摘要
为提高长租公寓REITs(房地产信托投资基金)模式融资风险预测精度,建立了一种基于ABC-SVM的长租公寓REITs融资风险预测模型。以房地产REITs共性融资风险为基础,结合长租公寓REITs融资模式的特点,建立了风险评价指标体系;通过设计问卷调查相关专家,经过不断反馈修正,得到所需样本集;基于人工蜂群(ABC)对支持向量机(SVM)进行优化,建立了基于ABC-SVM的风险评价模型。结合实例与SVM及BP神经网络风险预测精度进行对比,发现建立的模型对于融资风险的预测更为准确,可以用于长租公寓REITs模式融资风险评价。
A prediction model of the financing risk based on ABC-SVM is constructed in order to improve the accuracy of the financing risk predication of long lease apartments in REITs(real-estate investment trusts).Firstly,the index system of risk evaluation is established on the basis of the common financing risks of REITs and with the combination of the characteristics of financing patterns of long lease apartments in REITs.Then questionnaires are designed to investigate the concerning experts and the sample sets are obtained after constant feedback and modification.The risk evaluation model based on ABC-SVM is established with the Artificial Bee Colony(ABC)algorithm optimizing the Support Vector Machine(SVM)and comparing the accuracy of risk prediction in the actual cases and that of SVM and Back-Propagation Neural Network(BP).The study finds that the model is more accurate in predicting financing risks,which can be used for the financing risk evaluation of long lease apartment in REITs.
作者
王丽娜
郭平
邱晨展
WANG Lina;GUO Ping;QIU Chenzhan(School of Management Engineering,Qingdao University of Technology,Qingdao 266520,China;Research Center for Smart City Construction and Management in Colleges and Universities in Shandong Province,Qingdao 266520,China)
出处
《河南工业大学学报（社会科学版）》
2020年第4期27-34,共8页
Journal of Henan University of Technology:Social Science Edition
关键词
长租公寓
REITS
人工蜂群算法
支持向量机
风险评价
long lease apartment
REITs
artificial bee colony algorithm
support vector machine
risk evaluation
