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Fractionality and co-fractionality between Government Bond yields

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Abstract

In a co-fractional vector autoregressive (VAR) model two more parameters are estimated, compared to the traditional cointegrated VAR model. The increased number of parameters that needs to be estimated leads to identification problems; there is no unique formulation of a co-fractional system, though usually one formulation is preferred. This paper has the following contributions: (i) it discusses different kinds of identification problems in co-fractional VAR models; (ii) it proposes a specification test for higher order fractional processes; (iii) it presents an Ox program that can be used for estimating and testing co-fractional systems; and (iv) it uses the above mentioned contributions to analyse a system of Government Bonds in the US and Norway where the results indicates that the level and trend in the yield curve have a longer memory than the curvature (i.e., a linear combination of the yields of the Government Bonds that corresponds to representing the curvature of the yield curve is a co-fractional relationship).

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  • Håvard Hungnes, 2016. "Fractionality and co-fractionality between Government Bond yields," Discussion Papers 838, Statistics Norway, Research Department.
  • Handle: RePEc:ssb:dispap:838
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    1. Søren Johansen & Morten Ørregaard Nielsen, 2012. "Likelihood Inference for a Fractionally Cointegrated Vector Autoregressive Model," Econometrica, Econometric Society, vol. 80(6), pages 2667-2732, November.
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    4. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    5. Andreas Noack Jensen & Morten Ørregaard Nielsen, 2014. "A Fast Fractional Difference Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(5), pages 428-436, August.
    6. Daniela Osterrieder & Peter C. Schotman, 2012. "The Volatility of Long-term Bond Returns: Persistent Interest Shocks and Time-varying Risk Premiums," CREATES Research Papers 2012-35, Department of Economics and Business Economics, Aarhus University.
    7. Federico Carlini & Paolo Santucci de Magistris, 2019. "On the Identification of Fractionally Cointegrated VAR Models With the Condition," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 134-146, January.
    8. Johansen, SØren, 2008. "A Representation Theory For A Class Of Vector Autoregressive Models For Fractional Processes," Econometric Theory, Cambridge University Press, vol. 24(3), pages 651-676, June.
    9. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
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    More about this item

    Keywords

    Fractional cointegration;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects

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