Title: Priors and Bayesian parameter estimation of affine term structure models

Authors: Leopold Sögner

Addresses: Department of Economics and Finance, Institute for Advanced Studies, Stumpergasse 56, 1060 Vienna, Austria; Vienna Graduate School of Finance (VGSF), Vienna University of Economics and Business, Welthandelsplatz 1, 1020 Vienna, Austria

Abstract: Affine term structure models describe the term structure of interest rates by means of a small number of latent factors. Quasi-unit root behaviour for these latent factors arises from the high degree of serial correlation in interest rate data. In this paper we perform Bayesian parameter estimation and demonstrate that the close to unit root behaviour of the latent factors should be considered properly. We show that with increasing serial correlation the Fisher information matrix approaches a singularity. We apply Markov Chain Monte Carlo simulation techniques in conjunction with regularised priors to simulate the joint posterior distribution of the model parameters. Informative priors are necessary to obtain a well performing Bayesian sampler.

Keywords: affine term-structure models; MCMC; Markov chain Monte Carlo simulation; near unit root behaviour; regularised priors; Bayesian parameter estimation; term structure; interest rates.

DOI: 10.1504/IJCEE.2014.064785

International Journal of Computational Economics and Econometrics, 2014 Vol.4 No.3/4, pp.288 - 319

Received: 18 Apr 2013
Accepted: 10 Feb 2014
Published online: 14 Sep 2014 *

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