Does realized volatility help bond yield density prediction?

Minchul Shin and Molin Zhong

PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania

Abstract: 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.

Keywords: Dynamic factor model; forecasting; stochastic volatility; term structure of interest rates (search for similar items in EconPapers)
JEL-codes: C5 E4 G1 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2013-11-04
New Economics Papers: this item is included in nep-for
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Related works:
Journal Article: Does realized volatility help bond yield density prediction? (2017)
Working Paper: Does Realized Volatility Help Bond Yield Density Prediction? (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:pen:papers:13-064

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