基于前景云的不确定语言多准则国际股指投资群决策

针对投资决策过程中语言评价值具有随机性及模糊性,以及投资者的决策容易受到其情绪的影响且不同投资者受到的影响程度不同,本文提出基于前景云的不确定语言多准则投资群决策方法,并将其运用在国际股指投资中。其中,前景理论模型用来刻画投资者情绪对决策的影响,而云模型用来刻画语言评价值模糊性和随机性之间的关联。更具体来说,论文首先解决传统文献云生成方法中云期望值超过论域或者无法区分语言评价标度等级等问题,然后构建了前景云模型并将该模型应用于多个专家共同进行的国际股指投资群决策。实证结果显示,该模型得出的决策结果比传统决策方法下的结果更直观、可靠,表现为决策依据不仅考虑方案的期望值大小及变动风险,而且还考虑了投资者情绪对决策的影响。由此可得出,本文所提出的模型更符合现实情景,也更能有效实现对投资群决策。

Uncertain-language Multi-criteria Group Decision Making Based on Prospect-Cloud Model for Stock Indices Investment in International Wide

In view of the randomness and ambiguity of linguistic information in the process of investment decision, and the behavior of investors are easily affected by their sentiment at different degrees, this paper puts forward an uncertain-linguistic multi-criteria group investment decision based on the prospect-cloud model for international stock indices. In the method of decision, the prospect theory model can describe the influence of investment sentiment, while the cloud one can capture the association of ambiguity and randomness in linguistic evaluations. More specifically, after solving the problems that the cloud expectation exceeds the universe and the linguistic scale that cannot be distinguished in the existing cloud-generation methods, this paper proposes a prospect-cloud model and applies it to the empirical analysis for international stock-index investment decisions by group experts. The empirical result shows that the investment decision making based on the prospect-cloud model is more intuitive and reliable than the existing one. Since the former not only confers to the expectation, but also the risk of investment as well as investment sentiment. Thus, it can be concluded that our proposed model performs better in practice and is more effective to group decision of investment.