【摘要】 针对Black-Litterman模型中投资者观点难以量化的问题,本文提出一种基于TOPSIS方法的多指标排序信息下的Black-Litterman模型.首先通过TOPSIS方法对具有多个指标属性的资产进行排序,从而获得量化的观点.然后采用最新的随机最优化思想求解最优化问题,确定资产的组合权重.最后对构建的模型进行实证研究,选取上海证券交易所交易的十只个股进行资产配置.实证结果显示:与传统的投资组合方法相比,新方法可以有效的将价格以外的信息结合进来,从而提高了模型的稳健性和运用范围.更多还原

【Abstract】 In order to solve the problem that the viewpoints of investors are difficult to be quantified in Black-Litterman model, we propose a new model incorporated in multi-indicators sequencing based on the TOPSIS method. Firstly, quantitative viewpoint matrix is determined by using the multi-indicators sequence of assets, which is designed based on TOPSIS. Secondly,we apply the means of latest stochastic optimization to obtain the weights of portfolio. Finally,empirical research is studied by selecting several stocks in Shanghai Stock Exchange Market used for asset allocation. Empirical results reveal that as compared with other traditional portfolio methods, our new means can effectively include additional information except price, which leads to improvement of the robustness and application of the proposed model.更多还原