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We are updating The Handbook of News Analytics in Finance

Click here for more information on the updated handbook

The Handbook of Sentiment Analysis in Finance (2015)


The Handbook of News Analytics in Finance (2011)

Released: April 2011 Hardback

Price: £80.00 (Purchase via. OptiRisk discount) £50.00 + £5.00 P&P (UK)

ISBN: 978-0-470-66679-1

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The Handbook of News Analytics in Finance (2011) 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 is accompanied by a website which features supplementary resources for news analytics, including models and prototype tools.

Research Contributors

  • Brad Barber, UC Davis Graduate School of Management
  • Gurvinder Brar, MacQuarie Research Equities
  • Richard Brown, Thomson Reuters
  • Sanjiv R. Das, Leavey School of Business, Santa Clara University
  • Christian Davis, MacQuarie Research Equities
  • Dan diBartolomeo CFA, CEO Northfield Information Services Inc.
  • Huu Nhan Duong, Faculty of Business & Law, Deakin University, Australia
  • Michael Dzielinski, Swiss Banking Institute, University of Zurich
  • Armando Gonzalez, RavenPack International
  • Peter Hafez, RavenPack International
  • Alexander D. Healy, AlphaSimplex Group
  • Petko Kalev, Faculty of Business Economics, Monash University, Australia
  • John Kittrell, Knightsbridge Asset Management LLC
  • David Leinweber, UC Berkeley Center for Innovative Financial Technology & Leinweber & Co.
  • Andrew W. Lo, AlphaSimplex Group and MIT Sloan School of Management
  • Gautam Mitra, CARISMA and OptiRisk Systems
  • Leela Mitra, OptiRisk Systems
  • Andy Moniz, MacQuarie Research Equities
  • Marion Munz, Media Sentiment
  • Terrance Odean, Haas School of Business, University of California
  • Marc Rieger, Swiss Banking Institute, University of Zurich
  • Jacob Sisk, Infoshock Inc. & Leinweber & Co
  • Adam Strudwick, MacQuarie Research Equities
  • Tõnn Talsepp, Tallinn University of Technology, Estonia

The Handbook of Sentiment Analysis in Finance, 2015

Building on the success of the previous handbook, we are researching and compiling an update, set to be released in November 2015. The latest edition will include different sources of information such as:

  1. News Wires
  2. Macro-economic Announcements
  3. Social Media
  4. Microblogs/Twitter
  5. Online (search) Information e.g. Google Trends

The applications of sentiment analysis are considered for multiple asset classes including:

  1. Equities
  2. Fixed Income Instruments
  3. Foreign Exchange
  4. Commodities (Oil, Gas, Energy and others)
  5. Green Commodities

Click on the "2015 Handbook Content" Tab for the full content list


“This is a timely – and exciting – book. 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. Chief Scientific Advisor, Winton Capital Management. President, Royal Statistical Society

“This cutting edge collection of papers 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 presses! 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. 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 on News Analytics 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

“The world runs on information and few areas as directly so as in finance. Now that technology and quantitative techniques have caught up with the live news feed, this volume will be an indispensible addition to the practitioner's library.”
- Matthew Lee, Head of Research Global Index Equity, BlackRock

The Handbook will be of interest to key decision makers in the Banking, Finance and Insurances Services industry. In particular,

  • Asset Managers,
  • Algorithmic Traders
  • Brokerage Houses
  • Quantitative Fund Managers
  • Proprietary (program) Trading Desks
  • Risk Managers
  • Hedge Fund Managers
  • Sell-side Firms
  • Research Departments

These players need to continually innovate to stay competitive in an increasingly sophisticated and aggressive market place. They need to provide a differentiated service and produce excess returns.

Background and Overview of News Analytics in Finance
A review chapter on Scope of application of real time machine readable news and news sentiment data in finance
  • Trading models
  • Risk management
Part I - Sentiment classification
Papers on:
  • Turning textual information and headlines into sentiment scores
  • Trawling the web effectively for relevant data
Part II – News and abnormal returns
Papers on:
  • Models for abnormal returns
  • Models for trading
Part III – News and volatility
Papers on:
  • Models for volatility estimation
  • Models for trading and risk control
Part IV – Industry insights, technology, products and services
Papers on:
  • A comparative study if products and services offered to the trading and investment management community
  • Thought leadership articles
  • Case studies
  • Q & A write up
Part V – Bibliography
  • Annotated list of published journal papers and white papers on news.

Part VI – Directory of news analytics service providers
Company, Locations, Summary services and products
Chapter 1
Progress in Sentiment Analysis applied to Finance: An Overview

Gautam Mitra & Xiang Yu
Part I - Text Analytics, Classification and Metrics
  • Analysis of News
  • Analysis of Microblogs and Twitter
  • Analysis of other Social Media Data
  • Analysis of Online (search) Information
  • Measuring Sentiment and Measuring Impact
Part II – Sentiment Analysis Applied to Equities
Part III – Sentiment Analysis for other Asset Classes
  • Commodities - Oil, Gas, Energy
  • Green Commodities
  • Fixed Income Instruments
  • Foreign Exchange
Part IV – Predictive Analytics of Asset Behaviour - Return, Volatility & Liquidity

Part V – Applications of Sentiment Analysis
  • Fund Rebalancing Strategies
  • Trading Strategies
  • Risk Control
  • Regulatory Control and Market Surveillance

Part VI – Industry insights, Technology products and Service Providers
Papers on:
If you are interested in contributing to this section please find more details from the sponsorship pack.
Part VII - Directory of News Analytics Service Providers
Company, Locations, Summary services and products



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