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dc.contributor.authorHe, Chao
dc.date.accessioned2013-11-21T20:51:56Z
dc.date.available2013-11-21T20:51:56Z
dc.date.issued2013-11-21
dc.identifier.urihttp://hdl.handle.net/10464/5122
dc.description.abstractFor 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 yieldsen_US
dc.language.isoengen_US
dc.publisherBrock Universityen_US
dc.subjectyield curveen_US
dc.subjectdynamic modelen_US
dc.subjectKalman filteren_US
dc.subjectNelson and Siegel modelen_US
dc.titleForecasting the Yield Curve of Government Bonds: A Comparative Studyen_US
dc.typeElectronic Thesis or Dissertationen_US
dc.degree.nameM.Sc. Managementen_US
dc.degree.levelMastersen_US
dc.contributor.departmentFaculty of Business Programsen_US
dc.degree.disciplineFaculty of Businessen_US
dc.embargo.termsNoneen_US
refterms.dateFOA2021-08-01T01:23:09Z


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