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Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields

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  • Hautsch, Nikolaus
  • Ou, Yangguoyi

Abstract

We propose a Nelson-Siegel type interest rate term structure model where the underlying yield factors follow autoregressive processes with stochastic volatility. The factor volatilities parsimoniously capture risk inherent to the term structure and are associated with the time-varying uncertainty of the yield curve's level, slope and curvature. Estimating the model based on U.S. government bond yields applying Markov chain Monte Carlo techniques we find that the factor volatilities follow highly persistent processes. We show that slope and curvature risk have explanatory power for bond excess returns and illustrate that the yield and volatility factors are closely related to industrial capacity utilization, inflation, monetary policy and employment growth. --

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Bibliographic Info

Paper provided by Center for Financial Studies (CFS) in its series CFS Working Paper Series with number 2009/03.

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Date of creation: 2009
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Handle: RePEc:zbw:cfswop:200903

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Keywords: Term Structure Modelling; Yield Curve Risk; Stochastic Volatility; Factor Models; Macroeconomic Fundamentals;

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  6. Hautsch, Nikolaus & Yang, Fuyu, 2012. "Bayesian inference in a Stochastic Volatility Nelson–Siegel model," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 56(11), pages 3774-3792.
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Cited by:
  1. Christensen, Jens H.E. & Lopez, Jose A. & Rudebusch, Glenn D., 2014. "Can spanned term structure factors drive stochastic yield volatility?," Working Paper Series, Federal Reserve Bank of San Francisco 2014-3, Federal Reserve Bank of San Francisco.

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