论文标题
RM-CVAR：正规化多个$β$ -CVAR投资组合
RM-CVaR: Regularized Multiple $β$-CVaR Portfolio
论文作者
论文摘要
为投资者找到最佳投资组合的问题称为投资组合优化问题。此类问题主要涉及回报的期望和可变性（即平均值和差异）。尽管差异将是要最小化的最基本风险措施，但它具有几个缺点。有条件的价值风险（CVAR）是一种相对较新的风险措施，可以解决众所周知的与方差相关的风险指标的某些缺点，并且由于其计算效率，它已获得了普及。 CVAR定义为超出一定概率水平（$β$）的损失的预期值。但是，使用CVAR作为风险度量的投资组合优化问题是用单个$β$制定的，并且可能会根据选择$β$的方式产生明显不同的投资组合。我们确认即使$β$的小变化也可能导致整个投资组合结构的巨大变化。为了改善此问题，我们提出了RM-CVAR：正规化多个$β$ -CVAR投资组合。我们对众所周知的基准进行实验，以评估所提出的投资组合。与各种投资组合相比，RM-CVAR表现出较高风险调整后的回报和最大最大减收率的出色表现。
The problem of finding the optimal portfolio for investors is called the portfolio optimization problem. Such problem mainly concerns the expectation and variability of return (i.e., mean and variance). Although the variance would be the most fundamental risk measure to be minimized, it has several drawbacks. Conditional Value-at-Risk (CVaR) is a relatively new risk measure that addresses some of the shortcomings of well-known variance-related risk measures, and because of its computational efficiencies, it has gained popularity. CVaR is defined as the expected value of the loss that occurs beyond a certain probability level ($β$). However, portfolio optimization problems that use CVaR as a risk measure are formulated with a single $β$ and may output significantly different portfolios depending on how the $β$ is selected. We confirm even small changes in $β$ can result in huge changes in the whole portfolio structure. In order to improve this problem, we propose RM-CVaR: Regularized Multiple $β$-CVaR Portfolio. We perform experiments on well-known benchmarks to evaluate the proposed portfolio. Compared with various portfolios, RM-CVaR demonstrates a superior performance of having both higher risk-adjusted returns and lower maximum drawdown.
