Ambagaspitiya, RohanaDodampe Gamage, Rangika2021-09-162021-09-162021-09Dodampe Gamage, R. (2021). Empirical analysis and forecasting of yield curves (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.http://hdl.handle.net/1880/113887In this thesis, we focus on term structure models. An accurate estimate of the current term structure of interest rates plays an important role in many areas of finance. In addition, it is important to forecast the futures term structure. Therefore, a lot of research work is devoted to determining how to best estimate, model, and predict the interest rate structure. The first part of this thesis focuses on modeling and forecasting the yield curves. We used the Principal Component Analysis(PCA) , Nelson Siegel(NS) model, and Gaussian Regression Process(GPR) in order to fit and forecast the European yield curve with different maturities. The second part of this thesis focuses on the calibration of the term structure model, since calibration is a highly challenging task, in particular in multiple yield curve markets. We simulate rates for both single-curve and multi-curve frameworks using the exact method and Milstein method and then calibrate parameters of simulated rates using the Ordinary Least Square Estimation(OLSE) method and the Generalized Method of Moments(GMM).engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Interest rate modelsPrincipal Component AnalysisGeneralized Method of MomentsOrdinary Least Square EstimationCIR modelEducation--FinanceEducation--MathematicsStatisticsmaster thesis10.11575/PRISM/39213