An Empirical Assessment of Characteristics and Optimal Portfolios

56 Pages Posted: 12 Apr 2018 Last revised: 12 Aug 2022

See all articles by Christopher G. Lamoureux

Christopher G. Lamoureux

University of Arizona

Huacheng Zhang

Nottingham University Business School

Date Written: January 26, 2018

Abstract

We show that overfitting plagues optimal portfolios obtained by linking weights directly to characteristics. We effectively mitigate overfitting (regularize) by optimizing a more concave loss function than the investor’s utility function. Significant certainty equivalent gains over benchmarks
require at least three characteristics: momentum, size, and residual volatility. Out-of-sample
utility gains are due to characteristic complementarities and depend on investor risk aversion.
For example, conditioning on momentum relieves the overfitting bias inherent in the other characteristics for our most risk-averse investor. Optimal portfolios’ returns lie largely outside the span of traditional factors and move closer to the market as risk-aversion increases.

Keywords: cross-section of stock returns; stock characteristics; optimal portfolios

JEL Classification: G10, G11

Suggested Citation

Lamoureux, Christopher G. and Zhang, Huacheng, An Empirical Assessment of Characteristics and Optimal Portfolios (January 26, 2018). Available at SSRN: https://ssrn.com/abstract=3018499 or http://dx.doi.org/10.2139/ssrn.3018499

Christopher G. Lamoureux (Contact Author)

University of Arizona ( email )

Tucson, AZ 85721
United States
520-621-7488 (Phone)
520-621-1261 (Fax)

Huacheng Zhang

Nottingham University Business School ( email )

Business School South
Nottingham, Nottinghamshire NG81DD
United Kingdom

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