Forecasting the term structure of Korean government bond yields using the dynamic Nelson-Siegel class models

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1 Citation (Scopus)

Abstract

In this paper we propose and examine various extensions of the three-factor dynamic Nelson-Siegel model with the purpose of forecasting. We enhance the flexibility of the model by adding an additional driving factor or allowing for regime shifts in the model parameters. The regime changes are modeled through a recurring regime switching process or a change point process. Out-of-sample one through 6-months ahead forecasts are generated and evaluated using monthly Korean government bond yield data at sixteen different maturities. This paper finds that the three-factor model performs best for both short and long forecast horizons. Incorporating additional factor or multiple regimes does not seem to improve the out of- sample predictive accuracy of the yield curve forecasts.

Original languageEnglish
Pages (from-to)765-787
Number of pages23
JournalAsia-Pacific Journal of Financial Studies
Volume41
Issue number6
DOIs
Publication statusPublished - 2012 Dec 1

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Bond yields
Factors
Term structure
Government bonds
Regime switching
Regime shift
Change point
Maturity
Multiple regimes
Yield curve
Predictive accuracy
Point process
Nelson-Siegel model
Fama-French three-factor model
Forecast horizon
Regime change
Dynamic factor

Keywords

  • Bayesian MCMC estimation
  • Change-point
  • Dynamic Nelson-Siegel model
  • Markov switching process
  • Out-of-sample forecasting

ASJC Scopus subject areas

  • Finance

Cite this

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AB - In this paper we propose and examine various extensions of the three-factor dynamic Nelson-Siegel model with the purpose of forecasting. We enhance the flexibility of the model by adding an additional driving factor or allowing for regime shifts in the model parameters. The regime changes are modeled through a recurring regime switching process or a change point process. Out-of-sample one through 6-months ahead forecasts are generated and evaluated using monthly Korean government bond yield data at sixteen different maturities. This paper finds that the three-factor model performs best for both short and long forecast horizons. Incorporating additional factor or multiple regimes does not seem to improve the out of- sample predictive accuracy of the yield curve forecasts.

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