Title

Market sentiment dispersion and its effects on stock return and volatility

Document Type

Journal article

Source Publication

Electronic Markets

Publication Date

8-2017

Volume

27

Issue

3

First Page

283

Last Page

296

Publisher

Springer

Keywords

Investor sentiment, Text mining, Return and volatility predictability

Abstract

Behavioral economics has revealed that investor sentiment can profoundly affect individual behavior and decision-making. Recently, the question is no longer whether investor sentiment affects stock market valuation, but how to directly measure investor sentiment and quantify its effects. Before the era of big data, research uses proxies as a mediator to indirectly measure investor sentiment, which has proved elusive due to insufficient data points. In addition, most of extant sentiment analysis studies focus on institutional investors instead of individual investors. This is despite the fact that United States individual investors have been holding around 50% of the stock market in direct stock investments. In order to overcome difficulties in measuring sentiment and endorse the importance of individual investors, we examine the role of individual sentiment dispersion in stock market. In particular, we investigate whether sentiment dispersion contains information about future stock returns and realized volatility. Leveraging on development of big data and recent advances in data and text mining techniques, we capture 1,170,414 data points from Twitter and used a text mining method to extract sentiment and applied both linear regression and Support Vector Regression; found that individual sentiment dispersion contains information about stock realized volatility, and can be used to increase the prediction accuracy. We expect our results contribute to extant theories of electronic market financial behavior by directly measuring the individual sentiment dispersion; raising a new perspective to assess the impact of investor opinion on stock market; and recommending a supplementary investing approach using user-generated content.

DOI

10.1007/s12525-017-0254-5

Print ISSN

10196781

E-ISSN

14228890

Publisher Statement

Copyright © Institute of Applied Informatics at University of Leipzig 2017

Access to external full text or publisher's version may require subscription.

Full-text Version

Publisher’s Version

Recommended Citation

See-To, E. W. K., & Yang, Y. (2017). Market sentiment dispersion and its effects on stock return and volatility. Electron Markets, 27(3), 283-296. doi: 10.1007/s12525-017-0254-5

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