Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/331341 
Year of Publication: 
2025
Series/Report no.: 
Tinbergen Institute Discussion Paper No. TI 2025-045/III
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
We propose a methodology to construct tests for the null hypothesis that the pricing errors of a panel of asset returns are jointly equal to zero in a linear factor asset pric- ing model - that is, the null of "zero alpha". We consider, as a leading example, a model with observable, tradable factors, but we also develop extensions to accommodate for non- tradable and latent factors. The test is based on equation-by-equation estimation, using a randomized version of the estimated alphas, which only requires rates of convergence. The distinct features of the proposed methodology are that it does not require the estimation of any covariance matrix, and that it allows for both N and T to pass to infinity, with the former possibly faster than the latter. Further, unlike extant approaches, the procedure can accommodate conditional heteroskedasticity, non-Gaussianity, and even strong cross- sectional dependence in the error terms. We also propose a de-randomized decision rule to choose in favor or against the correct specification of a linear factor pricing model. Monte Carlo simulations show that the test has satisfactory properties and it compares favorably to several existing tests. The usefulness of the testing procedure is illustrated through an application of linear factor pricing models to price the constituents of the S&P 500.
Subjects: 
Capital market return
panel
stock index
statistical test
statistical error
USA
Document Type: 
Working Paper

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