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Bayesian comparison of several continuous time models of the Australian short rate

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  • Andrew D. Sanford
  • Gael M. Martin

Abstract

This paper provides an empirical analysis of a range of alternative single‐factor continuous time models for the Australian short‐term interest rate. The models are nested in a general single‐factor diffusion process for the short rate, with each alternative model indexed by the level effect parameter for the volatility. The inferential approach adopted is Bayesian, with estimation of the models proceeding through a Markov chain Monte Carlo simulation scheme. Discrimination between the alternative models is based on Bayes factors. A data augmentation approach is used to improve the accuracy of the discrete time approximation of the continuous time models. An empirical investigation is conducted using weekly observations on the Australian 90 day interest rate from January 1990 to July 2000. The Bayes factors indicate that the square root diffusion model has the highest posterior probability of all models considered.

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  • Andrew D. Sanford & Gael M. Martin, 2006. "Bayesian comparison of several continuous time models of the Australian short rate," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 46(2), pages 309-326, June.
    • Handle: RePEc:bla:acctfi:v:46:y:2006:i:2:p:309-326
    DOI: 10.1111/j.1467-629X.2006.00169.x
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    Cited by:

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    3. Shyh-Wei Chen & Chung-Hua Shen, 2007. "Evidence of the duration-dependence from the stock markets in the Pacific Rim economies," Applied Economics, Taylor & Francis Journals, vol. 39(11), pages 1461-1474.
    4. Vijay A. Murik, 2013. "Bond pricing with a surface of zero coupon yields," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 53(2), pages 497-512, June.
    5. Muteba Mwamba, John & Thabo, Lethaba & Uwilingiye, Josine, 2014. "Modelling the short-term interest rate with stochastic differential equation in continuous time: linear and nonlinear models," MPRA Paper 64386, University Library of Munich, Germany.
    6. Tunaru, Diana, 2017. "Gaussian estimation and forecasting of the U.K. yield curve with multi-factor continuous-time models," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 119-129.
    7. Chua, Chew Lian & Suardi, Sandy & Tsiaplias, Sarantis, 2013. "Predicting short-term interest rates using Bayesian model averaging: Evidence from weekly and high frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 442-455.
    8. Vijay A Murik, 2013. "Measuring monetary policy expectations," Australian Journal of Management, Australian School of Business, vol. 38(1), pages 49-65, April.

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