Simulation-Based Bayesian Estimation of Affine Term Structure Models

Andrew D. Sanford and Gael Martin

No 15/03, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: This paper demonstrates the application of Bayesian simulation-based estimation to a class of interest rate models known as Affine Term Structure (ATS) models. The technique used is based on a Markov Chain Monte Carlo algorithm, with the discrete observations on yields augmented by additional higher frequency latent data. The introduction of augmented yield data reduces the bias associated with estimating a continuous time model using discretely observed data. The technique is demon-strated using a one-factor ATS model, with the latent factor process that underlies the yields sampled via a single-move algorithm. Numerical application of the method is demonstrated using both simulated and empirical data. Extension of the method to a three-factor ATS model is also discussed, as well as the application of a multi-move sampler based on a Kalman Filtering and Smoothing algorithm.

Keywords: Interest Rate Models; Markov Chain Monte Carlo; Data Augmentation; Nonlinear State Space Models; Kalman Filtering. (search for similar items in EconPapers)
JEL-codes: C11 C15 E43 (search for similar items in EconPapers)
Pages: 41 pages
Date: 2003-09
New Economics Papers: this item is included in nep-cmp, nep-ecm, nep-ets, nep-fin and nep-rmg
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2003/wp15-03.pdf (application/pdf)

Related works:
Journal Article: Simulation-based Bayesian estimation of an affine term structure model (2005)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:msh:ebswps:2003-15

Ordering information: This working paper can be ordered from
http://business.mona ... -business-statistics

Access Statistics for this paper

More papers in Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics PO Box 11E, Monash University, Victoria 3800, Australia. Contact information at EDIRC.
Bibliographic data for series maintained by Professor Xibin Zhang ().