“This is a timely – and exciting – book. The technology of extracting financial sentiment from news feeds and other such sources is one that has been slowly growing, supported by the accelerating infrastructure provided by the World Wide Web. Over the past ten years or so, papers have been appearing showing that useful information can be extracted in this way. Moreover, one can legitimately expect the rate of progress to gather pace, as other supporting web technologies continue to develop.
This book is the first to provide a comprehensive overview of the state of the art. It will attract a lot of attention. From a technical perspective, the area presents some deep and interesting challenges, which are nicely captured here. One is the central issue of fusing entirely different kinds of information, from quite distinct sources, and with very different degrees of reliability. Another is an issue which mining of large observational data sets has to contend with, whatever its area of application, namely the problem of selection bias: it is all too easy to extract a distorted, non-representative, data set, so that any analyses based on it are at risk of mistaken conclusions. Overall, this technology is still in its infancy, but the papers presented in this volume provide a perfect launch pad for the future of news analytics in finance.
Just as social statistics enables us both to define and measure the aggregate phenomena that define society, so the work described in this volume will enable us to discern and quantify the forces which steer financial markets.”
Professor David J. Hand, Professor of Statistics, Imperial College, London, and Chief Scientific Advisor, Winton Capital Management, and President, Royal Statistical Society.
“This cutting edge collection of writings offers important insights into the connection between news analytics and sentiment that are rich, deep, and systematic. Investors and academics alike have much to learn from reading this fascinating book.”
Hersh Shefrin, Mario L. Belotti Professsor of Finance, Santa Clara University, Leavey School of Business.
“Stop the press! At last, we have a substantive book on financial news. This scholarly treatise reaches way beyond how to read the stock pages to provide modern insights on the relationship between news and price formation.”
Peter Carr, Global Head of Market Modeling, Morgan Stanley, and Executive Director, Masters in Math Finance, NYU.
“Technological progress enhances human efficiency including the efficiency of our markets. Trading on news is an integral part of such progress and The Handbook of News Analytics in Finance is a welcome compendium on where we stand with regard to the risks and rewards of News in markets.”
Dilip B. Madan, Professor of Finance, Robert H. Smith School of Business and Consultant to Morgan Stanley and Caspian Capital.
From the Back Cover
The Handbook of News Analytics in Finance is a landmark publication bringing together the latest models and applications of News Analytics for asset pricing, portfolio construction, trading and risk control.
Designed to provide a rapid yet comprehensive understanding of this topic, the book begins with an overview of News Analytics (NA), and an explanation of the technology and applications. It is then presented in four parts: Part 1 contains an explanation of methods and models which are used to measure and quantify news sentiment. In Part 2 the relationship between news events and discovery of abnormal returns (the elusive alpha) is discussed in detail by the leading researchers and industry experts. The material in this part also covers potential applications of NA to trading and fund management. Part 3 covers the use of quantified news for the purpose of monitoring, early diagnostics and risk control. Part 4 is entirely industry focused; it contains insights of experts from leading technology (content) vendors. It also contains a discussion of technologies and finally a compact directory of content vendors and financial analytics companies in the marketplace of NA. The book draws equally upon the expertise of academics and practitioners who have developed these models and is supported by two major content vendors – RavenPack and Thomson Reuters – leading providers of news analytics software and machine readable news.
The book will appeal to decision makers in the banking, finance and insurance services industry. In particular: asset managers; quantitative fund managers; hedge fund managers; algorithmic traders; proprietary (program) trading desks; sell-side firms; brokerage houses; risk managers and research departments will benefit from the unique insights into this new and pertinent area of financial modelling.
Reviews
There are no reviews yet.