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Social Media and News Sentiment Analysis for Advanced Investment Strategies

  • Steve Y. YangEmail author
  • Sheung Yin Kevin Mo
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 639)

Abstract

The motivation of this chapter hinges on the growing popularity in the use of news and social media information and their increasing influence on the financial investment community . This chapter investigates the interplay between news/social sentiment and financial market movement in the form of empirical impact. The underlying belief is that news and social media influence investor sentiment, which in turn drives financial decisions and predicates the upward or downward movement of the financial markets. This book chapter contributes to the existing literature of sentiment analysis in the following three areas: (a) It provides a review of existing findings about influence of social media and news sentiment to asset prices and documents the persistent correlation between media sentiment and market movement. (b) It shows that abnormal news sentiment can be a predictive proxy for financial market returns and volatility, based on the intuition that extreme investor sentiment changes tend to have long and last effects to market movement. (c) It presents a number of approaches to formulate investment strategies based on the sentiment trend, shocks and feedback strength. The results show that the sentiment-based strategies yield superior risk-adjusted returns over other benchmark strategies. Altogether, this chapter provides a framework of existing empirical knowledge on the impact of sentiment on financial markets and further prescribes advanced investment strategies based on sentiment analytics.

Keywords

Sentiment analysis Financial investment community Genetic algorithms Investment strategies 

Notes

Acknowledgments

The authors would like to thank the Financial Engineering Division at Stevens Institute of Technology for providing a state-of-the-art research environment with data access and hardware support. They would also like to acknowledge the support from the Civil Group of Northrop Grumman Corporation.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Faculty of Financial Engineering, School of Systems & EnterprisesStevens Institute of TechnologyHobokenUSA
  2. 2.Faculty of Financial EngineeringStevens Institute of TechnologyHobokenUSA

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