Modeling Multivariate Interest Rates Using Time-Varying Copulas and Reducible Nonlinear Stochastic Differential Equations

Bu, R ORCID: 0000-0002-3947-3038, Giet, L, Hadri, K and Lubrano, M (2011) Modeling Multivariate Interest Rates Using Time-Varying Copulas and Reducible Nonlinear Stochastic Differential Equations. Journal of Financial Econometrics, 9 (1). pp. 198-236.

Text Bu et al. (2011) Copula Multivariate RDs for Interest Rates.pdf - Author Accepted Manuscript Download (307kB)

Abstract

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein-Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe-Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. © The Author 2010. Published by Oxford University Press. All rights reserved.

Item Type:	Article
Additional Information:	## TULIP Type: Articles/Papers (Journal) ##
Depositing User:	Symplectic Admin
Date Deposited:	17 Oct 2016 13:47
Last Modified:	22 Nov 2023 12:33
DOI:	10.1093/jjfinec/nbq022
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3003752