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Term Structure Forecasting: No‐Arbitrage Restrictions versus Large Information Set

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  • Carlo A. Favero
  • Linlin Niu
  • Luca Sala

Abstract

This paper addresses the issue of forecasting the term structure. We provide a unified state-space modelling framework that encompasses different existing discrete-time yield curve models. Within such framework we analyze the impact of two modelling choices, namely the imposition of no-arbitrage restrictions and the size of the information set used to extract factors, on the forecasting performance. Using US yield curve data, we find that both no-arbitrage and large info help in forecasting but no model uniformly dominates the other. No-arbitrage models are more useful at shorter horizon for shorter maturities. Large information sets are more useful at longer horizons and longer maturities. We also find evidence for a significant feedback from yield curve models to macroeconomic variables that could be exploited for macroeconomic forecasting.
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  • Carlo A. Favero & Linlin Niu & Luca Sala, 2012. "Term Structure Forecasting: No‐Arbitrage Restrictions versus Large Information Set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(2), pages 124-156, March.
    • Handle: RePEc:wly:jforec:v:31:y:2012:i:2:p:124-156
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    1. Qiang Dai & Kenneth J. Singleton, 2000. "Specification Analysis of Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 55(5), pages 1943-1978, October.
    2. Marcello Pericoli & Marco Taboga, 2008. "Canonical Term‐Structure Models with Observable Factors and the Dynamics of Bond Risk Premia," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(7), pages 1471-1488, October.
    3. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
    4. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 161-224, National Bureau of Economic Research, Inc.
    5. Christensen, Jens H.E. & Diebold, Francis X. & Rudebusch, Glenn D., 2011. "The affine arbitrage-free class of Nelson-Siegel term structure models," Journal of Econometrics, Elsevier, vol. 164(1), pages 4-20, September.
    6. Moench, Emanuel, 2008. "Forecasting the yield curve in a data-rich environment: A no-arbitrage factor-augmented VAR approach," Journal of Econometrics, Elsevier, vol. 146(1), pages 26-43, September.
    7. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
    8. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    9. 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.
    10. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    11. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    12. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    13. GlennD. Rudebusch & Tao Wu, 2008. "A Macro-Finance Model of the Term Structure, Monetary Policy and the Economy," Economic Journal, Royal Economic Society, vol. 118(530), pages 906-926, July.
    14. Gregory R. Duffee, 2002. "Term Premia and Interest Rate Forecasts in Affine Models," Journal of Finance, American Finance Association, vol. 57(1), pages 405-443, February.
    15. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    16. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    17. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    18. 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.
    19. Don H Kim, 2007. "Challenges in macro-finance modeling," BIS Working Papers 240, Bank for International Settlements.
    20. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    21. Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006. "The macroeconomy and the yield curve: a dynamic latent factor approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 309-338.
    22. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
    23. Dai, Qiang & Singleton, Kenneth J., 2002. "Expectation puzzles, time-varying risk premia, and affine models of the term structure," Journal of Financial Economics, Elsevier, vol. 63(3), pages 415-441, March.
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    Cited by:

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    4. João F. Caldeira & Guilherme V. Moura & , Fabricio Tourrucôo, 2016. "Forecasting the yield curve with the arbitrage-free dynamic Nelson-Siegel model: Brazilian evidence," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 17(2), pages 221-237.
    5. Lelo de Larrea Alejandra, 2020. "Forecast Comparison of the Term Structure of Interest Rates of Mexico for Different Specifications of the Affine Model," Working Papers 2020-01, Banco de México.
    6. Duffee, Gregory, 2013. "Forecasting Interest Rates," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 385-426, Elsevier.
    7. 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.
    8. Wali Ullah, 2020. "The arbitrage-free generalized Nelson–Siegel term structure model: Does a good in-sample fit imply better out-of-sample forecasts?," Empirical Economics, Springer, vol. 59(3), pages 1243-1284, September.
    9. Adam Traczyk, 2013. "Financial integration and the term structure of interest rates," Empirical Economics, Springer, vol. 45(3), pages 1267-1305, December.
    10. Shang, Yuhuang & Zheng, Tingguo, 2018. "Fitting and forecasting yield curves with a mixed-frequency affine model: Evidence from China," Economic Modelling, Elsevier, vol. 68(C), pages 145-154.
    11. Chen, Ying & Niu, Linlin, 2014. "Adaptive dynamic Nelson–Siegel term structure model with applications," Journal of Econometrics, Elsevier, vol. 180(1), pages 98-115.
    12. Zaremba, Adam & Kizys, Renatas & Aharon, David Y. & Umar, Zaghum, 2022. "Term spreads and the COVID-19 pandemic: Evidence from international sovereign bond markets," Finance Research Letters, Elsevier, vol. 44(C).
    13. Evgenidis, Anastasios & Tsagkanos, Athanasios & Siriopoulos, Costas, 2017. "Towards an asymmetric long run equilibrium between stock market uncertainty and the yield spread. A threshold vector error correction approach," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 267-279.
    14. Kyle E. Binder & Mohsen Pourahmadi & James W. Mjelde, 2020. "The role of temporal dependence in factor selection and forecasting oil prices," Empirical Economics, Springer, vol. 58(3), pages 1185-1223, March.
    15. Carlo A. Favero & Arie E. Gozluklu & Haoxi Yang, 2016. "Demographics and the Behavior of Interest Rates," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 64(4), pages 732-776, November.
    16. Kaya, Huseyin, 2013. "Forecasting the yield curve and the role of macroeconomic information in Turkey," Economic Modelling, Elsevier, vol. 33(C), pages 1-7.
    17. Julián Andrada-Félix & Adrian Fernandez-Perez & Fernando Fernández-Rodríguez, 2015. "Fixed income strategies based on the prediction of parameters in the NS model for the Spanish public debt market," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 6(2), pages 207-245, June.
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    19. Kyle E. Binder & James W. Mjelde, 2018. "Projecting impacts of carbon dioxide emission reductions in the US electric power sector: evidence from a data-rich approach," Climatic Change, Springer, vol. 151(2), pages 143-155, November.
    20. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.

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    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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