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Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities

Mohammad Pesaran and Takashi Yamagata

Discussion Papers from Department of Economics, University of York

Abstract: This paper proposes a novel test of zero pricing errors for the linear factor pricing model when the number of securities, N, can be large relative to the time dimension, T, of the return series. The test is based on Student t tests of individual securities and has a number of advantages over the existing standardised Wald type tests. It allows for non-Gaussianity and general forms of weakly cross correlated errors. It does not require estimation of an invertible error covariance matrix, it is much faster to implement, and is valid even if N is much larger than T. Monte Carlo evidence shows that the proposed test performs remarkably well even when T = 60 and N = 5,000. The test is applied to monthly returns on securities in the S&P 500 at the end of each month in real time, using rolling windows of size 60. Statistically significant evidence against Sharpe-Lintner CAPM and Fama-French three factor models are found mainly during the recent financial crisis. Also we find a significant negative correlation between a twelve-months moving average p-values of the test and excess returns of long/short equity strategies (relative to the return on S&P 500) over the period November 1994 to June 2015, suggesting that abnormal profits are earned during episodes of market inefficiencies.

Keywords: CAPM; Testing for alpha; Weak and spatial error cross-sectional dependence; S&P 500 securities; Long/short equity strategy. (search for similar items in EconPapers)
JEL-codes: C12 C15 C23 G11 G12 (search for similar items in EconPapers)
Date: 2017-04
New Economics Papers: this item is included in nep-ecm and nep-fmk
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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