Stock Evaluation Using a Preference Disaggregation Methodology
提出一种基于偏好分解的多准则决策方法，通过序数回归和线性规划构建加性效用函数，用于股票评估和投资组合选择，并以雅典证券交易所98只股票为例验证其有效性。
ABSTRACT This paper presents a real application of a multicriteria decision aid (MCDA) approach to portfolio selection based on preference disaggregation, using ordinal regression and linear programming (UTADIS method; UTilités Additives DIScriminantes). The additive utility functions that are derived through this approach have the extrapolation ability that any new alternative (share) can be easily evaluated and classified into one of several user‐predefined groups. The procedure is illustrated with a case study of 98 stocks from the Athens stock exchange, using 15 criteria. The results are encouraging, indicating that the proposed methodology could be used as a tool for the analysis of the portfolio managers' preferences and choices. Furthermore, the comparison with multiple discriminant analysis (either using a stepwise procedure or not) illustrates the superiority of the proposed methodology over a well‐known multivariate statistical technique that has been extensively used to study financial decision‐making problems.