Identifying and exploiting alpha in linear asset pricing models with strong, semi-strong, and latent factors

Pesaran, M.H. and Smith, Ron (2024) Identifying and exploiting alpha in linear asset pricing models with strong, semi-strong, and latent factors. Journal of Financial Econometrics , ISSN 1479-8409. (In Press)

Abstract

The risk premia of traded factors are the sum of factor means and a parameter vector we denote by which is identi ed from the cross-section regression of i on the vector of factor loadings, i. If is non-zero, then i are non-zero and one can construct "phi-portfolios" which exploit the systematic components of non-zero alpha. We show that for known values of i and when is non-zero there exist phi-portfolios that dominate mean-variance portfolios. The paper then proposes a two-step bias corrected estimator of and derives its asymptotic distribution allowing for idiosyncratic pricing errors, weak missing factors, and weak error crosssectional dependence. Small sample results from extensive Monte Carlo experiments show that the proposed estimator has the correct size with good power properties. The paper also provides an empirical application to a large number of U.S. securities with risk factors selected from a large number of potential risk factors according to their strength and constructs phi-portfolios and compares their Sharpe ratios to mean variance and S&P portfolios.

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