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Markov-Switching and Stochastic Volatility Diffusion Models of Short-Term Interest Rates

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Author Info
Smith, Daniel R

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Abstract

This article empirically compares the Markov-switching and stochastic volatility diffusion models of the short rate. The evidence supports the Markov-switching diffusion model. Estimates of the elasticity of volatility parameter for single-regime models unanimously indicate an explosive volatility process, whereas the Markov-switching models estimates are reasonable. It is found that either Markov switching or stochastic volatility, but not both, is needed to adequately fit the data. A robust conclusion is that volatility depends on the level of the short rate. Finally, the Markov-switching model is the best for forecasting. A technical contribution of this article is a presentation of quasi-maximum likelihood estimation techniques for the Markov-switching stochastic-volatility model.

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Publisher Info
Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 20 (2002)
Issue (Month): 2 (April)
Pages: 183-97
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Handle: RePEc:bes:jnlbes:v:20:y:2002:i:2:p:183-97

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  1. Soosung Hwang & Steve E. Satchell & Pedro L. Valls Pereira, 2004. "How Persistent is Volatility? An Answer with Stochastic Volatility Models with Markov Regime Switching State Equations," Econometric Society 2004 Latin American Meetings 198, Econometric Society. [Downloadable!]
    Other versions:
  2. Christiansen, Charlotte, 2005. "Level-ARCH Short Rate Models with Regime Switching: Bivariate Modeling of US and European Short Rates," Finance Research Group Working Papers F-2005-03, University of Aarhus, Aarhus School of Business, Department of Business Studies. [Downloadable!]
    Other versions:
  3. Daniel R. Smith & Christophe Parignon, 2004. "Modeling Yield-Factor Volatility," Econometric Society 2004 Australasian Meetings 307, Econometric Society. [Downloadable!]
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This page was last updated on 2009-11-22.


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