We investigate the role algorithmic trading (AT) on days when the absolute value of the market return is more than two percent. We find that the abnormal return of a stock is related to the stock's AT intensity, that high AT intensity stocks experience less price drops (surges) on days when the...

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...

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...

Despite the fact that an intraday market price distribution is not normal, the random walk model of price behaviour is as important for the understanding of basic principles of the market as the pendulum model is a starting point of many fundamental theories in physics. This model is a good zero...

Algorithmic traders acknowledge that their models are incorrectly specified, thus we allow for ambiguity in their choices to make their models robust to misspecification in: (i) the arrival rate of market orders (MOs), (ii) the fill probability of limit orders, and (iii) the dynamics of the...

Algorithmic trading is generally defined as using computer-generated algorithms to create and execute orders on marketplaces. Recently, such algo-trading strategies are increasingly being associated with the negative impact on capital markets – both from a technological as well as a business...

We assume that the drift in the returns of asset prices consists of an idiosyncratic component and a common component given by a co-integration factor. We analyze the optimal investment strategy for an agent who maximizes expected utility of wealth by dynamically trading in these assets. The...

The financial services industry is among the leading industries in IT-spending. Still, little research exists which investigates how IT influences the financial services sector. Against this background, we study how a technology which emerged within the last years affects securities trading:...

Using high frequency data from the London Stock Exchange (LSE), we investigate the relationship between informed trading and the price impact of block trades on intraday and inter-day basis. Price impact of block trades is stronger during the first hour of trading; this is consistent with the...