IDEAS home Printed from https://ideas.repec.org/p/zbw/safewp/331899.html

What 200 years of data tell us about the predictive variance of long-term bonds

Author

Listed:
  • Della Corte, Pasquale
  • Gao, Can
  • Preve, Daniel P. A.
  • Valente, Giorgio

Abstract

This paper investigates the long-horizon predictive variance of an international bond strategy where a U.S. investor holds unhedged positions in constant-maturity long-term foreign bonds funded at domestic short-term interest rates. Using over two centuries of data from major economies, the study finds that predictive variance grows with the investment horizon, driven primarily by uncertainties in interest rate differentials and exchange rate returns, which outweigh mean reversion effects. The analysis, incorporating both observable and unobservable predictors, highlights that unobservable predictors linked to shifts in monetary and exchange rate regimes are the dominant source of long-term risk, offering fresh insights into international bond investment strategies.

Suggested Citation

  • Della Corte, Pasquale & Gao, Can & Preve, Daniel P. A. & Valente, Giorgio, 2025. "What 200 years of data tell us about the predictive variance of long-term bonds," SAFE Working Paper Series 460, Leibniz Institute for Financial Research SAFE.
  • Handle: RePEc:zbw:safewp:331899
    DOI: 10.2139/ssrn.5734512
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/331899/1/1942040474.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.2139/ssrn.5734512?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kim, Tae-Hwan & White, Halbert, 2004. "On more robust estimation of skewness and kurtosis," Finance Research Letters, Elsevier, vol. 1(1), pages 56-73, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Per Hjertstrand & Pehr-Johan Norbäck & Lars Persson, 2020. "Skill Formation, Temporary Disadvantage and Elite Education," CESifo Working Paper Series 8612, CESifo.
    2. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    3. Noori, Mohammad & Hitaj, Asmerilda, 2023. "Dissecting hedge funds' strategies," International Review of Financial Analysis, Elsevier, vol. 85(C).
    4. Lujano-Rojas, Juan M. & Monteiro, Cláudio & Dufo-López, Rodolfo & Bernal-Agustín, José L., 2012. "Optimum load management strategy for wind/diesel/battery hybrid power systems," Renewable Energy, Elsevier, vol. 44(C), pages 288-295.
    5. Niklas Ahlgren & Alexander Back & Timo Terasvirta, 2025. "Testing parametric additive time-varying GARCH models," Papers 2506.23821, arXiv.org.
    6. Hutson, Elaine & Kearney, Colm & Lynch, Margaret, 2008. "Volume and skewness in international equity markets," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1255-1268, July.
    7. Changli He & Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Parameterizing Unconditional Skewness in Models for Financial Time Series," Journal of Financial Econometrics, Oxford University Press, vol. 6(2), pages 208-230, Spring.
    8. Chang, Bo Young & Christoffersen, Peter & Jacobs, Kris, 2013. "Market skewness risk and the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 107(1), pages 46-68.
    9. Hjertstrand, Per & Norbäck, Pehr-Johan & Persson, lars, 2017. "The Educated Underdog Becomes the Ultimate Superstar," Working Paper Series 1176, Research Institute of Industrial Economics.
    10. Briec, Walter & Kerstens, Kristiaan, 2010. "Portfolio selection in multidimensional general and partial moment space," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 636-656, April.
    11. A Ford Ramsey, 2020. "Probability Distributions of Crop Yields: A Bayesian Spatial Quantile Regression Approach," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 220-239, January.
    12. Timo Teräsvirta, 2009. "An Introduction to Univariate GARCH Models," Springer Books, in: Thomas Mikosch & Jens-Peter Kreiß & Richard A. Davis & Torben Gustav Andersen (ed.), Handbook of Financial Time Series, chapter 1, pages 17-42, Springer.
    13. Sanjiv Jaggia & Alison Kelly-Hawke, 2009. "Modelling skewness and elongation in financial returns: the case of exchange-traded funds," Applied Financial Economics, Taylor & Francis Journals, vol. 19(16), pages 1305-1316.
    14. Tamara Broderick & Ryan Giordano & Rachael Meager, 2020. "An Automatic Finite-Sample Robustness Metric: When Can Dropping a Little Data Make a Big Difference?," Papers 2011.14999, arXiv.org, revised Jul 2023.
    15. Martin Eling & Simone Farinelli & Damiano Rossello & Luisa Tibiletti, 2010. "Skewness in hedge funds returns: classical skewness coefficients vs Azzalini's skewness parameter," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 6(4), pages 290-304, September.
    16. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tédongap, 2016. "Which parametric model for conditional skewness?," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1237-1271, October.
    17. Stelios Bekiros & Amanda Dahlström & Gazi Salah Uddin & Oskar Ege & Ranadeva Jayasekera, 2020. "A tale of two shocks: The dynamics of international real estate markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(1), pages 3-27, January.
    18. Colin Ferguson & Matthew Pinnuck & Douglas J. Skinner, 2025. "Why did the Big Four get so large? Evidence from Australia," Review of Accounting Studies, Springer, vol. 30(3), pages 2508-2554, September.
    19. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    20. Ji Ho Kwon, 2021. "On the factors of Bitcoin’s value at risk," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:safewp:331899. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/csafede.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.