Ioannis A. Venetis and Avgoustinos Ladas

Correspondence: Ioannis A. Venetis, ivenetis@upatras.gr

University of Patras, School of Economics and Business, Department of Economics, University Campus, Rio 26504.

pdf (1910.4 Kb) | doi: https://doi.org/10.47260/bae/1022

Abstract

We study the co-movement in international zero-coupon government bond yields using a recently proposed methodology by Choi et al. (2018) and Choi et al. (2021) for the estimation of multilevel factor models. We employ a readily available non-proprietary dataset coupled with open-source code which facilitates reproduction of the results but also comparability with the existing bibliography. The ten countries dataset is cross-sectionally expanded to eleven countries with newly constructed data series on the term structure of Greek constant-maturity, government zero-coupon bond rates. We find that the country pair US-Germany is most suitable as an initial candidate for global factor estimation. We confirm that three global factors account for most of the variation in zero-coupon bond yields leaving a small proportion to be (contemporaneously) explained by local factors. Global inflation and global real activity are related to the global level and slope factors. The third global factor, “curvature,” is strongly related to economic/financial uncertainty linked to systemic risk stemming from the US financial markets.

Keywords:

  Sovereign bonds; Yield curve; Term structure; Multilevel factor model; Global factors; Local factors.

References

Abbritti, M., Dell’Erba, S., Moreno, A., & Sola, S. 2018. Global factors in the term structure of interest rates. International Journal of Central Banking, 14(2), 301 - 340.Afonso, A., & Martins, M.M.F. 2012. Level, slope, curvature of the sovereign yield curve, and fiscal behaviour. Journal of Banking &amp Finance, 36(6), 1789 - 1807.Ahn, Seung C., & Horenstein, Alex R. 2013. Eigenvalue Ratio Test for the Number of Factors. Econometrica, 81(3), 1203 - 1227.Andreou, E., Gagliardini, P., Ghysels, E., & Rubin, M. 2019. Inference in Group Factor Models with an Application to Mixed-Frequency Data. Econometrica, 87(4), 1267 - 1305.Bae, Byung Yoon, & Kim, Dong Heon. 2011. Global and Regional Yield Curve Dynamics and Interactions: The Case of Some Asian Countries. International Economic Journal, 25(4), 717 - 738.Bai, J., & Wang, P. 2015. Identification and estimation of dynamic factor models. Journal of Business & Economic Statistics, 33(2), 221 - 240.Bai, Jushan, & Ng, Serena. 2002. Determining the Number of Factors in Approximate Factor Models. Econometrica, 70(1), 191 - 221.Baker, S., Bloom, N., Davis, S., & Kost, K. 2019. Policy News and Stock Market Volatility. NBER Working Paper 25720, mar.Baker, S.R., Bloom, N., & Davis, S.J. 2016. Measuring Economic Policy Uncertainty. The Quarterly Journal of Economics, 131(4), 1593 - 1636.Bhatt, Vipul, Kishor, N Kundan, & Ma, Jun. 2017. The impact of EMU on bond yield convergence: Evidence from a time-varying dynamic factor model. Journal of Economic Dynamics and Control, 82(Sep), 206 - 222.Byrne, J.P., Cao, S., & Korobilis, D. 2019. Decomposing global yield curve co- movement. Journal of Banking & Finance, 106(Sep), 500 - 513.Chen, P. 2012. Common Factors and Specific Factors. Unpublished Manuscript, MPRA Paper No. 36114.Chin, M., De Graeve, F., Filippeli, T., & Theodoridis, K. 2022. Understanding International Long-term Interest Rate Comovement. in Dolado, J.J., Gambetti, L. and Matthes, C. (Ed.) Essays in Honour of Fabio Canova (Advances in Econometrics, Vol. 44B), Emerald Publishing Limited, Bingley, Sep, 147 - 189.Choi, I., Kim, D., Kim, Y.J., & Kwark, H-S. 2018. A multilevel factor model: Identification, asymptotic theory and applications. Journal of Applied Econometrics, 33(3), 355 - 377.Choi, I., Lin, R., & Shin, Y. 2021. Canonical correlation-based model selection for the multilevel factors. Journal of Econometrics, oct.Chuhan, Punam, Claessens, Stijn, & Mamingi, Nlandu. 1998. Equity and bond flows to Latin America and Asia: the role of global and country factors. Journal of Development Economics, 55(2), 439 - 463.Coroneo, L., Garrett, I., & Sanhueza, J. 2018. Dynamic Linkages Across Country Yield Curves: The Effects of Global and Local Yield Curve Factors on US, UK and German Yields. Mili M., Samaniego Medina R., di Pietro F. (eds) New Methods in Fixed Income Modeling. Contributions to Management Science. Springer, Cham, 205 - 222.Dahlquist, Magnus, & Hasseltoft, Henrik. 2013. International Bond Risk Premia. Journal of International Economics, 90(1), 17 - 32.Diebold, F.X., & Li, C. 2006. Forecasting the term structure of government bond yields. Journal of Econometrics, 130(2), 337 - 364.Diebold, F.X., Rudebusch, G.D., & Aruoba, S.B. 2006. The macroeconomy and the yield curve: a dynamic latent factor approach. Journal of Econometrics, 131(1 - 2), 309 - 338.Diebold, F.X., Li, C., & Yue, V.Z. 2008. Global yield curve dynamics and interactions: A dynamic Nelson-Siegel approach. Journal of Econometrics, 146(2), 351 - 363.Han, Xu. 2021. Shrinkage Estimation of Factor Models With Global and Group- Specific Factors. Journal of Business & Economic Statistics, 39(1), 1 - 17.Jotikasthira, Chotibhak, Le, Anh, & Lundblad, Christian. 2015. Why do term structures in different currencies co-move? Journal of Financial Economics, 115(1), 58 - 83.Kaminska, I., Meldrum, A., & Smith, J. 2013. A global model of international yield curves: no-arbitrage term structure approach. International Journal of Finance & Economics, 18(4), 352 - 374.Kim, Dukpa, Kim, Yunjung, & Bak, Yuhyeon. 2017. Multilevel factor analysis of bond risk premia. Studies in Nonlinear Dynamics & Econometrics, 21(5).Kobayashi, T. 2020. Global Bond Market Interaction: An Arbitrage-free Dynamic Nelson Siegel Modeling Approach. Working paper. Availble at: https://researchmap.jp/kobayashitakeshi.ht/presentations/36078140/attachmentfile.pdf , Apr., 1 - 22.Litterman, R.B., & Scheinkman, J. 1991. Common Factors Affecting Bond Returns. The Journal of Fixed Income, 1(1), 54 - 61.Modugno, M., & Nikolaou, K. 2009. The forecasting power of international yield curve linkages. European Central Bank, Working Paper Series, Apr., No. 1044.Moench, Emanuel. 2010. Term structure surprises: the predictive content of curvature, level, and slope. Journal of Applied Econometrics, 27(4), 574 - 602.Nelson, Charles R., & Siegel, Andrew F. 1987. Parsimonious Modeling of Yield Curves. The Journal of Business, 60(4), 473.Onatski, Alexei. 2010. Determining the Number of Factors from Empirical Distribution of Eigenvalues. Review of Economics and Statistics, 92(4), 1004 - 1016.Perignon, Christophe, Smith, Daniel R., & Villa, Christophe. 2007. Why common factors in international bond returns are not so common. Journal of International Money and Finance, 26(2), 284 - 304.Puttmann, L. 2018. Patterns of Panic: Financial Crisis Language in Historical Newspapers. SSRN Electronic Journal.Rudebusch, G.D. 2010. Macro-finance models of interest rates and the economy. The Manchester School, 78(aug), 25 - 52.Stagnol, L. 2019. Extracting global factors from local yield curves. Journal of Asset Management, 20(5), 341 - 350.Stock, J.H., & Watson, M.W. 2011. Dynamic factor models. In: Clements, M.J., Hendry, D.F. (Eds.), Oxford Handbook on Economic Forecasting. Oxford University Press, Oxford, 35 - 39.Stolyarov, D., & Tesar, L.L. 2021. Interest rate trends in a global context. Economic Modelling, 101(Aug), 105532.Svensson, Lars E O. 1994. Estimating and interpreting forward interest rates: Sweden 1992-1994. NBER Working Paper No. 4871, sep, 1 - 47.Wright, J.H. 2011. Term Premia and Inflation Uncertainty: Empirical Evidence from an International Panel Dataset. American Economic Review, 101(4), 1514 - 1534.