Bayesian Methods of Parameter Estimation in Term Structure Fitting Methods

Student: Glukhov Nikita

Supervisor: Victor A Lapshin

Faculty: International College of Economics and Finance

Educational Programme: Double degree programme in Economics of the NRU HSE and the University of London (Bachelor)

Year of Graduation: 2021

The term structure (or yield curve) is an important tool in pricing financial derivatives and policy making. Thus, modelling a yield curve is a wellestablished field of research. However, while there are many works focusing on the point in time fit of the curve still there is less research on the forecasting of the yield curve. In some models such as the NelsonSiegel model, one can forecast the yield curve by forecasting its parameters. In the following thesis, we consider such framework introduced by Diebold and Li (2006) and extend it by applying the Bayesian Inference to the autoregressive process of parameters of the NelsonSiegel model. The key result obtained in the work is reducing of the width of prediction interval of parameters, thus, reducing the uncertainty of our forecasts to some extent.

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