positive is the important hypotheses of many financial forecasting models, but the correlation coefficient matrix we get from actual samples are not always positive.
正定性是许多金融预测模型的重要假设前提,然而从实际样本中得到的相关系数矩阵并不能保证其正定性。
a new topsis model which based on the gray correlation coefficient matrix is presented in order to overcome the deficiency in more indicator of decision-making process.
以原始数据样本与理想方案之间的灰色关联系数矩阵为新的决策矩阵,利用理想解法对方案进行排序。
first take the gray correlation coefficient matrix between primitive data sample and ideal scheme as new decision-making matrix, and then use topsis to evaluate and arrange all schemes.
该方法以原始数据样本与理想方案之间的灰色关联系数矩阵为新的决策矩阵,利用理想解法对方案进行排序。
meanwhile, the traditional correlation coefficient matrix can not describe the non-linear relationship between asset prices from the portfolio assets.
同时,传统的相关系数矩阵不能描述资产组合中几项资产价格之间的非线性关系。