摘要：In this paper,a fuzzy volatility labeling algorithm is offered to detect the periods with abnormal activities on daily share returns. Considering the vagueness in the switches of the time periods,the membership functions of high and normal volatility classes are introduced. In the assignments,both the density structure and membership degree are used.It is believed that this algorithm may be helpful to construct different estimation models for the time periods with normal and abnormal activities.Authors offer algorithm,which can be used as a tool for sustainable risk management.
