Calibration of Interest Rates
WDS'12 Proceedings of Contributed Papers: Part I – Mathematics and Computer Sciences
6 Pages Posted: 29 Jul 2013
Date Written: November 2, 2012
In this contribution we study calibration methods of interest rate models. First, we assume that model parameters are constant and can be estimated by the maximum likelihood estimation or yield curve fitting methods. Next, we suppose that model parameters are random variables with their prior distributions. We present Markov Chain Monte Carlo algorithm to generate from posterior distribution using the Bayes theorem. Different methods of calibration based on real data are then applied on well-known Vasicek model with constant volatility.
Keywords: Interest rate models calibration, Vasicek model, Bayesian methods, MCMC algorithm
JEL Classification: C11, C15, G12
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