基于ANN-CVaR模型的住宅投资风险评价研究

Study on the Residential Risk Investment Evaluation Based on the Ann-CVaR Model

商品住宅的开发投资风险越来越大,建立有效的评价方法和模型已经迫在眉睫。文章定性分析和定量测算相结合,使用BP神经网络和条件在险价值,构建了商品住宅开发投资的风险评价模型。通过整合BP神经网络和CVaR模型的优点,更真实准确地反映住宅投资风险,并做了实证研究。该模型在判断出风险程度的同时给出风险来源,指导商品住宅的投资决策,还为以后研究商品住宅开发投资风险提供了新思路。

With the investment risk of the commercial residential housing increases,the establishment of effective evaluation methods and models is urgent.Combining the qualitative analysis and quantitative estimation,this paper used the BP neural network and the Conditions Value at Risk（CVaR） to develop a residential investment risk evaluation model,which more accurately reflects the investment risk by integrating the advantages of the BP neural network and the CVaR model.The case study was conducted.This model can determine the degree of the risk and indentifies the risk sources,which guides the investment decision-making and provides a new way for the study of the residential investment risk.