An Empirical Assessment of Characteristics and Optimal Portfolios

55 Pages Posted: 12 Apr 2018 Last revised: 30 Apr 2021

See all articles by Christopher G. Lamoureux

Christopher G. Lamoureux

University of Arizona

Huacheng Zhang

Southwestern University of Finance and Economics - Institute of Financial Studies

Date Written: January 26, 2018

Abstract

We analyze characteristics' joint predictive information through the lens of out-of-sample power
utility functions. Linking weights to characteristics to form optimal portfolios suffers from estimation
error which we mitigate by maximizing an in-sample loss function that is more concave than
the utility function. While no single characteristic can be used to enhance utility by all investors,
conditioning on momentum, size, and residual volatility produces portfolios with significantly
higher certainty equivalents than benchmarks for all investors. Characteristic complementarities
produce the benefits, for example momentum mitigates overfitting inherent in other characteristics.
Optimal portfolios? returns lie largely outside the span of traditional factors.

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

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

Southwestern University of Finance and Economics - Institute of Financial Studies ( email )

55 Guanghuacun St,
Chengdu, Sichuan 610074
China

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