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Adaptive Dynamic Nelson–Siegel Term Structure Model with Applications
Ying Chen, Linlin Niu
Journal of Econometrics 180 (2014) 98–115
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We propose an Adaptive Dynamic Nelson–Siegel (ADNS) model to adaptively detect parameter changes and forecast the yield curve. The model is simple yet flexible and can be safely applied to both stationary and nonstationary situations with different sources of parameter changes. For the 3- to 12-months ahead out-of-sample forecasts of the US yield curve from 1998:1 to 2010:9, the ADNS model dominates both the popular reduced-form and affine term structure models; compared to random walk prediction, the ADNS steadily reduces the forecast error measurements by between 20% and 60%. The locally estimated coefficients and the identified stable subsamples over time align with policy changes and the timing of the recent financial crisis.
JEL-Codes: C32 C53 E43 E47
Keywords: Yield curve Term structure of interest rates Local parametric models Forecasting


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