基于GM(1,1,μ,ν)模型的股指预测

物流企业客户违约及其变化过程具有马尔可夫性。在利用经典算法预测违约损失值的基础上，将违约损失值作为影响因素，借鉴隐马尔可夫理论，构建基于影响因素的物流企业客户违约风险评估模型。通过该模型可以计算得到某一时刻物流企业服务的每个客户的违约风险及其风险变化指数和物流企业面临的平均违约风险及其变化指数。算例计算结果表明，该评估模型能够准确度量客户违约风险，并具有可行性和易操作性。

Client Default Risk Assessment of Logistics Enterprises based on Hidden Markov Model

Client default of logistics enterprises has Markov characteristics. This paper uses the classical algorithms to forecast the default loss. A client default risk assessment model, which considers the default loss as factors, is built based on Hidden Markov Model. The model proposed can be used to forecast the default risk and its variability index of each client and the average default risk and its variability index of all clients. The calculation result shows that the new model can assess the client default risk precisely and is feasible.