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

M. Hashem Pesaran, Ron P. Smith

arXiv 3 May 2024 · Econometrics · publishedJournal of Financial Econometrics (2024)

arXiv:2405.02217 · PDF · DOI · OpenAlex · Extracted main text

Abstract

The risk premia of traded factors are the sum of factor means and a parameter vector we denote by {\phi} which is identified from the cross section regression of alpha of individual securities on the vector of factor loadings. If phi is non-zero one can construct "phi-portfolios" which exploit the systematic components of non-zero alpha. We show that for known values of betas and when phi is non-zero there exist phi-portfolios that dominate mean-variance portfolios. The paper then proposes a two-step bias corrected estimator of phi and derives its asymptotic distribution allowing for idiosyncratic pricing errors, weak missing factors, and weak error cross-sectional 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 500 portfolio.

Citation extraction

70
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in-text mentions
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distinct cited
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main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Shanken (1992) On the estimation of beta-pricing models1.00073100%
2Bailey, Kapetanios, and Pesaran (2021) Measurement of factor strength: theory and practice self0.9416583%
3Chen and Zimmermann (2022) Open source cross-sectional asset pricing0.9285380%
4Giglio, Xiu, and Zhang (2023) Test assets and weak factors0.92843100%
5Giglio and Xiu (2021) Asset pricing with omitted factors0.84333100%
6Fan, Liao, and Mincheva (2011) High dimensional covariance matrix estimation in approximate factor models0.81142100%
7Ross (1976) The arbitrage theory of capital asset pricing0.73732100%
8Chamberlain and Rothschild (1983) Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets0.73732100%
9Fan, Liao, and Mincheva (2013) Large covariance estimation by thresholding principal orthogonal complements0.73732100%
10Jagannathan, Skoulakis, and Wang (2010) The analysis of the cross-section of security returns0.73732100%

Showing the top 10 of 70 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1How weak are weak factors? Uniform inference for signal strength in signal plus noise models0.40511