Ambiguity, Prudence, and Optimal Portfolio Choice: Beyond Robust Mean–Variance Analysis

I extend the robust mean-variance portfolio analysis proposed by Maccheroni et al. (2013) by examining how ambiguity prudence affects optimal stock allocation when portfolios are evaluated using the smooth ambiguity model. Ambiguity prudence reflects an aversion to model uncertainty that intensifies as the investor believes unfavorable events to be more likely. I derive a higher-order approximation of the certainty equivalent to disentangle the contributions of preferences and beliefs in payoff valuation. Ambiguity prudence introduces nonlinearities into the investor’s valuation, leading to sizable deviations from the robust mean-variance solution and to underreaction (overreaction) to positive news when concerns about downside model uncertainty are high (low)