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机构地区:[1]北京化工大学经济管理学院,北京100029 [2]北京化工大学理学院,北京100029
出 处:《系统工程理论与实践》2013年第12期3061-3067,共7页Systems Engineering-Theory & Practice
基 金:国家自然科学基金(71171012;71371024);中央高校基本科研业务费专项资金(ZZ1319;ZZ1320)
摘 要:本文选取上海证券交易所2003年至2010年国债和企业债交易数据,通过遗传算法求解五因子利率期限结构模型,分别得到不同期限国债和企业债的收益率时间序列,然后分别用两因子与四因子仿射过程来刻画国债收益率与企业债收益率的动态变化,从而构建债券信用价差的两因子仿射期限结构模型,并运用卡尔曼滤波法求解模型参数,进而预测出企业债信用价差序列.实证结果表明,该仿射模型能够较好地描述企业债信用价羞的动态变化,可为企业债及其衍生产品的定价提供方法支持.Based on the government bonds and corporate bonds trading data from the Shanghai stock exchange from 2003 to 2010, the time series of the yield of government bonds and corporate bonds to different maturities are obtained by solving five factors term structure model. Then two factors and four factors arlene processes are respectively used to describe the dynamic change of treasury yields and corporate bond yields, and two factors model of ai]~ine term structure of corporate bond are developed. The parameters of the model can be solved with Kalman filtering method, and the dynamic changes of the corporate bond's credit spreads are predicted. Furthermore, the empirical results show that the affine model can describe the dynamic changes of the corporate bond credit spreads relative perfectly, which can provide the method support for pricing corporate bond and its derivates.
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