# Characteristic-Sorted Portfolios: Estimation and Inference

arXiv: https://arxiv.org/abs/1809.03584 · HTML: https://mlsanity.com/paper/1809.03584/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Sep 2018.

## Built on by (most cited first, 1 of 1)

- [QuantBench: Benchmarking AI Methods for Quantitative Investment](https://mlsanity.com/paper/2504.18600/) (2025)

## Abstract (arXiv)

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 5 or 10. To illustrate the relevance of our results, we revisit the size and momentum anomalies.