Forward Selection Fama-MacBeth Regression with Higher Order Asset-Pricing Factors / Nicola Borri, Denis Chetverikov, Yukun Liu, Aleh Tsyvinski.

Format:

Book

Author/Creator:

Borri, Nicola.

Contributor:

Chetverikov, Denis.

Liu, Yukun.

Tsyvinski, Aleh.

National Bureau of Economic Research.

Series:

Working Paper Series (National Bureau of Economic Research) no. w33663.

NBER working paper series no. w33663

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2025.

Summary:

We show that the higher-orders and their interactions of the common sparse linear factors can effectively subsume the factor zoo. We propose a forward selection Fama-MacBeth procedure as a method to estimate a high-dimensional stochastic discount factor model, isolating the most relevant higher-order factors. Applying this approach to terms derived from six widely used factors (the Fama-French five-factor model and the momentum factor), we show that the resulting higher-order model with only a small number of selected higher-order terms significantly outperforms traditional benchmarks both in-sample and out-of-sample. Moreover, it effectively subsumes a majority of the factors from the extensive factor zoo, suggesting that the pricing power of most zoo factors is attributable to their exposure to higher-order terms of common linear factors.

Notes:

April 2025.

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