基于扭曲风险度量的鲁棒投资策略

Worst-Case Distortion Risk Measure with Application to Robust Portfolio Selection

投资组合策略在很大程度上取决于损失的基本分布.因此当损失的分布信息只能通过有限的数据样本来观察时,投资组合策略模型的稳健性是至关重要的.假设损失的基本分布具有已知的均值和方差且位于一个以经验分布为中心,以Wasserstein距离为半径的球内,本文建立了一个基于扭曲风险度量的稳健投资组合策略模型,并将其转化为更简便的等价形式.此外,本文运用模拟和实证研究证明了该模型的有效性.

Portfolio selection depends heavily on the underlying distribution of loss.When the distribution information of loss can only be observed through a limited sample of data,robustness of the portfolio selection model is of crucial importance.Assuming that the underlying distribution of loss has a known mean and variance and lies within a ball centred on the reference distribution with the Wasserstein distance as the radius,this paper proposes a robust portfolio strategy model based on the distortion risk measure and translates it into a simpler equivalent form.Furthermore,simulation and empirical study are used to demonstrate the validity of the model.