Forecasting the Yield Curve of Government Bonds: A Comparative Study

For the past 20 years, researchers have applied the Kalman filter to the modeling and forecasting the term structure of interest rates. Despite its impressive performance in in-sample fitting yield curves, little research has focused on the out-of-sample forecast of yield curves using the Kalman filter. The goal of this thesis is to develop a unified dynamic model based on Diebold and Li (2006) and Nelson and Siegel’s (1987) three-factor model, and estimate this dynamic model using the Kalman filter. We compare both in-sample and out-of-sample performance of our dynamic methods with various other models in the literature. We find that our dynamic model dominates existing models in medium- and long-horizon yield curve predictions. However, the dynamic model should be used with caution when forecasting short maturity yields

Name thesis:degree_name

M.Sc. Management

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Faculty of Business

Department dc:contributor.department

Faculty of Business Programs

Grantor

Brock University

Year dc:date.issued

2013

Author dc:creator

• He, Chao

• yield curve
• dynamic model
• Kalman filter
• Nelson and Siegel model

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/10464/5122

OAI identifier oai:identifier

oai:brocku.scholaris.ca:10464/5122