IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2309.16888.html
   My bibliography  Save this paper

Beyond Gut Feel: Using Time Series Transformers to Find Investment Gems

Author

Listed:
  • Lele Cao
  • Gustaf Halvardsson
  • Andrew McCornack
  • Vilhelm von Ehrenheim
  • Pawel Herman

Abstract

This paper addresses the growing application of data-driven approaches within the Private Equity (PE) industry, particularly in sourcing investment targets (i.e., companies) for Venture Capital (VC) and Growth Capital (GC). We present a comprehensive review of the relevant approaches and propose a novel approach leveraging a Transformer-based Multivariate Time Series Classifier (TMTSC) for predicting the success likelihood of any candidate company. The objective of our research is to optimize sourcing performance for VC and GC investments by formally defining the sourcing problem as a multivariate time series classification task. We consecutively introduce the key components of our implementation which collectively contribute to the successful application of TMTSC in VC/GC sourcing: input features, model architecture, optimization target, and investor-centric data processing. Our extensive experiments on two real-world investment tasks, benchmarked towards three popular baselines, demonstrate the effectiveness of our approach in improving decision making within the VC and GC industry.

Suggested Citation

  • Lele Cao & Gustaf Halvardsson & Andrew McCornack & Vilhelm von Ehrenheim & Pawel Herman, 2023. "Beyond Gut Feel: Using Time Series Transformers to Find Investment Gems," Papers 2309.16888, arXiv.org, revised Jun 2024.
    • Handle: RePEc:arx:papers:2309.16888
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2309.16888
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. José Santisteban & David Mauricio & Orestes Cachay, 2021. "Critical success factors for technology-based startups," International Journal of Entrepreneurship and Small Business, Inderscience Enterprises Ltd, vol. 42(4), pages 397-421.
    2. Sergey Chernenko & Josh Lerner & Yao Zeng, 2021. "Mutual Funds as Venture Capitalists? Evidence from Unicorns [The role of boards of directors in corporate governance: a conceptual framework and survey]," The Review of Financial Studies, Society for Financial Studies, vol. 34(5), pages 2362-2410.
    3. Block, Joern & Fisch, Christian & Vismara, Silvio & Andres, René, 2019. "Private equity investment criteria: An experimental conjoint analysis of venture capital, business angels, and family offices," Journal of Corporate Finance, Elsevier, vol. 58(C), pages 329-352.
    4. Dafei Yin & Jing Li & Gaosheng Wu, 2021. "Solving the Data Sparsity Problem in Predicting the Success of the Startups with Machine Learning Methods," Papers 2112.07985, arXiv.org.
    5. Eulalia Skawińska & Romuald I. Zalewski, 2020. "Success Factors of Startups in the EU—A Comparative Study," Sustainability, MDPI, vol. 12(19), pages 1-28, October.
    6. Gompers, Paul A. & Gornall, Will & Kaplan, Steven N. & Strebulaev, Ilya A., 2020. "How do venture capitalists make decisions?," Journal of Financial Economics, Elsevier, vol. 135(1), pages 169-190.
    7. Clement Gastaud & Theophile Carniel & Jean-Michel Dalle, 2019. "The varying importance of extrinsic factors in the success of startup fundraising: competition at early-stage and networks at growth-stage," Papers 1906.03210, arXiv.org.
    8. Marco Guerzoni & Consuelo R. Nava & Massimiliano Nuccio, 2019. "The survival of start-ups in time of crisis. A machine learning approach to measure innovation," Papers 1911.01073, arXiv.org.
    9. Kaiser, Ulrich & Kuhn, Johan M., 2020. "The value of publicly available, textual and non-textual information for startup performance prediction," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
    10. Lele Cao & Vilhelm von Ehrenheim & Sebastian Krakowski & Xiaoxue Li & Alexandra Lutz, 2022. "Using Deep Learning to Find the Next Unicorn: A Practical Synthesis," Papers 2210.14195, arXiv.org, revised Jun 2024.
    11. Jan Kinne & David Lenz, 2021. "Predicting innovative firms using web mining and deep learning," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-18, April.
    12. Malmström, Malin & Voitkane, Aija & Johansson, Jeaneth & Wincent, Joakim, 2020. "What do they think and what do they say? Gender bias, entrepreneurial attitude in writing and venture capitalists’ funding decisions," Journal of Business Venturing Insights, Elsevier, vol. 13(C).
    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. Lele Cao & Vilhelm von Ehrenheim & Sebastian Krakowski & Xiaoxue Li & Alexandra Lutz, 2022. "Using Deep Learning to Find the Next Unicorn: A Practical Synthesis," Papers 2210.14195, arXiv.org, revised Jun 2024.
    2. Ewens, Michael & Malenko, Nadya, 2020. "Board Dynamics over the Startup Life Cycle," SocArXiv t96yq, Center for Open Science.
    3. Bian, Bo & Li, Yingxiang & Nigro, Casimiro A., 2022. "Conflicting fiduciary duties and fire sales of VC-backed start-ups," LawFin Working Paper Series 35, Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin).
    4. Julian Kaboth & Arnd Lodowicks & Maximilian Schreiter & Bernhard Schwetzler, 2023. "Same same but different: how preferential claims trigger valuation discounts in equity tranches of VC-backed firms," Review of Quantitative Finance and Accounting, Springer, vol. 60(3), pages 877-914, April.
    5. Alexandra Moritz & Walter Diegel & Joern Block & Christian Fisch, 2022. "VC investors’ venture screening: the role of the decision maker’s education and experience," Journal of Business Economics, Springer, vol. 92(1), pages 27-63, January.
    6. Ari Hyytinen & Petri Rouvinen & Mika Pajarinen & Joosua Virtanen, 2023. "Ex Ante Predictability of Rapid Growth: A Design Science Approach," Entrepreneurship Theory and Practice, , vol. 47(6), pages 2465-2493, November.
    7. Lavanchy, Maude & Reichert, Patrick & Joshi, Amit, 2022. "Blood in the water: An abductive approach to startup valuation on ABC's Shark Tank," Journal of Business Venturing Insights, Elsevier, vol. 17(C).
    8. Ashish Vazirani & Titas Bhattacharjee, 2021. "Entrepreneurial Finance in the Twenty-first Century, a Review of Factors Influencing Venture Capitalist’s Decision," Journal of Entrepreneurship and Innovation in Emerging Economies, Entrepreneurship Development Institute of India, vol. 30(2), pages 306-335, September.
    9. Niculaescu, Corina-Elena & Sangiorgi, Ivan & Bell, Adrian R., 2023. "Venture capital financing in the eSports industry," Research in International Business and Finance, Elsevier, vol. 65(C).
    10. Fisch, Christian & Momtaz, Paul P., 2020. "Institutional investors and post-ICO performance: an empirical analysis of investor returns in initial coin offerings (ICOs)," Journal of Corporate Finance, Elsevier, vol. 64(C).
    11. Block, Joern H. & Hirschmann, Mirko & Fisch, Christian, 2021. "Which criteria matter when impact investors screen social enterprises?," Journal of Corporate Finance, Elsevier, vol. 66(C).
    12. Kang, Jun-Koo & Li, Yingxiang & Oh, Seungjoon, 2022. "Venture Capital Coordination in Syndicates, Corporate Monitoring, and Firm Performance," Journal of Financial Intermediation, Elsevier, vol. 50(C).
    13. Ye Zhang, 2020. "Discrimination in the Venture Capital Industry: Evidence from Field Experiments," Papers 2010.16084, arXiv.org, revised Aug 2022.
    14. Josh Lerner & Ramana Nanda, 2020. "Venture Capital's Role in Financing Innovation: What We Know and How Much We Still Need to Learn," Journal of Economic Perspectives, American Economic Association, vol. 34(3), pages 237-261, Summer.
    15. Bhanot, Karan & Kadapakkam, Palani-Rajan, 2022. "Pay for performance, partnership success, and the internal organization of venture capital firms," Journal of Corporate Finance, Elsevier, vol. 75(C).
    16. Nanda, Ramana & Samila, Sampsa & Sorenson, Olav, 2020. "The persistent effect of initial success: Evidence from venture capital," Journal of Financial Economics, Elsevier, vol. 137(1), pages 231-248.
    17. Agarwal, Vikas & Barber, Brad M. & Cheng, Si & Hameed, Allaudeen & Shanker, Harshini & Yasuda, Ayako, 2023. "Do investors overvalue startups? Evidence from the junior stakes of mutual funds," CFR Working Papers 23-04, University of Cologne, Centre for Financial Research (CFR).
    18. Simone Aresu & Luigi Rombi & Andrea Cardia, 2019. "Management accounting systems in venture capital-backed start-up companies," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2019(3), pages 35-58.
    19. Amaya, Diego & Brolley, Michael & Smith, Brian F., 2020. "Diamonds in the rough: The value of scouting for early-stage funding," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    20. Michael Ewens & Joan Farre-Mensa, 2020. "The Deregulation of the Private Equity Markets and the Decline in IPOs," The Review of Financial Studies, Society for Financial Studies, vol. 33(12), pages 5463-5509.

    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:2309.16888. 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.