An Econometric Model of the Term Structure of Interest Rates Under Regime-Switching Risk

2014 ◽  
pp. 55-83 ◽  
Author(s):  
Shu Wu ◽  
Yong Zeng
Keyword(s):  
Interest Rates ◽  
Term Structure ◽  
Regime Switching ◽  
Econometric Model

scholarly journals A GENERAL EQUILIBRIUM MODEL OF THE TERM STRUCTURE OF INTEREST RATES UNDER REGIME-SWITCHING RISK

2005 ◽  
Vol 08 (07) ◽  
pp. 839-869 ◽  
Author(s):  
SHU WU ◽  
YONG ZENG
Keyword(s):  
General Equilibrium ◽  
Interest Rates ◽  
Term Structure ◽  
Risk Premium ◽  
Equilibrium Model ◽  
Regime Switching ◽  
Yield Curve ◽  
Closed Form Solution ◽  
Form Solution ◽  
General Equilibrium Model

This paper develops a general equilibrium model of the term structure of interest rates in the presence of the systematic risk of regime shifts. The model elucidates the economic nature of the regime-shift risk premium and introduces a new source of time-variation in bond returns. A closed-form solution for the term structure of interest rates is obtained under an affine model using log-linear approximation. The model is estimated by Efficient Method of Moments. The regime-switching risk is found to be statistically significant and mostly affect the long-end of the yield curve.

PMCMC for Term Structure of Interest Rates under Markov Regime Switching and Jumps

2020 ◽  
Vol 8 (2) ◽  
pp. 159-169
Author(s):  
Xiangdong Liu ◽  
Xianglong Li ◽  
Shaozhi Zheng ◽  
Hangyong Qian
Keyword(s):  
Parameter Estimation ◽  
Interest Rates ◽  
Closed Form ◽  
State Space ◽  
Term Structure ◽  
Regime Switching ◽  
State Space Model ◽  
Gaussian State ◽  
Space Model ◽  
Non Gaussian

AbstractA parameter estimation method, called PMCMC in this paper, is proposed to estimate a continuous-time model of the term structure of interests under Markov regime switching and jumps. There is a closed form solution to term structure of interest rates under Markov regime. However, the model is extended to be a CKLS model with non-closed form solutions which is a typical nonlinear and non-Gaussian state-space model(SSM) in the case of adding jumps. Although the difficulty of parameter estimation greatly prevents from researching models, we prove that the nonlinear and non-Gaussian state-space model has better performances in studying volatility. The method proposed in this paper will be implemented in simulation and empirical study for SHIBOR. Empirical results illustrate that the PMCMC algorithm has powerful advantages in tackling the models.

Sign in / Sign up

Export Citation Format

Share Document