Naïve Markowitz policies
研究连续时间下天真型投资者在均值-方差投资组合模型中不断重新优化的策略，发现其预期收益高于原计划但风险效率较低，且风险暴露高于均衡策略。
Abstract We study a continuous‐time Markowitz mean–variance portfolio selection model in which a naïve agent, unaware of the underlying time‐inconsistency, continuously reoptimizes over time. We define the resulting naïve policies through the limit of discretely naïve policies that are committed only in very small time intervals, and derive them analytically and explicitly. We compare naïve policies with pre‐committed optimal policies and with consistent planners' equilibrium policies in a Black–Scholes market, and find that the former achieve higher expected terminal returns than originally planned yet are mean–variance inefficient when the risk aversion level is sufficiently small, and always take strictly riskier exposure than equilibrium policies. We finally define an efficiency ratio for comparing return–risk tradeoff with the same original level of risk aversion, and show that naïve policies are always strictly less efficient than pre‐committed and equilibrium policies.