论文标题
基于投资者厌恶的分销强大的投资组合构建
Distributional Robust Portfolio Construction based on Investor Aversion
论文作者
论文摘要
在行为融资中，厌恶会影响投资者对损益时对未来不确定性的判断。考虑到投资者对损失和风险的厌恶以及表征资产回报的模棱两可的不确定性，我们在风险资产回报的分布的条件下构建了一个分销强大的投资组合模型（DRP）。具体而言，我们的目标是找到最佳的资产组合，以最大程度地提高Wasserstein Ball上最差的效用水平，该效用级别以样本回报的经验分布为中心，球的半径量化了投资者的模棱两可水平。该模型还被称为具有基数限制的混合成分二次编程问题。此外，我们提出了一种混合算法来提高溶液的效率，并使其更适合大规模问题。考虑厌恶的分布鲁棒投资组合模型经验测试了资产分配的出色绩效，我们还比较了共同资产分配策略，以进一步提高投资组合的信誉。
In behavioral finance, aversion affects investors' judgment of future uncertainty when profit and loss occur. Considering investors' aversion to loss and risk, and the ambiguous uncertainty characterizing asset returns, we construct a distributional robust portfolio model (DRP) under the condition that the distribution of risky asset returns is unknown. Specifically, our objective is to find an optimal portfolio of assets that maximizes the worst-case utility level on the Wasserstein ball, which is centered on the empirical distribution of sample returns and the radius of the ball quantifies the investor's ambiguity level. The model is also formulated as a mixed-integer quadratic programming problem with cardinality constraints. In addition, we propose a hybrid algorithm to improve the efficiency of the solution and make it more suitable for large-scale problems. The distributional robust portfolio model considering aversion is empirically tested for superior performance in asset allocation, and we also compare common asset allocation strategies to further enhance the credibility of the portfolio.
