基于K-means聚类和广义熵约束的CVaR投资组合模型

CVaR portfolio model based on K-means clustering with the constraint of generalized entropy

构造带有广义熵约束的CVa R投资组合线性规划模型,采用K-means聚类法产生投资组合中各个资产收益率的情景及概率,并把它们代入模型中,得出投资组合的最优投资权数.通过选取深市的8只股票作为投资组合进行实证分析,并与MV模型对比,发现本模型不仅更能体现分散化投资的原则,且收益表现更好,具有较强的实用性.

The present work constructs the CVaR linear programming model of portfolio with the constraint of generalized entropy. We generate scenarios and probabilities of each asset yield in the portfolio using the K-means clustering method. Then we substitute them into the model. Finally we get the optimal investment weights for various assets. The feasibility of this model is certificated by testing a portfolio which contains eight selected stocks in Shenzhen stock market. Compared with MV model,this model not only incorporates more decentralized investment principle,but also has better performance in the future yields. This model has strong practicability.