The Handbook of Sentiment Analysis in Finance
Published on 10. March 2016
Book
Hardback
616 pages
978-1-910571-57-6 (ISBN)
Description
In this handbook, our aim has been to compile a comprehensive collection of relevant research results, which cover the financial applications of sentiment classification in general, and sentiment classification in particular. This is a emerging and evolving topic area that has been impacted by (i) growth in social media, (ii) online information sources, (iii) evolution of data sciences, (iv) continued developments in machine learning and artificial intelligence and (v) maturing of financial technologies (fintech), which exploit speed of communications and computations. Whereas early applications of sentiment analysis have been in the domain of equities, the recent developments have covered other asset classes, specifically, fixed income, foreign exchange, energy products and commodities. In all these domains we have focused on three major application areas which are automated trading, fund rebalancing and risk qualification and control.
Reviews / Votes
The technology of extracting financial sentiment from news feeds and other such sources continues to advance. This volume, an update of the earlier Handbook of News Analytics in Finance, describes the current state of the art, illustrating the considerable progress over the past five years. It will provide an indispensible introduction to the area, as well as a comprehensive reference work. - Professor David J. Hand - Emeritus Professor of Mathematics, Imperial College, London - Chief Scientific Advisor, Winton Capital Management; An excellent collection of studies into how market prices respond to the flow of information in the economy. Many sources of information ranging from prominent news stories through to social media discussions are analysed for their impact on asset pricing, including the development of strategies trading the flow of information. The handbook is a fundamental addition to understanding the origins, processes and pathways of price discovery. - Prof Dillip Madan - Professor of Finance, Roert H. Smith School of Business; The effective quantification of non-standard, non-numerical data has opened up vast new avenues of investment signal research. The volume provides a cogent and valuable summary of the current research in this area. - Peter Swank, Ph.D., - Vice President, Tudor Investment CorporationMore details
Language
English
Place of publication
Thame
United Kingdom
Dimensions
Height: 216 mm
Width: 135 mm
ISBN-13
978-1-910571-57-6 (9781910571576)
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Schweitzer Classification
Persons
GAUTAM MITRA is founder and MD of Optirisk Systems. He is an internationally renowned research scientist in the field of Operational Research in general and computational optimisation and modelling in particular. He is an alumni of UCL and currently a visiting professor at UCL. In 2004 he was awarded the title of 'distinguished professor' by Brunel University in recognition of his contributions in the domain of computational optimisation, risk analytics and modelling. Professor Mitra is also the founder and chairman of the sister company UNICOM seminars.XIANG YU is a Business Development Techno Executive at Optirisk Systems. She has a PhD in Mathematics from Brunel University. Her research interests are in sentiment analysis and market microstructure and their application in financial analytics. In Optirisk Systems, she conducts client facing applied research, she is also in charge of all aspects of acquiring market data and news metadata.