We implement a dynamically regularized, bootstrapped two-stage out-of-sample parametric portfolio policy to evaluate characteristics’ efficacy in the conditional stock return-generating process in the metric of expected power utility. Traditional characteristics, such as momentum and size afforded large utility gains before 1999. These opportunities have since vanished. Overfitting—imprecision in weight estimation—is correlated with the optimal portfolio’s variance. Therefore, it is not a problem for power utility investors with coefficients of relative aversion greater than four. For more risk-tolerant investors, we successfully reduce estimation error by increasing the curvature of the loss function relative to the investor’s utility function. (JEL L200; C110; C350)

中文翻译：

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特征和最佳投资组合的实证评估

我们实施动态正则化、自举两阶段样本外参数投资组合策略，以评估预期电力效用指标中的条件股票收益生成过程中特征的功效。 1999 年之前，势头和规模等传统特征带来了巨大的效用收益。但此后这些机会就消失了。过度拟合（权重估计的不精确）与最优投资组合的方差相关。因此，对于相对厌恶系数大于4的电力投资者来说，这不是问题。对于更具风险承受能力的投资者，我们通过增加损失函数相对于投资者效用函数的曲率成功地减少了估计误差。 （JEL L200；C110；C350）