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Forecasting government bond yields with large Bayesian vector autoregressions

Author

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  • Carriero, Andrea
  • Kapetanios, George
  • Marcellino, Massimiliano

Abstract

We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the information contained in a large panel of yields. In particular, we use a large Bayesian Vector Autoregression (BVAR) with an optimal amount of shrinkage towards univariate AR models. The optimal shrinkage is chosen by maximizing the Marginal Likelihood of the model. Focusing on the US, we provide an extensive study on the forecasting performance of the proposed model relative to most of the existing alternative specifications. While most of the existing evidence focuses on statistical measures of forecast accuracy, we also consider alternative measures based on trading schemes and portfolio allocation. We extensively check the robustness of our results, using different datasets and Monte Carlo simulations. We find that the proposed BVAR approach produces competitive forecasts, systematically more accurate than random walk forecasts, even though the gains are small.

Suggested Citation

  • Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2012. "Forecasting government bond yields with large Bayesian vector autoregressions," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2026-2047.
  • Handle: RePEc:eee:jbfina:v:36:y:2012:i:7:p:2026-2047
    DOI: 10.1016/j.jbankfin.2012.03.008
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    References listed on IDEAS

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    Cited by:

    1. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2014. "Forecasting with factor-augmented error correction models," International Journal of Forecasting, Elsevier, vol. 30(3), pages 589-612.
    2. repec:sbe:breart:v:34:y:2014:i:2:a:48700 is not listed on IDEAS
    3. Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," SFB 649 Discussion Papers SFB649DP2014-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Ralf Brüggemann & Christian Kascha, 2017. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2017-06, Department of Economics, University of Konstanz.
    5. repec:oup:jfinec:v:16:y:2018:i:1:p:1-33. is not listed on IDEAS
    6. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    7. Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz, 2015. "Forecasting with Bayesian multivariate vintage-based VARs," International Journal of Forecasting, Elsevier, vol. 31(3), pages 757-768.
    8. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, Elsevier.
    9. Koop, Gary & Korobilis, Dimitris, 2014. "A new index of financial conditions," European Economic Review, Elsevier, vol. 71(C), pages 101-116.
    10. Argyropoulos Efthymios & Tzavalis Elias, 2015. "Term spread regressions of the rational expectations hypothesis of the term structure allowing for risk premium effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 49-70, February.
    11. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.
    12. repec:spr:empeco:v:53:y:2017:i:2:d:10.1007_s00181-016-1128-y is not listed on IDEAS
    13. repec:scn:guhrje:2017_4_04 is not listed on IDEAS
    14. Duffee, Gregory, 2013. "Forecasting Interest Rates," Handbook of Economic Forecasting, Elsevier.
    15. repec:eee:jouret:v:92:y:2016:i:1:p:25-39 is not listed on IDEAS
    16. Danilo Leiva-Leon, 2017. "Monitoring the Spanish Economy through the Lenses of Structural Bayesian VARs," Occasional Papers 1706, Banco de España;Occasional Papers Homepage.
    17. repec:eee:empfin:v:44:y:2017:i:c:p:209-225 is not listed on IDEAS
    18. Dimitris P. Louzis, 2014. "Macroeconomic and credit forecasts in a small economy during crisis: A large Bayesian VAR approach," Working Papers 184, Bank of Greece.
    19. Gregory R. Duffee, 2012. "Forecasting interest rates," Economics Working Paper Archive 599, The Johns Hopkins University,Department of Economics.

    More about this item

    Keywords

    Bayesian methods; Forecasting; Marginal likelihood; Term structure;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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