Another look at portfolio optimization with mental accounts

Das et al. (2010, 2018)[11,12] numerically solve the portfolio optimization with mental accounts (POMA) problem, which maps the mean-variance theory and mean-variance utility into a behavioral portfolio theory. We derive a POMA closed-form solution based on the maximum Sharpe ratio and minimum value-at-risk (VaR) rule. The extension offers an alternate equivalence between the POMA problem, the mean-VaR model, and the generalized Sharpe measure. From the manageable VaR-measure perspective, our evidence indicates that many efficient portfolios are statistically equivalent to the global minimum variance portfolio under the estimation risk. (C) 2021 Elsevier Inc. All rights reserved.

Automated summary

Das et al. (2010, 2018) numerically solve the portfolio optimization with mental accounts (POMA) problem and derive a closed-form solution based on the maximum Sharpe ratio and minimum value-at-risk (VaR) rule. The study finds that many efficient portfolios are statistically equivalent to the global minimum variance portfolio under estimation risk.