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:	2013-11-04
Authors:	Shin, Minchul ; Zhong, Molin
Institutions:	Department of Economics, University of Pennsylvania
Subject:	Dynamic factor model \| forecasting \| stochastic volatility \| term structure of interest rates

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Extent:	application/pdf
Series:	PIER Working Paper Archive.
Type of publication:	Book / Working Paper
Notes:	48 pages
Classification:	C5 - Econometric Modeling ; G1 - General Financial Markets ; E4 - Money and Interest Rates
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010822928