Characteristic-Sorted Portfolios: Estimation and Inference

Matias D. Cattaneo; Richard K. Crump; Max H. Farrell; Ernst Schaumburg

doi:10.1162/rest_a_00883

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Characteristic-Sorted Portfolios: Estimation and Inference

Matias D. Cattaneo¹; Richard K. Crump²; Max H. Farrell³; Ernst Schaumburg⁴

¹ Princeton University · ² Federal Reserve Bank of New York · ³ University of Chicago · ⁴ AQR Capital Management

The Review of Economics and Statistics 2020 open access

Portfolio sorting is ubiquitous in the empirical finance literature, where it has been widely used to identify pricing anomalies. Despite its popularity, little attention has been paid to the statistical properties of the procedure. We develop a general framework for portfolio sorting by casting it as a nonparametric estimator. We present valid asymptotic inference methods and a valid mean square error expansion of the estimator leading to an optimal choice for the number of portfolios. In practical settings, the optimal choice may be much larger than the standard choices of five or ten. To illustrate the relevance of our results, we revisit the size and momentum anomalies.

DOI: 10.1162/rest_a_00883
Volume: 102 (3)
Pages: 531-551
Language: en
Export: BibTeX
Sources: openalex crossref