Orderimbalance, Liquidity and Market Returns


Book Description

We focus on an intuitive measure of trading activity: the aggregate daily order imbalance, buy orders less sell orders, on the NYSE. Order imbalance increases following market declines and vice versa, which reveals that investors are contrarians in aggregate. Order imbalances in either direction, excess buy or sell orders, reduce liquidity. Market-wide returns are strongly affected by contemporaneous and lagged order imbalances. Market returns reverse themselves after high negative imbalance, large negative return days. Even after controlling for aggregate volume and liquidity, market returns are affected by order imbalance.




Order Imbalance and Returns


Book Description

The paper explores the lead-lag relationship between the variables of order imbalance and return in futures and spot markets. Order imbalance is defined as the difference between buyer and seller initiated trades. Using tick test, the trades have been classified as buyer and seller initiated. The paper finds positive correlation between the variables of order imbalance in the futures market and the returns in the spot market. This relationship is further explored using a VAR framework for daily as well as a shorter interval of 120 min. The results reveal that even after controlling for lagged futures and spot returns, the futures market imbalance has a significant effect on spot market returns.




Order Imbalance and Individual Stock Returns


Book Description

This paper studies the relation between order imbalances and daily returns of individual stocks. Our tests are motivated by a theoretical framework, whose distinguishing feature is that it explicitly considers how market makers with inventory concerns dynamically accommodate autocorrelated imbalances. Persistence in imbalances arises because agents split their orders over time to minimize expected trading costs. In equilibrium, continuing price pressures caused by autocorrelated imbalances cause a positive relation between lagged imbalances and returns over daily horizons. However, this positive relation reverses sign after controlling for the current imbalance. We find empirical evidence consistent with all of these implications of the model. We also find that imbalance-based trading strategies yield statistically significant returns, the magnitude of which is moderate enough to be consistent with an equilibrium wherein intermediaries with inventory concerns accommodate persistent trader demands.




Cross Return, Volatility and Order Imbalance in International Cross Listings


Book Description

The globalization of financial markets motivates plenty of non-U.S. companies listing their shares on the U.S. exchanges. Following Eun and Sabherwal (2003), we investigate the extent to which the NYSE and the TSX contribute to price discovery of the Canadian Stocks listing on these exchanges. By examining the effect of contemporaneous order imbalances on cross-border stock returns, we find that contemporaneous imbalance on the NYSE is significant to the stock returns on the TSX. Since the U.S. exchanges are the most liquid and largest exchanges in the world, they play a leading role in capital markets. Our findings imply that the NYSE significantly contributes to price discovery.Besides, we apply GARCH (1, 1) model to test the effect of contemporaneous imbalance on the cross-listing returns and the effect of trading volume on foreign return variance. We find that there is a significant influence of trading volume in domestic/foreign markets on the volatility of the stock return in foreign/domestic markets in our empirical results. The evidence shows that cross-listing helps informed traders distribute their trading across the two markets to make use of private information between the markets. This activity results in the increasing generation of private information, and then causes an increase in the stock return variance. However, contemporaneous order imbalance on the TSX/NYSE does not have an important impact on the stock returns on the NYSE/TSX. It means that order is not a good indicator of information flow. The significance in GARCH (1, 1) model comes from trading volume to the return volatility, not to the stock return. The insignificance for effect of order imbalance on the cross-board return represents limited capital flow between countries. The view supports evidence of segmentation between Canadian and the U.S. markets suggested by Foerster and Karolyi (1993).




High-Frequency Trading


Book Description

A fully revised second edition of the best guide to high-frequency trading High-frequency trading is a difficult, but profitable, endeavor that can generate stable profits in various market conditions. But solid footing in both the theory and practice of this discipline are essential to success. Whether you're an institutional investor seeking a better understanding of high-frequency operations or an individual investor looking for a new way to trade, this book has what you need to make the most of your time in today's dynamic markets. Building on the success of the original edition, the Second Edition of High-Frequency Trading incorporates the latest research and questions that have come to light since the publication of the first edition. It skillfully covers everything from new portfolio management techniques for high-frequency trading and the latest technological developments enabling HFT to updated risk management strategies and how to safeguard information and order flow in both dark and light markets. Includes numerous quantitative trading strategies and tools for building a high-frequency trading system Address the most essential aspects of high-frequency trading, from formulation of ideas to performance evaluation The book also includes a companion Website where selected sample trading strategies can be downloaded and tested Written by respected industry expert Irene Aldridge While interest in high-frequency trading continues to grow, little has been published to help investors understand and implement this approach—until now. This book has everything you need to gain a firm grip on how high-frequency trading works and what it takes to apply it to your everyday trading endeavors.




The Human Face of Big Data


Book Description

The authors invited more than 100 journalists worldwide to use photographs, charts and essays to explore the world of big data and its growing influence on our lives and society.




Market Microstructure In Practice (Second Edition)


Book Description

This book exposes and comments on the consequences of Reg NMS and MiFID on market microstructure. It covers changes in market design, electronic trading, and investor and trader behaviors. The emergence of high frequency trading and critical events like the'Flash Crash' of 2010 are also analyzed in depth.Using a quantitative viewpoint, this book explains how an attrition of liquidity and regulatory changes can impact the whole microstructure of financial markets. A mathematical Appendix details the quantitative tools and indicators used through the book, allowing the reader to go further independently.This book is written by practitioners and theoretical experts and covers practical aspects (like the optimal infrastructure needed to trade electronically in modern markets) and abstract analyses (like the use on entropy measurements to understand the progress of market fragmentation).As market microstructure is a recent academic field, students will benefit from the book's overview of the current state of microstructure and will use the Appendix to understand important methodologies. Policy makers and regulators will use this book to access theoretical analyses on real cases. For readers who are practitioners, this book delivers data analysis and basic processes like the designs of Smart Order Routing and trade scheduling algorithms.In this second edition, the authors have added a large section on orderbook dynamics, showing how liquidity can predict future price moves, and how High Frequency Traders can profit from it. The section on market impact has also been updated to show how buying or selling pressure moves prices not only for a few hours, but even for days, and how prices relax (or not) after a period of intense pressure.Further, this edition includes pages on Dark Pools, Circuit Breakers and added information outside of Equity Trading, because MiFID 2 is likely to push fixed income markets towards more electronification. The authors explore what is to be expected from this change in microstructure. The appendix has also been augmented to include the propagator models (for intraday price impact), a simple version of Kyle's model (1985) for daily market impact, and a more sophisticated optimal trading framework, to support the design of trading algorithms.




Order Flow Imbalance Effects on the German Stock Market


Book Description

Order flow imbalance refers to the difference between market buy and sell orders during a given period. This paper analyzes effects of order flow imbalance on returns of stocks traded on the German Xetra trading system on a daily basis. It is the first study examining this relation for the German stock market. In contrast to previous studies on other markets, we control for unobserved effects by using a fixed effects panel regression. For the concurrent (or conditional) relation between order imbalance and returns, our results confirm those of the literature. For the question of return predictability from past order imbalances (unconditional relation), our results are partly confirmatory. As a new contribution, we provide evidence for size and liquidity effects for the unconditional relation between order imbalance and returns.




Trade Size, Order Imbalance, and the Volatility-Volume Relation


Book Description

This paper examines the roles of the number of trades, trade size, and order imbalance (buyer- versus seller- initiated trades) in explaining the volatility-volume relation for a sample of NYSE and NASDAQ stocks. Contrary to some previous studies, our results reconfirm the significance of trade size, beyond that of the number of trades, in the volatility-volume relation in both markets. After controlling for the return impact of order imbalance, the volatility-volume relation becomes much weaker. This suggests that one major driving force for the volatility-volume relation stems from order imbalance. Furthermore, on the NYSE, the return impact of order imbalance increases monotonically with the trade size of order imbalance, whereas on NASDAQ, there is no such monotonic relation and the largest return impact comes from the order imbalance in maximum-sized Small Order Execution System (SOES) trades.




Algorithmic and High-Frequency Trading


Book Description

The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you.