期刊
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
卷 28, 期 3, 页码 329-343出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/jbes.2009.07295
关键词
Extended Kalman filter; Generalized autoregressive conditional heteroscedasticity model; Time-varying volatility; Yield curve
资金
- CREATES
- Danish National Research Foundation
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.
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