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Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson–Siegel Model With Time-Varying Parameters

Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson–Siegel Model With... In this article we introduce time-varying parameters in the dynamic Nelson–Siegel yield curve model for the simultaneous analysis and forecasting of interest rates of different maturities. The Nelson–Siegel model has been recently reformulated as a dynamic factor model with vector autoregressive factors. We extend this framework in two directions. First, the factor loadings in the Nelson–Siegel yield model depend on a single loading parameter that we treat as the fourth latent factor. Second, we specify the overall volatility as a generalized autoregressive conditional heteroscedasticity (GARCH) process. We present empirical evidence of considerable increases in within-sample goodness of fit for these advances in the dynamic Nelson–Siegel model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Business & Economic Statistics Taylor & Francis

Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson–Siegel Model With Time-Varying Parameters

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References (40)

Publisher
Taylor & Francis
Copyright
© 2010 American Statistical Association
ISSN
1537-2707
eISSN
0735-0015
DOI
10.1198/jbes.2009.07295
Publisher site
See Article on Publisher Site

Abstract

In this article we introduce time-varying parameters in the dynamic Nelson–Siegel yield curve model for the simultaneous analysis and forecasting of interest rates of different maturities. The Nelson–Siegel model has been recently reformulated as a dynamic factor model with vector autoregressive factors. We extend this framework in two directions. First, the factor loadings in the Nelson–Siegel yield model depend on a single loading parameter that we treat as the fourth latent factor. Second, we specify the overall volatility as a generalized autoregressive conditional heteroscedasticity (GARCH) process. We present empirical evidence of considerable increases in within-sample goodness of fit for these advances in the dynamic Nelson–Siegel model.

Journal

Journal of Business & Economic StatisticsTaylor & Francis

Published: Jul 1, 2010

Keywords: Extended Kalman filter; Generalized autoregressive conditional heteroscedasticity model; Time-varying volatility; Yield curve

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