IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1811.10195.html
   My bibliography  Save this paper

Bull Bear Balance: A Cluster Analysis of Socially Informed Financial Volatility

Author

Listed:
  • Jonathan Manfield
  • Derek Lukacsko
  • Th'arsis T. P. Souza

Abstract

Using a method rooted in information theory, we present results that have identified a large set of stocks for which social media can be informative regarding financial volatility. By clustering stocks based on the joint feature sets of social and financial variables, our research provides an important contribution by characterizing the conditions in which social media signals can lead financial volatility. The results indicate that social media is most informative about financial market volatility when the ratio of bullish to bearish sentiment is high, even when the number of messages is low. The robustness of these findings is verified across 500 stocks from both NYSE and NASDAQ exchanges. The reported results are reproducible via an open-source library for social-financial analysis made freely available.

Suggested Citation

  • Jonathan Manfield & Derek Lukacsko & Th'arsis T. P. Souza, 2018. "Bull Bear Balance: A Cluster Analysis of Socially Informed Financial Volatility," Papers 1811.10195, arXiv.org.
    • Handle: RePEc:arx:papers:1811.10195
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1811.10195
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Th'arsis T. P. Souza & Tomaso Aste, 2016. "A nonlinear impact: evidences of causal effects of social media on market prices," Papers 1601.04535, arXiv.org, revised Mar 2016.
    2. Paul C. Tetlock & Maytal Saar‐Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, June.
    3. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    4. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    5. Edward A. Dyl & George J. Jiang, 2008. "Valuing Illiquid Common Stock," Financial Analysts Journal, Taylor & Francis Journals, vol. 64(4), pages 40-47, July.
    6. Zheludev, Ilya & Smith, Robert & Aste, Tomaso, 2014. "When can social media lead financial markets?," LSE Research Online Documents on Economics 57376, London School of Economics and Political Science, LSE Library.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gabriele Ranco & Darko Aleksovski & Guido Caldarelli & Miha Grčar & Igor Mozetič, 2015. "The Effects of Twitter Sentiment on Stock Price Returns," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-21, September.
    2. Agarwal, Shweta & Kumar, Shailendra & Goel, Utkarsh, 2019. "Stock market response to information diffusion through internet sources: A literature review," International Journal of Information Management, Elsevier, vol. 45(C), pages 118-131.
    3. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2016. "Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-14, January.
    4. David E. Allen & Michael McAleer & Abhay K. Singh, 2019. "Daily market news sentiment and stock prices," Applied Economics, Taylor & Francis Journals, vol. 51(30), pages 3212-3235, June.
    5. Marlene Amstad & Leonardo Gambacorta & Chao He & Dora Xia, 2021. "Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media," BIS Working Papers 917, Bank for International Settlements.
    6. Ahmad, Khurshid & Han, JingGuang & Hutson, Elaine & Kearney, Colm & Liu, Sha, 2016. "Media-expressed negative tone and firm-level stock returns," Journal of Corporate Finance, Elsevier, vol. 37(C), pages 152-172.
    7. Ding, Rong & Hou, Wenxuan & Liu, Yue (Lucy) & Zhang, John Ziyang, 2018. "Media censorship and stock price: Evidence from the foreign share discount in China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 112-133.
    8. David E. Allen & Michael McAleer, 2019. "Fake News and Propaganda: Trump’s Democratic America and Hitler’s National Socialist (Nazi) Germany," Sustainability, MDPI, vol. 11(19), pages 1-19, September.
    9. Li, Yuanpeng & Shi, Haina & Zhou, Yi, 2021. "The influence of the media on government decisions: Evidence from IPOs in China," Journal of Corporate Finance, Elsevier, vol. 70(C).
    10. Huang, Tzu-Lun, 2018. "The puzzling media effect in the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 129-146.
    11. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2014. "Coupling news sentiment with web browsing data improves prediction of intra-day price dynamics," Papers 1412.3948, arXiv.org, revised Dec 2015.
    12. Tsai, Feng-Tse & Lu, Hsin-Min & Hung, Mao-Wei, 2016. "The impact of news articles and corporate disclosure on credit risk valuation," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 100-116.
    13. Laura Xiaolei Liu & Ann E. Sherman & Yong Zhang, 2014. "The Long-Run Role of the Media: Evidence from Initial Public Offerings," Management Science, INFORMS, vol. 60(8), pages 1945-1964, August.
    14. Souza, Thársis T.P. & Aste, Tomaso, 2019. "Predicting future stock market structure by combining social and financial network information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    15. Jaroslav Bukovina, 2015. "Sentiment of a society and large-cap stock liquidity," MENDELU Working Papers in Business and Economics 2015-56, Mendel University in Brno, Faculty of Business and Economics.
    16. Allen, D.E. & McAleer, M.J. & McHardy Reid, D., 2018. "Fake News and Indifference to Truth," Econometric Institute Research Papers EI2018-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    17. Angelos J. Doukas & Jie (Michael) Guo & Herbert Y. T. Lam & Sarah (Hong) Xiao, 2016. "Media Endorsements of New Product Announcements: A New Marketing Strategy," European Financial Management, European Financial Management Association, vol. 22(3), pages 394-426, June.
    18. David E. Allen & Michael McAleer & David McHardy Reid, 2018. "Fake News And Indifference To Truth: Dissecting Tweets And State Of The Union Addresses By Presidents Obama And Trump," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 180-203, December.
    19. Frank, Murray Z. & Sanati, Ali, 2018. "How does the stock market absorb shocks?," Journal of Financial Economics, Elsevier, vol. 129(1), pages 136-153.
    20. Zongwu Cai & Pixiong Chen, 2022. "New Online Investor Sentiment and Asset Returns," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202216, University of Kansas, Department of Economics, revised Nov 2022.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1811.10195. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.