Expected Utility Regret Rule: Minimax and Bayes Optimal Portfolio Choice
Abstract
This study considers the problem of portfolio choice, where we recommend a portfolio to an investor to maximize the expected utility of their wealth. Our goal is to construct an asymptotically optimal portfolio choice rule in terms of expected utility regret, the difference between the expected utility of an oracle investor and that achieved by a portfolio chosen from data. We propose the Expected Utility Regret (EUR) rule, which jointly selects a portfolio class and estimates its weights. In a regular parametric return model, a single EUR rule attains both the minimax and the Bayes lower bounds, including their leading constants, without using the prior distribution that defines the Bayes criterion. We then derive the mean--variance and risk-parity portfolios as special cases of this framework. Under smooth increasing and concave utility, the EUR rule and the sample mean--variance portfolio attain the same leading expected regret when expected excess returns approach zero sufficiently fast. When the returns divided by their volatilities have a joint distribution that does not depend on the order of the assets, the EUR rule and the risk-parity portfolio coincide.
Related
- Expected Minimax Regret Rates for Adaptive LQG Control on Fixed Parameter Sets
- Simple-regret rates and minimax optimality of fixed-prior expected improvement in Matérn and squared-exponential RKHSs
- Bandits with Multiple Optimal Arms: Minimax Regret and Non-Adaptivity
- Closing the Log Gap: Minimax-Optimal Regret for Episodic RL
- Nearly Minimax Optimal Regret for Adversarial Linear Bandits with Strong Corruptions
BibTeX
@misc{kato2026expected,
title = {{Expected Utility Regret Rule: Minimax and Bayes Optimal Portfolio Choice}},
author = {Masahiro Kato},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.02290},
eprint = {2610.02290},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.02290},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Expected Utility Regret Rule: Minimax and Bayes Optimal Portfolio Choice
AU - Masahiro Kato
PY - 2026
DA - 2026/10/01
PB - arXiv
DO - 10.48550/arxiv.2610.02290
UR - https://arxiv.org/abs/2610.02290
AB - This study considers the problem of portfolio choice, where we recommend a portfolio to an investor to maximize the expected utility of their wealth. Our goal is to construct an asymptotically optimal portfolio choice rule in terms of expected utility regret, the difference between the expected utility of an oracle investor and that achieved by a portfolio chosen from data. We propose the Expected Utility Regret (EUR) rule, which jointly selects a portfolio class and estimates its weights. In a regular parametric return model, a single EUR rule attains both the minimax and the Bayes lower bounds, including their leading constants, without using the prior distribution that defines the Bayes criterion. We then derive the mean--variance and risk-parity portfolios as special cases of this framework. Under smooth increasing and concave utility, the EUR rule and the sample mean--variance portfolio attain the same leading expected regret when expected excess returns approach zero sufficiently fast. When the returns divided by their volatilities have a joint distribution that does not depend on the order of the assets, the EUR rule and the risk-parity portfolio coincide.
ER -