Research of market interest rates of the SHIBOR based on regime switching model
Liu Xiangdong and Guo Hui

Liu Xiangdong and Guo HuiDepartment of Statistics, Jinan University, Guangzhou 510632, P.R.China

application of statistical mathematics; Markov regime switching; generalized autoregressive conditional heteroskedasticity(GARCH); Shanghai interbank offered rate(SHIBOR); term structure of interest rates; fixed volatility; single regime model

DOI: 10.3724/SP.J.1249.2015.03317


基于固定波动率模型和广义自回归条件异方差(generalized autoregressive conditional heteroskedasticity,GARCH)模型,研究引入马氏市道轮换模型. 该模型可以将线性利率期限结构推广到非线性形式,运用到资产定价的变化中,特别是债券收益率的确定中.不同于唯一依赖利率水平的传统模型,马氏市道轮换模型能够模拟货币政策对利率的影响.利用2006-10-08至2013-03-29每周三上海银行间同业拆放利率(Shanghai interbank offered rate,SHIBOR)月度数据,用R语言实现并比较了固定波动率模型、GARCH模型以及混合GARCH马氏市道轮换模型对各参数的估计效果.结果表明,混合GARCH马氏市道轮换模型的拟合效果在各种情形下均占优.

In this paper, a new model, the Markov regime switching model, based on the fixed volatility model and the generalized autoregressive conditional heteroskedasticity(GARCH)model is introduced. In the Markov regime switching model, the linear term structure of interest rates can be extended to nonlinear form. The Markov regime switching model can be used to estimate the dynamics of asset prices, especially the bond yields. Different from the traditional model, which only depends on the level of interest rates, a state variable is introduced in the regime switching model, and thus the model can indicate the impact of the monetary policy on interest rates. Using the monthly Shanghai interbank offered rate(SHIBOR)data issued every Wednesday from October 8th, 2006 to March 29th, 2013, we use R implement and compare the performances of fixed volatility model, GARCH model, and the mixed GARCH Markov regime switching model in estimating the monthly SHIBOR. The results indicate that the mixed GARCH Markov regime switching model can make good estimations and can be considered as the best one under all circumstances.