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The purpose of this paper is to test the new Fama and French (2015) five-factor model relying on a thorough sample of hedge fund strategies drawn from the Barclay’s Global hedge fund database.

The authors use a stepwise regression to identify the factors of the q-factor model which are relevant for the hedge fund strategy analysis. Doing so, the authors account for the Fung and Hsieh seven factors which prove very useful in the explanation of the hedge fund strategies. The authors introduce interaction terms to depict any interaction of the traditional Fama and French factors with the factors associated with the q-factor model. The authors also examine the dynamic dimensions of the risk-taking behavior of hedge funds using a BEKK procedure and the Kalman filter algorithm.

The results show that hedge funds seem to prefer stocks of firms with a high investment-to-assets ratio (low conservative minus aggressive (CMA)), on the one hand, and weak firms’ stocks (low robust minus weak (RMW)), on the other hand. This combination is not associated with the conventional properties of growth stocks – i.e., low high minus low (HML) stocks – which are related to firms which invest more (low CMA) and which are more profitable (high RMW). Finally, small minus big (SMB) interacts more with RMW while HML is more correlated with CMA. The conditional correlations between SMB and CMA, on the one hand, and HML and RMW, on the other hand, are less tight and may change sign over time.

To the best of the authors’ knowledge, the authors are the first to cast the new Fama and French five-factor model in a hedge fund setting which account for the Fung and Hsieh option-like trading strategies. This approach allows the authors to better understand hedge fund strategies because q-factors are useful to study the dynamic behavior of hedge funds.