Bayesian Estimation of Short-Rate Models

Philip Gray
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Philip Gray: UQ Business School, The University of Queensland, St Lucia QLD 4072.

Australian Journal of Management, 2005, vol. 30, issue 1, 1-22

Abstract: Estimating continuous-time short-rate models is challenging since the likelihood function for most popular models is unknown. While approximate likelihood functions are often used, this practice induces bias into the estimation process. This paper explores a Bayesian method of estimating short-rate models. While the approach also employs an approximate likelihood data augmentation is utilised to mitigate discretisation bias. The results suggest that Bayesian estimates of posterior densities for model parameters closely resemble true posterior densities. While nonessential for point estimation, a small degree of data augmentation is useful in recovering accurate posterior densities and reducing the bias in estimates of bond price. These findings are encouraging for the many cases where exact likelihood-based estimation is impossible and approximations must be relied upon.

Keywords: SHORT-RATE MODELS; CONTINUOUS-TIME FINANCE; BAYESIAN ESTIMATION; VASICEK (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:ausman:v:30:y:2005:i:1:p:1-22

DOI: 10.1177/031289620503000102

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