The purpose of this paper is to test the multi-factor beta model implied by the generalized arbitrage pricing theory ( APT)and the Adaptive Multi-Factor (AMF ) model with the Groupwise Interpretable Basis Selection (GIBS) algorithm , without imposing the exogenous assumption of constant betas. The intercept (arbitrage) tests validate both the AMF and the Fama-French 5-factor (FF5) model. We do the time-invariance tests for the betas for both the AMF model and the FF5 in various time periods. We show that for nearly all time periods with length less than 6 years, the beta coefficients are time-invariant for the AMF model, but not  the FF5 model. The beta coefficients are time-varying for both AMF and FF5 models for longer time periods. Therefore, using the dynamic AMF model with a decent rolling window (such as 5 years) is more powerful and stable than the FF5 model.
The purpose of this paper is to test the time-invariance of the beta coefficients estimated by the Adaptive Multi-Factor (AMF) model. The AMF model is implied by the generalized arbitrage pricing theory ( GAPT), which implies constant beta coefficients. The AMF model utilizes a Groupwise Interpretable Basis Selection (GIBS) algorithm to identify the relevant factors from among all traded ETFs. We compare the AMF model with the Fama-French 5-factor (FF5) model. We show that for nearly all time periods with length less than 6 years, the beta coefficients are time-invariant for the AMF model, but not for the FF5 model. This implies that the AMF model with a rolling window (such as 5 years) is more consistent with realized asset returns than is the FF5 model.
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, without imposing the exogenous assumption of constant betas. The intercept (arbitrage) tests validate both the AMF and
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do the time-invariance tests for the betas for both the AMF model and the FF5 in various time periods. We
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The beta coefficients are time-varying for both AMF and FF5 models for longer time periods. Therefore, using the dynamic
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