IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2211.06378.html
   My bibliography  Save this paper

A Multimodal Embedding-Based Approach to Industry Classification in Financial Markets

Author

Listed:
  • Rian Dolphin
  • Barry Smyth
  • Ruihai Dong

Abstract

Industry classification schemes provide a taxonomy for segmenting companies based on their business activities. They are relied upon in industry and academia as an integral component of many types of financial and economic analysis. However, even modern classification schemes have failed to embrace the era of big data and remain a largely subjective undertaking prone to inconsistency and misclassification. To address this, we propose a multimodal neural model for training company embeddings, which harnesses the dynamics of both historical pricing data and financial news to learn objective company representations that capture nuanced relationships. We explain our approach in detail and highlight the utility of the embeddings through several case studies and application to the downstream task of industry classification.

Suggested Citation

  • Rian Dolphin & Barry Smyth & Ruihai Dong, 2022. "A Multimodal Embedding-Based Approach to Industry Classification in Financial Markets," Papers 2211.06378, arXiv.org.
    • Handle: RePEc:arx:papers:2211.06378
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2211.06378
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Itzhak Ben-David & Francesco A. Franzoni & Rabih Moussawi, 2016. "Exchange Traded Funds (ETFs)," Swiss Finance Institute Research Paper Series 16-64, Swiss Finance Institute.
    2. Kahle, Kathleen M. & Walkling, Ralph A., 1996. "The Impact of Industry Classifications on Financial Research," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 31(3), pages 309-335, September.
    3. Kathleen M. Kahle & Ralph A. Walkling, "undated". "The Impact of Industry Classifications on Financial Research," Research in Financial Economics 9607, Ohio State University.
    4. Guenther, David A. & Rosman, Andrew J., 1994. "Differences between COMPUSTAT and CRSP SIC codes and related effects on research," Journal of Accounting and Economics, Elsevier, vol. 18(1), pages 115-128, July.
    5. Rian Dolphin & Barry Smyth & Ruihai Dong, 2022. "Stock Embeddings: Learning Distributed Representations for Financial Assets," Papers 2202.08968, arXiv.org.
    6. Bhaskarjit Sarmah & Nayana Nair & Dhagash Mehta & Stefano Pasquali, 2022. "Learning Embedded Representation of the Stock Correlation Matrix using Graph Machine Learning," Papers 2207.07183, arXiv.org.
    7. Vipul Satone & Dhruv Desai & Dhagash Mehta, 2021. "Fund2Vec: Mutual Funds Similarity using Graph Learning," Papers 2106.12987, arXiv.org.
    8. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    9. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    10. Xingchen Wan & Jie Yang & Slavi Marinov & Jan-Peter Calliess & Stefan Zohren & Xiaowen Dong, 2020. "Sentiment Correlation in Financial News Networks and Associated Market Movements," Papers 2011.06430, arXiv.org, revised Feb 2021.
    11. Qiong Wu & Christopher G. Brinton & Zheng Zhang & Andrea Pizzoferrato & Zhenming Liu & Mihai Cucuringu, 2019. "Equity2Vec: End-to-end Deep Learning Framework for Cross-sectional Asset Pricing," Papers 1909.04497, arXiv.org, revised Oct 2021.
    12. Christian Weiner, 2005. "The Impact of Industry Classification Schemes on Financial Research," SFB 649 Discussion Papers SFB649DP2005-062, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Parameswaran Gopikrishnan & Bernd Rosenow & Vasiliki Plerou & H. Eugene Stanley, 2000. "Identifying Business Sectors from Stock Price Fluctuations," Papers cond-mat/0011145, arXiv.org.
    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. Rian Dolphin & Barry Smyth & Ruihai Dong, 2022. "Stock Embeddings: Learning Distributed Representations for Financial Assets," Papers 2202.08968, arXiv.org.
    2. Lisa Baudot & Zhongwei Huang & Dana Wallace, 2021. "Stakeholder Perceptions of Risk in Mandatory Corporate Responsibility Disclosure," Journal of Business Ethics, Springer, vol. 172(1), pages 151-174, August.
    3. Dimitrios Vamvourellis & M'at'e Toth & Snigdha Bhagat & Dhruv Desai & Dhagash Mehta & Stefano Pasquali, 2023. "Company Similarity using Large Language Models," Papers 2308.08031, arXiv.org.
    4. Lee, Charles M.C. & Ma, Paul & Wang, Charles C.Y., 2015. "Search-based peer firms: Aggregating investor perceptions through internet co-searches," Journal of Financial Economics, Elsevier, vol. 116(2), pages 410-431.
    5. Brickley, James A. & Zimmerman, Jerold L., 2010. "Corporate governance myths: Comments on Armstrong, Guay, and Weber," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 235-245, December.
    6. Rian Dolphin & Barry Smyth & Ruihai Dong, 2023. "Industry Classification Using a Novel Financial Time-Series Case Representation," Papers 2305.00245, arXiv.org.
    7. Chen, Huaizhi & Cohen, Lauren & Lou, Dong, 2013. "Industry window dressing," LSE Research Online Documents on Economics 119035, London School of Economics and Political Science, LSE Library.
    8. Tobias Keller & Martin Glaum & Andreas Bausch & Thorsten Bunz, 2023. "The “CEO in context” technique revisited: A replication and extension of Hambrick and Quigley (2014)," Strategic Management Journal, Wiley Blackwell, vol. 44(4), pages 1111-1138, April.
    9. Yasser Alhenawi & Martha L. Stilwell, 2019. "Toward a complete definition of relatedness in merger and acquisition transactions," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 351-396, August.
    10. Dou, Winston Wei & Ji, Yan & Wu, Wei, 2021. "Competition, profitability, and discount rates," Journal of Financial Economics, Elsevier, vol. 140(2), pages 582-620.
    11. Andrade, Gregor & Stafford, Erik, 2004. "Investigating the economic role of mergers," Journal of Corporate Finance, Elsevier, vol. 10(1), pages 1-36, January.
    12. Eaton, Gregory W. & Guo, Feng & Liu, Tingting & Officer, Micah S., 2022. "Peer selection and valuation in mergers and acquisitions," Journal of Financial Economics, Elsevier, vol. 146(1), pages 230-255.
    13. Jensen, Gerald R. & Lundstrum, Leonard L. & Miller, Robert E., 2010. "What do dividend reductions signal?," Journal of Corporate Finance, Elsevier, vol. 16(5), pages 736-747, December.
    14. David Flacher & Jacques Pelletan, 2007. "Le concept d'industrie et sa mesure : origines, limites et perspectives - Une application à l'étude des mutations industrielles," Économie et Statistique, Programme National Persée, vol. 405(1), pages 13-46.
    15. Grimm Noh, 2019. "Strategic Decoupling in Korean Business Groups: Ambiguous Identity as a Strategy in Chaebol Groups," Sustainability, MDPI, vol. 11(9), pages 1-18, May.
    16. Zura Kakushadze & Willie Yu, 2017. "Open Source Fundamental Industry Classification," Papers 1706.04210, arXiv.org, revised Dec 2017.
    17. Sanjeev Bhojraj & Charles M. C. Lee & Derek K. Oler, 2003. "What's My Line? A Comparison of Industry Classification Schemes for Capital Market Research," Journal of Accounting Research, Wiley Blackwell, vol. 41(5), pages 745-774, December.
    18. Chunxia, Yang & Xueshuai, Zhu & Luoluo, Jiang & Sen, Hu & He, Li, 2016. "Study on the contagion among American industries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 601-612.
    19. Christensen, Jesper Lindgaard, 2013. "The ability of current statistical classifications to separate services and manufacturing," Structural Change and Economic Dynamics, Elsevier, vol. 26(C), pages 47-60.
    20. Henri Servaes & Ane Tamayo, 2014. "How Do Industry Peers Respond to Control Threats?," Management Science, INFORMS, vol. 60(2), pages 380-399, February.

    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:2211.06378. 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.