Term structure modelling using the Nelson-Siegel framework
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Open Access
Type
ThesisThesis type
Doctor of PhilosophyAuthor/s
Chen, RuiAbstract
Nelson and Siegel [1987] introduce a smooth exponential function to
analyze the term structure of interest rates. This greatly facilitates the
literature in the Nelson-Siegel model family. In this thesis, the Nelson-
Siegel framework is studied extensively in terms of arbitrage-free ...
See moreNelson and Siegel [1987] introduce a smooth exponential function to analyze the term structure of interest rates. This greatly facilitates the literature in the Nelson-Siegel model family. In this thesis, the Nelson- Siegel framework is studied extensively in terms of arbitrage-free restrictions, pricing of interest rate derivatives and empirical performance of both in-sample fitting and out-of-sample forecasting. Chapter 1 introduces the motivations and contributions of this thesis. In the following chapter, I review the literature of interest rate models that are used in this thesis. In chapter 3, I study the performance of the dynamic Nelson-Siegel model in fitting and forecasting the government bond yields in Australia. The model is improved by utilizing a more powerful and robust state-space framework estimated with a Kalman filter. I show that this approach outperforms a random walk and a two-step estimation dynamic Nelson-Siegel model in forecasting the Australian government term structure across various forecasting horizons. Using the results from chapter 3 and Diebold and Li [2006], the dynamic Nelson-Siegel model provides exceptional in-sample fitting and out-of-sample forecasting of interest rates. However, the lack of theoretical background is criticized by academics and practitioners, such as the absence of arbitrage-free pricing. In this chapter, I develop a general arbitrage-free Nelson-Siegel model under the HJM framework, see Heath, Jarrow, and Morton [1992]. It maintains a Nelson-Siegel factor loading structure and features unspanned stochastic volatility factors. The corresponding market price of risk is derived based on Duffie, Pan, and Singleton [2000], Trolle and Schwartz [2009a], and Christensen, Diebold, and Rudebusch [2011]. The price of interest rate contingent claims, such as caps, swaptions and bond options, are derived from the generalized arbitrage-free Nelson-Siegel model based on Schrager and Pelser [2006] approximation procedure. To overcome a computationally inefficient pricing scheme in chapter 4, chapter 5 derives a consistent pricing framework of interest rate caps and swaptions based on Carr and Madan [1999] and Duffie, Pan, and Singleton [2000]. This exploits the potential to jointly model the interest rates and their derivatives. I calibrate the model on an extensive panel data including Libor/Swap rate, At-The-Money (ATM) caps and swaptions. By casting the entire model into a state-space form, the extended Kalman filter is employed to calibrate the model. The results show that the model prices both interest rates and their derivatives accurately. Finally, Chapter 6 concludes the thesis and discusses potential extensions.
See less
See moreNelson and Siegel [1987] introduce a smooth exponential function to analyze the term structure of interest rates. This greatly facilitates the literature in the Nelson-Siegel model family. In this thesis, the Nelson- Siegel framework is studied extensively in terms of arbitrage-free restrictions, pricing of interest rate derivatives and empirical performance of both in-sample fitting and out-of-sample forecasting. Chapter 1 introduces the motivations and contributions of this thesis. In the following chapter, I review the literature of interest rate models that are used in this thesis. In chapter 3, I study the performance of the dynamic Nelson-Siegel model in fitting and forecasting the government bond yields in Australia. The model is improved by utilizing a more powerful and robust state-space framework estimated with a Kalman filter. I show that this approach outperforms a random walk and a two-step estimation dynamic Nelson-Siegel model in forecasting the Australian government term structure across various forecasting horizons. Using the results from chapter 3 and Diebold and Li [2006], the dynamic Nelson-Siegel model provides exceptional in-sample fitting and out-of-sample forecasting of interest rates. However, the lack of theoretical background is criticized by academics and practitioners, such as the absence of arbitrage-free pricing. In this chapter, I develop a general arbitrage-free Nelson-Siegel model under the HJM framework, see Heath, Jarrow, and Morton [1992]. It maintains a Nelson-Siegel factor loading structure and features unspanned stochastic volatility factors. The corresponding market price of risk is derived based on Duffie, Pan, and Singleton [2000], Trolle and Schwartz [2009a], and Christensen, Diebold, and Rudebusch [2011]. The price of interest rate contingent claims, such as caps, swaptions and bond options, are derived from the generalized arbitrage-free Nelson-Siegel model based on Schrager and Pelser [2006] approximation procedure. To overcome a computationally inefficient pricing scheme in chapter 4, chapter 5 derives a consistent pricing framework of interest rate caps and swaptions based on Carr and Madan [1999] and Duffie, Pan, and Singleton [2000]. This exploits the potential to jointly model the interest rates and their derivatives. I calibrate the model on an extensive panel data including Libor/Swap rate, At-The-Money (ATM) caps and swaptions. By casting the entire model into a state-space form, the extended Kalman filter is employed to calibrate the model. The results show that the model prices both interest rates and their derivatives accurately. Finally, Chapter 6 concludes the thesis and discusses potential extensions.
See less
Date
2012Rights statement
The author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.Faculty/School
The University of Sydney Business School, Discipline of FinanceAwarding institution
The University of SydneyShare