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Machine learning applied to accounting variables yields the risk-return metrics of private company portfolios

Author

Listed:
  • Elias Cavalcante-Filho
  • Flavio Abdenur, Rodrigo De Losso

Abstract

Constructing optimal Markowitz Mean-Variance portfolios of publicly-traded stock is a straighforward and well-known task. Doing the same for portfolios of privately-owned firms, given the lack of historical price data, is a challenge. We apply machine learning models to historical accounting variable data to estimate risk-return metrics – specifically, expected excess returns, price volatility and (pairwise) price correlation – of private companies, which should allow the construction of Mean-Variance optimized portfolios consisting of private companies. We attain out-of-sample 𠑅2 s around 45%, while linear regressions yield 𠑅2 s of only about 10%. This short paper is the result of a real-world consulting project on behalf of Votorantim S.A (“VSA†), a multinational holding company. To the authors’ best knowledge this is a novel application of machine learning in the finance literature.

Suggested Citation

  • Elias Cavalcante-Filho & Flavio Abdenur, Rodrigo De Losso, 2018. "Machine learning applied to accounting variables yields the risk-return metrics of private company portfolios," Working Papers, Department of Economics 2018_23, University of São Paulo (FEA-USP).
  • Handle: RePEc:spa:wpaper:2018wpecon23
    as

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    File URL: http://www.repec.eae.fea.usp.br/documentos/Cavalcante_Abdenur_DeLosso_23WP.pdf
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    References listed on IDEAS

    as
    1. Kursa, Miron B. & Rudnicki, Witold R., 2010. "Feature Selection with the Boruta Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i11).
    2. LAVEREN, Eddy & DURINCK, Eduard & DE CEUSTER, Marc & LYBAERT, Nadine, 1997. "Can accounting variables explain any beta? The empirical association between various betas and nine accounting variables in Belgian listed firms," Business Economics Working Papers 1997006, University of Antwerp, Faculty of Business and Economics.
    3. Bowman, Robert G, 1979. "The Theoretical Relationship between Systematic Risk and Financial (Accounting) Variables," Journal of Finance, American Finance Association, vol. 34(3), pages 617-630, June.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    assent pricing; Machine Learning; Portfolio Theory;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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