Does Realized Volatility Help Bond Yield Density Prediction?

This paper examines the importance of realized volatility in bond yield density prediction. We incorporate realized volatility into a Dynamic Nelson-Siegel (DNS) model with stochastic volatility and evaluate its predictive performance on US bond yield data. When compared to popular specifications in the DNS literature without realized volatility, we find that having this information improves density forecasting performance

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Year of publication:	2018
Authors:	Shin, Minchul
Other Persons:	Zhong, Molin (contributor)
Publisher:	[2018]: [S.l.] : SSRN
Subject:	Volatilität \| Volatility \| Kapitaleinkommen \| Capital income \| Prognoseverfahren \| Forecasting model \| Anleihe \| Bond \| Statistische Verteilung \| Statistical distribution \| Zinsstruktur \| Yield curve \| ARCH-Modell \| ARCH model \| Öffentliche Anleihe \| Public bond

Extent:	1 Online-Ressource (46 p)
Series:	PIER Working Paper ; No. 13-064
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments November 4, 2013 erstellt
Other identifiers:	10.2139/ssrn.2350776 [DOI]
Classification:	C5 - Econometric Modeling ; G1 - General Financial Markets ; E4 - Money and Interest Rates
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10012938238