity, and toxicity/adverse...

In this paper, we explore the link between culture, measured by collectivism, and commonality in liquidity for 51 countries over the period 1985 to 2012. We provide evidence that commonality in liquidity is higher for stocks that trade in collectivist countries, after controlling for supply-side...

This paper investigates the information content present in the quotes in an order driven market without the presence of designated market makers. A representation is proposed that recognises the ability of participants in such markets to observe market events and calibrate their quoting...

The Probability of Informed Trading (PIN) is a widely used indicator of information asymmetry risk in the trading of securities. Its estimation using maximum likelihood algorithms has been shown to be problematic, resulting in biased estimates, especially in the case of liquid and frequently...

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...

This paper proposes a method to compute ex-ante trading costs at the intraday level from limit order books. Using nearly 500 of the largest traded companies in the NYSE ArcaBook, we show that these costs have nontrivial intraday dynamics, are negatively related to volume and positively related...

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...