基于非线性时间序列与极值理论的Shibor市场风险度量研究

发布时间：2019-01-12 06:33

【摘要】：利率市场化的加速，使金融机构不得不关注利率带来的市场风险。上海银行间同业拆借利率作为中国重要的银行间同业拆借利率，选择适当的模型来衡量上海银行间同业拆借利率风险，对银行利率风险管理具有重要的意义本文在研究上海银行间同业拆借利率这一金融时间序列时，不仅考虑了传统的尖峰厚尾性、集聚性，还注意到其不对称性、周期性、波动的跳跃性等，为此，本文不仅引入了模拟厚尾性、集聚性的极值理论、GARCH模型，还引入了非线性时间序列分析的门限自回归模型来度量不对称性、周期性、波动的跳跃性，形成了TAR-GARCH-POT模型，并通过实证分析，与传统的线性时间序列模型AR-GARCH-POT模型，，极值除串模型相比较，计算三个模型的VaR和CVaR值，并通过回测检验得到，TAR-GARCH-POT模型能够更好的模拟上海银行间同业拆借利率的风险。
[Abstract]:With the acceleration of interest rate marketization, financial institutions have to pay attention to the market risk brought by interest rate. Shanghai Interbank offered rate (SAIBOR) is an important interbank offered rate in China. The appropriate model is chosen to measure the risk of Shanghai Interbank offered rate. This paper studies the financial time series of Shanghai Interbank offered rate, which not only considers the traditional peak and thick tail, but also notes its asymmetry and periodicity. For this reason, this paper not only introduces the extreme value theory of simulating thick tail, agglomeration, GARCH model, but also introduces threshold autoregressive model of nonlinear time series analysis to measure asymmetry, periodicity and jump of fluctuation. The TAR-GARCH-POT model is formed and compared with the traditional linear time series model (AR-GARCH-POT model), the VaR and CVaR values of the three models are calculated by comparison with the traditional linear time series model (AR-GARCH-POT model). TAR-GARCH-POT model can better simulate the risk of Shanghai Interbank offered rate.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F832.5;F224

【参考文献】