混合状态变量和过程变量的风险评估模型

针对常用风险评估方法仅使用单期截面数据构造模型,对风险动态演化趋势信息反映能力不足的问题,提出一种同时考虑单期截面数据和时间序列数据的企业风险评估模型.对于可用单期截面数据表示的状态变量,采用S型函数度量该类指标的风险;对于需要用时间序列数据反映的过程变量,综合考虑该类指标的时间序列均值、方差或偏度等特征,将包含企业风险演化趋势信息的时间序列数据映射为一个截面值,从而使风险评估模型具有处理动态信息的能力.应用实例表明了该方法的可行性和有效性.

Risk evaluation model for mixed state variables and process variables

For the problem that the commonly used risk evaluation model only uses cross-sectional data and the trend
information of evolution is not fully reflected in the risk evaluation models, a risk evaluation model based on the risk of
specific indexes is proposed. For the state variables that can be reflected with cross sectional data, the risks are measured
through Sigmoid function. For the process variables that need to be reflected with time series data, the risks are measured by
using two-attribute models and value-at-risk models. By considering the mean, variance and skewness, the time series data
are mapped to a cross section data such that the risk evaluation model has the ability to handle the dynamic information. A
specific example shows the feasibility and effectiveness of the proposed method.