论文部分内容阅读
为了克服静态CVaR模型的不足,且试图为实现投资组合的最优配置以权衡期望财富和尾部风险提供更贴近现实的方案,文中提出了多期的均值-CVaR模型,并给出了正态条件分布和一般条件分布情形下模型的转化和推导。
In order to overcome the shortcomings of the static CVaR model and attempt to provide a more realistic solution to the optimal allocation of the portfolio to weigh the expected wealth and the tail risk, a multi-period mean-CVaR model is proposed and the normal conditions Transformation and derivation of model under the distribution and general condition distribution.