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<p>This paper examines the predictive value of fast-and-frugal trees modelling embeding thefive factors suggested by model. We examine a fast-andfrugaltrees predictive model of returns upon stock traded on the S&amp;P500 over the years2010 to 2024. We allow for three variations in the predictive context of the fast-and-frugaltrees used:<OrderedList> <ListItem> <ItemNumber>•</ItemNumber> <ItemContent> <p>Skewness in the coefficients of the Fama-French models OLS regressionestimates</p> </ItemContent> </ListItem> <ListItem> <ItemNumber>•</ItemNumber> <ItemContent> <p>Analysts following the chosen firm/industry sector.</p> </ItemContent> </ListItem> <ListItem> <ItemNumber>•</ItemNumber> <ItemContent> <p>Market value of the firm or sector examined.We find the FFT model is a worthy competitor to regression models in predictingstock returns for the S&amp;P 500 in our sample period, especially in terms of theconsistent nature of the predictions across sectoral groups. But a logisticregression alternative outperforms both OLS and our fast-and-frugal-tree inpredicting S&amp;P 500 returns in our sample period.</p> </ItemContent> </ListItem> </OrderedList></p>

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Potential of fast and frugal trees in factor investing on the US equity market

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月19日

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  • William Forbes,
  • Egor Kiselev,
  • Len Skerratt

摘要

This paper examines the predictive value of fast-and-frugal trees modelling embeding thefive factors suggested by model. We examine a fast-andfrugaltrees predictive model of returns upon stock traded on the S&P500 over the years2010 to 2024. We allow for three variations in the predictive context of the fast-and-frugaltrees used: •

Skewness in the coefficients of the Fama-French models OLS regressionestimates

•

Analysts following the chosen firm/industry sector.

 •

Market value of the firm or sector examined.We find the FFT model is a worthy competitor to regression models in predictingstock returns for the S&P 500 in our sample period, especially in terms of theconsistent nature of the predictions across sectoral groups. But a logisticregression alternative outperforms both OLS and our fast-and-frugal-tree inpredicting S&P 500 returns in our sample period.