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Company Similarity using Large Language Models

Author

Listed:
  • Dimitrios Vamvourellis
  • M'at'e Toth
  • Snigdha Bhagat
  • Dhruv Desai
  • Dhagash Mehta
  • Stefano Pasquali

Abstract

Identifying companies with similar profiles is a core task in finance with a wide range of applications in portfolio construction, asset pricing and risk attribution. When a rigorous definition of similarity is lacking, financial analysts usually resort to 'traditional' industry classifications such as Global Industry Classification System (GICS) which assign a unique category to each company at different levels of granularity. Due to their discrete nature, though, GICS classifications do not allow for ranking companies in terms of similarity. In this paper, we explore the ability of pre-trained and finetuned large language models (LLMs) to learn company embeddings based on the business descriptions reported in SEC filings. We show that we can reproduce GICS classifications using the embeddings as features. We also benchmark these embeddings on various machine learning and financial metrics and conclude that the companies that are similar according to the embeddings are also similar in terms of financial performance metrics including return correlation.

Suggested Citation

  • 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.
  • Handle: RePEc:arx:papers:2308.08031
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    References listed on IDEAS

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    1. Sanjeev Bhojraj & Charles M. C. Lee, 2002. "Who Is My Peer? A Valuation‐Based Approach to the Selection of Comparable Firms," Journal of Accounting Research, Wiley Blackwell, vol. 40(2), pages 407-439, May.
    2. Gerard Hoberg & Gordon Phillips, 2016. "Text-Based Network Industries and Endogenous Product Differentiation," Journal of Political Economy, University of Chicago Press, vol. 124(5), pages 1423-1465.
    3. Paul Geertsema & Helen Lu, 2023. "Relative Valuation with Machine Learning," Journal of Accounting Research, Wiley Blackwell, vol. 61(1), pages 329-376, March.
    4. Rian Dolphin & Barry Smyth & Ruihai Dong, 2022. "Stock Embeddings: Learning Distributed Representations for Financial Assets," Papers 2202.08968, arXiv.org.
    5. Tim Loughran & Bill McDonald, 2020. "Textual Analysis in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 12(1), pages 357-375, December.
    6. Rhodes-Kropf, Matthew & Robinson, David T. & Viswanathan, S., 2005. "Valuation waves and merger activity: The empirical evidence," Journal of Financial Economics, Elsevier, vol. 77(3), pages 561-603, September.
    7. Kaustia, Markku & Rantala, Ville, 2015. "Social learning and corporate peer effects," Journal of Financial Economics, Elsevier, vol. 117(3), pages 653-669.
    8. 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.
    9. 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.
    10. Fama, Eugene F. & French, Kenneth R., 1997. "Industry costs of equity," Journal of Financial Economics, Elsevier, vol. 43(2), pages 153-193, February.
    11. Rian Dolphin & Barry Smyth & Ruihai Dong, 2023. "Industry Classification Using a Novel Financial Time-Series Case Representation," Papers 2305.00245, arXiv.org.
    12. 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.
    13. Bartram, Söhnke M. & Grinblatt, Mark, 2018. "Agnostic fundamental analysis works," Journal of Financial Economics, Elsevier, vol. 128(1), pages 125-147.
    14. Jing Liu & Doron Nissim & Jacob Thomas, 2002. "Equity Valuation Using Multiples," Journal of Accounting Research, Wiley Blackwell, vol. 40(1), pages 135-172, March.
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