Forecasting the term structures of Treasury and corporate yields using dynamic Nelson-Siegel models

Yu, Wei-Choun; Zivot, Eric

doi:10.1016/j.ijforecast.2010.04.002

Cited by 38 publications

(27 citation statements)

References 15 publications

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“…We also observe the more flexible model configurations, such as the time varying loadings and the dynamic NSS model which provides better fit in-sample, performs badly out-of-sample compared with the more parsimonious alternatives. Yu and Zivot (2010) corroborate this result using corporate bonds data. A conclusion from this analysis is that allowing for time varying loadings, in terms of forecasting, can be labelled as excessive.…”

Section: Dynamic Nelson-siegel-svensson Model (Nss)supporting

confidence: 75%

Prediction Bias Correction for Dynamic Term Structure Models

Raviv¹

2012

SSRN Journal

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Section: Dynamic Nelson-siegel-svensson Model (Nss)supporting

confidence: 75%

Prediction Bias Correction for Dynamic Term Structure Models

Raviv¹

2012

SSRN Journal

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“…Especially for short-term investment grade bonds and long-term high-yield bonds. But the dynamics of short-term high-yield bonds varies with time, and the parameter of instability [23].…”

Section: Dr(t)=(θ-r(t))dt+√vdb(t)mentioning

confidence: 99%

Review on Term Structure

Huang¹

2016

Proceedings of the 6th International Conference on Electronic, Mechanical, Information and Management Society

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Abstract. Domestic and foreign scholars on corporate bonds affine term structure models with varying degrees of research, the results is very rich. We can predict bond forward rates for Treasury bonds, the current yield term structure includes information of long-term maturity structure. For example, if a bond yield curve is steeper than usual, the long maturity bond yields will be reduced over time. This prediction depends only on the relationship between the yield time series behavior, it can extract more information from the current term structure, improve prediction. Research abroad Interest Rate Term Structure affine model are as follows.

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“…Examples are Duffie-Kan restrictions (Duffie and Kan, 1996), smoothing restrictions (Koopman and Van der Wel, 2010) Yu and Zivot (2010) find that using the state-space estimation method results in poor out-of-sample performance compared with the two-step procedure.…”

Section: General Factor Modelmentioning

confidence: 99%

Prediction bias correction for dynamic term structure models

Raviv

2015

Economics Letters

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Forecasting the term structures of Treasury and corporate yields using dynamic Nelson-Siegel models

Cited by 38 publications

References 15 publications

Prediction Bias Correction for Dynamic Term Structure Models

Prediction Bias Correction for Dynamic Term Structure Models

Review on Term Structure

Prediction bias correction for dynamic term structure models

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