Evaluating alternative methods of asset pricing based on the overall magnitude of pricing errors

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Accepted Manuscript (AM)
Author(s)
Shi, Qi
Li, Bin
Griffith University Author(s)
Year published
2019
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We are the first pioneers who evaluate the overall fitness of the two-pass Fama–MacBeth regression and the generalized method of moments (GMM) by comparing the R 2 or mean absolute pricing error (MAE), using a Monte Carlo simulation of different models and portfolios for hundreds of trials and, in particular, focusing on the case that the expected return is always a gross return in both methods. Our findings reveal an innovative finding that both methodologies achieve approximate overall magnitudes of pricing errors.We are the first pioneers who evaluate the overall fitness of the two-pass Fama–MacBeth regression and the generalized method of moments (GMM) by comparing the R 2 or mean absolute pricing error (MAE), using a Monte Carlo simulation of different models and portfolios for hundreds of trials and, in particular, focusing on the case that the expected return is always a gross return in both methods. Our findings reveal an innovative finding that both methodologies achieve approximate overall magnitudes of pricing errors.
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Journal Title
Finance Research Letters
Volume
29
Copyright Statement
© 2019 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
Subject
Banking, finance and investment