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A neural approach to the value investing tool F-Score

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  • Gimeno, Ruth
  • Lobán, Lidia
  • Vicente, Luis

Abstract

This work is the first neural approach to Piotroski's (2000) F-Score. From the same informative signals, our approach based on network data envelopment analysis allows for (1) overcoming the binary perspective of classification between companies with good/bad fundamentals, and (2) appropriately assessing the existing interaction among a company's main financial areas. The analysis of a complete sample of the largest listed companies in the Eurozone and in the U.S. market in the period 2006–2017 shows that our neural F-Score significantly improves the portfolio returns obtained by the original F-Score.

Suggested Citation

  • Gimeno, Ruth & Lobán, Lidia & Vicente, Luis, 2020. "A neural approach to the value investing tool F-Score," Finance Research Letters, Elsevier, vol. 37(C).
    • Handle: RePEc:eee:finlet:v:37:y:2020:i:c:s1544612319304660
    DOI: 10.1016/j.frl.2019.101367
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    References listed on IDEAS

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