Using Bayesian Methods in Estimation of the Parameters of Zero-Coupon Yield Curve Analysis Models

Student: Zamalutdinova Albina

Supervisor: Victor A Lapshin

Faculty: International College of Economics and Finance

Educational Programme: Financial Economics (Master)

Year of Graduation: 2021

In this work, we present the Bayesian methods, in particular, Gibbs sampler and Metropolis-Hastings algorithms for calibration of Vasicek model. Data on the 6 months short rate and the yields of Russian government bonds is used. In order to show the significance of usage Bayesian methods, we also introduce maximum likelihood calibration for comparison of obtained results. Finally, the firm’s loss function metric is used to confirm the prevalence of MCMC Bayesian method for interest rate model estimation over maximum likelihood. We work with model measurement error and find patterns where the model fits good or poor.

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