Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/171800
Authors: 
Christensen, Nicolaj H.
Nysteen, Anders
Pedersen, Niklas B. D.
Year of Publication: 
2016
Series/Report no.: 
Danmarks Nationalbank Working Papers 106
Abstract: 
We model the dynamics of Danish government bond yields in a low-rate environment using a term structure model with a lower bound, a so-called shadow rate model. Specifically, we use a shadow rate extension of the well-known Arbitrage-Free Nelson
Abstract (Translated): 
Vi undersøger fordelene ved at modellere udviklingen i danske statsrenter i et lavrentemiljø ved brug af en dynamisk rentemodel med en nedre grænse, en såkaldt skyggerente-model. Vi benytter en skyggerente-udvidelse af den velkendte arbitrage-fri Nelson-Siegel model. I litteraturen har skyggerentemodellen vist at kunne forbedre cross-sectional fit og renteforecasts, når renterne er tæt på nul. Vi finder imidlertid ikke de samme forbedringer ved at benytte en skyggerentemodel på dansk data. Skyggerentemodellen udfordres af, at de danske statsrenter over de seneste år er blevet stadig mere negative. Trods udfordringerne foretrækker vi stadig en skyggerentemodel frem for Gaussiske modeller, da førstnævnte fanger den asymmetriske fordeling af fremtidige renter, som karakteriserer lavrentemiljøet. Set fra et risikostyringsperspektiv finder vi, at skyggerente-udvidelsen kun påvirker løbetidspræmierne i en kort periode i begyndelsen af 2015, hvor renterne var på deres laveste. Til sidst viser vi, at en rentemodel med to frem for tre faktorer forbedrer renteforecasts i lavrentemiljøet.
Subjects: 
Term structure model
Shadow-rate model
Arbitrage-free Nelson-Siegel
Low-rate environment
Government debt management
Risk management
Siegel model. In the literature, shadow rate models have been shown to improve the cross-sectional fit and the forecast performance when interest rates are close to zero. We do not, however, identify such improvements when using a shadow rate model on Danish yield data. The reason is that the shadow rate model is challenged when rates continue to decline into negative territory as has been the case in Denmark in recent years. Despite the challenges, we still prefer a shadow rate model over Gaussian models as the former captures the asymmetric distribution of future rates that characterises the low-yield environment. From a risk management perspective, we find that the shadow rate extension influences the term premia estimates notably only for a brief period in the beginning of 2015, where rates were at their lowest. Finally, as an aside we find that a term structure model with two rather than three factors improves the forecast performance in the low-rate period.
JEL: 
C32
C53
G17
Document Type: 
Working Paper

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