Factor models with many assets: strong factors, weak factors, and the two-pass procedure

Stanislav Anatolyev and Anna Mikusheva

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Abstract: This paper re-examines the problem of estimating risk premia in linear factor pricing models. Typically, the data used in the empirical literature are characterized by weakness of some pricing factors, strong cross-sectional dependence in the errors, and (moderately) high cross-sectional dimensionality. Using an asymptotic framework where the number of assets/portfolios grows with the time span of the data while the risk exposures of weak factors are local-to-zero, we show that the conventional two-pass estimation procedure delivers inconsistent estimates of the risk premia. We propose a new estimation procedure based on sample-splitting instrumental variables regression. The proposed estimator of risk premia is robust to weak included factors and to the presence of strong unaccounted cross-sectional error dependence. We derive the many-asset weak factor asymptotic distribution of the proposed estimator, show how to construct its standard errors, verify its performance in simulations, and revisit some empirical studies.

Date: 2018-07, Revised 2019-04
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (4)

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Journal Article: Factor models with many assets: Strong factors, weak factors, and the two-pass procedure (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1807.04094

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