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Open Source Fundamental Industry Classification

Author

Listed:
  • Zura Kakushadze

    (Quantigic® Solutions LLC, 1127 High Ridge Road, #135, Stamford, CT 06905, USA
    Business School & School of Physics, Free University of Tbilisi, 240 David Agmashenebeli Alley, Tbilisi 0159, Georgia
    Disclaimer: This address is used by the corresponding author for no purpose other than to indicate his professional affiliation as is customary in publications. In particular, the contents of this paper are not intended as an investment, legal, tax or any other such advice, and in no way represent views of Quantigic® Solutions LLC, the website www.quantigic.com or any of their other affiliates.)

  • Willie Yu

    (Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore 169857, Singapore)

Abstract

: We provide complete source code for building a fundamental industry classification based on publicly available and freely downloadable data. We compare various fundamental industry classifications by running a horserace of short-horizon trading signals (alphas) utilizing open source heterotic risk models (https://ssrn.com/abstract=2600798) built using such industry classifications. Our source code includes various stand-alone and portable modules, e.g., for downloading/parsing web data, etc.

Suggested Citation

  • Zura Kakushadze & Willie Yu, 2017. "Open Source Fundamental Industry Classification," Data, MDPI, vol. 2(2), pages 1-77, June.
    • Handle: RePEc:gam:jdataj:v:2:y:2017:i:2:p:20-:d:101806
    as

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    References listed on IDEAS

    as
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