论文部分内容阅读
VaR(value at risk)的测算精度一直是业界和学术关注热点问题.本文应用定义的经济测度距离和引力空间权重矩阵,建立广义多维空间计量模型捕捉金融系统的空间效应信息,构造S-VaR(saptial-value at risk),提高VaR的测算精度.以S&P亚洲50指数作为股票资产组合替代变量进行实证分析,结果表明:广义多维空间效应S-VaR能捕捉金融市场存在的多维空间相关性和风险的空间溢出效应,提高了VaR模型在风险预测中的精确性.
The measurement accuracy of VaR (value at risk) has always been a hot issue in industry and academia.In this paper, a generalized multidimensional spatial econometric model is built to capture the spatial effect information of financial system by using the defined economic measure distance and gravity space weight matrix to construct S-VaR saptial-value at risk) to improve the accuracy of VaR.The empirical analysis based on the S & P Asia 50 index as an alternative to stock portfolio shows that the generalized multi-dimensional space effect S-VaR can capture the multidimensional spatial correlation and risk in financial markets The spatial spillover effect improves the accuracy of the VaR model in risk prediction.