Expanding the Fama-French Factor Model with the Industry Beta
Anatoly B. Schmidt (NYU Tandon School of Engineering)
August 2023
Recently it was shown that the news-based stock pricing model (NBSPM) outperforms the momentum-enhanced five-factor Fama-French model (FF5M) for a representative list of holdings of the major US equity sector ETFs both in-sample (Schmidt 2023) and out-of-sample (Schmidt 2022). The leading term in NBSPM besides the market (CAPM) beta is the industry beta estimated using returns of the relevant equity sector ETFs or industry ETFs. In this work, the industry beta is added to FF5M. It is found that the resulting model (FF5MI) is generally more accurate in-sample than NBSPM in terms of the mean squared error but not necessarily in terms of the mean absolute error. However, FF5MI is always inferior to NBSPM out-of-sample. This implies that the industry beta has the major impact on stock prices while the FF5M factors may yield an over-fitted model.

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