IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v59y2020i1d10.1007_s00181-019-01629-0.html
   My bibliography  Save this article

Investigating the expectation hypothesis and the risk premium dynamics: new evidence for Brazil

Author

Listed:
  • João F. Caldeira

    (Universidade Federal do Rio Grande do Sul & CNPq)

Abstract

We re-examine the validity of the expectation hypothesis (EH) of the term structure for the Brazilian fixed income market, using data from January 2000 to June 2017. Furthermore, we investigated the out-of-sample predictability of bond excess returns by means of common factors extracted from a cross-section of Brazilian macro-variables and zero-coupon interest rates. The EH is rejected throughout the term structure examined on the basis of the statistical tests across the entire maturity spectrum considered. Our results confirm previous findings, mostly obtained for developed markets, that a linear combination of forward rates and macroeconomic factors can explain a substantial portion of movements in bonds excess returns, contributing novel and up-to-date evidence from a large and dynamic emerging bond market, such as Brazil. Furthermore, we find that the factor extracted from a large panel of macroeconomic variables generates significant gains in forecasting bond excess returns relative to yield curve information.

Suggested Citation

  • João F. Caldeira, 2020. "Investigating the expectation hypothesis and the risk premium dynamics: new evidence for Brazil," Empirical Economics, Springer, vol. 59(1), pages 395-412, July.
  • Handle: RePEc:spr:empeco:v:59:y:2020:i:1:d:10.1007_s00181-019-01629-0
    DOI: 10.1007/s00181-019-01629-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-019-01629-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00181-019-01629-0?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Benjamin Tabak, 2009. "Testing the expectations hypothesis in the Brazilian term structure of interest rates: a cointegration analysis," Applied Economics, Taylor & Francis Journals, vol. 41(21), pages 2681-2689.
    3. Benjamin Miranda Tabak & Sandro Canesso de Andrade, 2003. "Testing the Expectations Hypothesis in the Brazilian Term Structure of Interest Rates," Brazilian Review of Finance, Brazilian Society of Finance, vol. 1(1), pages 19-43.
    4. Scott Joslin & Marcel Priebsch & Kenneth J. Singleton, 2014. "Risk Premiums in Dynamic Term Structure Models with Unspanned Macro Risks," Journal of Finance, American Finance Association, vol. 69(3), pages 1197-1233, June.
    5. Klein, William, 1990. "Forward Rates and the Expectations Theory of the Term Structure: Tests for the Federal Republic of Germany," Empirical Economics, Springer, vol. 15(3), pages 245-265.
    6. John H. Cochrane & Monika Piazzesi, 2005. "Bond Risk Premia," American Economic Review, American Economic Association, vol. 95(1), pages 138-160, March.
    7. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    8. Bernanke, Ben S & Blinder, Alan S, 1992. "The Federal Funds Rate and the Channels of Monetary Transmission," American Economic Review, American Economic Association, vol. 82(4), pages 901-921, September.
    9. Beechey, Meredith & Hjalmarsson, Erik & sterholm, Pr, 2009. "Testing the expectations hypothesis when interest rates are near integrated," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 934-943, May.
    10. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    11. John Y. Campbell & Robert J. Shiller, 1991. "Yield Spreads and Interest Rate Movements: A Bird's Eye View," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 495-514.
    12. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2016. "The economic value of predicting bond risk premia," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 247-267.
    13. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    14. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    15. 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.
    16. Ilan Cooper, 2009. "Time-Varying Risk Premiums and the Output Gap," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2601-2633, July.
    17. Thornton, Daniel L., 2005. "Tests of the expectations hypothesis: Resolving the anomalies when the short-term rate is the federal funds rate," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2541-2556, October.
    18. Daniel L. Thornton & Giorgio Valente, 2012. "Out-of-Sample Predictions of Bond Excess Returns and Forward Rates: An Asset Allocation Perspective," The Review of Financial Studies, Society for Financial Studies, vol. 25(10), pages 3141-3168.
    19. Jonathan H. Wright, 2011. "Term Premia and Inflation Uncertainty: Empirical Evidence from an International Panel Dataset," American Economic Review, American Economic Association, vol. 101(4), pages 1514-1534, June.
    20. Dahlquist, Magnus & Hasseltoft, Henrik, 2013. "International Bond Risk Premia," Journal of International Economics, Elsevier, vol. 90(1), pages 17-32.
    21. Zhu, Xiaoneng, 2015. "Out-of-sample bond risk premium predictions: A global common factor," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 155-173.
    22. Eriksen, Jonas N., 2017. "Expected Business Conditions and Bond Risk Premia," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(4), pages 1667-1703, August.
    23. Fama, Eugene F & Bliss, Robert R, 1987. "The Information in Long-Maturity Forward Rates," American Economic Review, American Economic Association, vol. 77(4), pages 680-692, September.
    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. Zhang, Han & Fan, Xiaoyun & Guo, Bin & Zhang, Wei, 2019. "Reexamining time-varying bond risk premia in the post-financial crisis era," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    2. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024. "Predicting Bond Return Predictability," Management Science, INFORMS, vol. 70(2), pages 931-951, February.
    3. De Rezende, Rafael B., 2015. "Risks in macroeconomic fundamentals and excess bond returns predictability," Working Paper Series 295, Sveriges Riksbank (Central Bank of Sweden).
    4. Antonio Gargano & Davide Pettenuzzo & Allan Timmermann, 2019. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Management Science, INFORMS, vol. 65(2), pages 508-540, February.
    5. Jing-Zhi Huang & Zhan Shi, 2023. "Machine-Learning-Based Return Predictors and the Spanning Controversy in Macro-Finance," Management Science, INFORMS, vol. 69(3), pages 1780-1804, March.
    6. Wan, Runqing & Fulop, Andras & Li, Junye, 2022. "Real-time Bayesian learning and bond return predictability," Journal of Econometrics, Elsevier, vol. 230(1), pages 114-130.
    7. Zhang, Han & Guo, Bin & Liu, Lanbiao, 2022. "The time-varying bond risk premia in China," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 51-76.
    8. Feng Zhao & Guofu Zhou & Xiaoneng Zhu, 2021. "Unspanned Global Macro Risks in Bond Returns," Management Science, INFORMS, vol. 67(12), pages 7825-7843, December.
    9. Zhu, Xiaoneng, 2015. "Out-of-sample bond risk premium predictions: A global common factor," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 155-173.
    10. Mirco Rubin & Dario Ruzzi, 2020. "Equity tail risk in the treasury bond market," Temi di discussione (Economic working papers) 1311, Bank of Italy, Economic Research and International Relations Area.
    11. Mirco Rubin & Dario Ruzzi, 2020. "Equity Tail Risk in the Treasury Bond Market," Papers 2007.05933, arXiv.org.
    12. Andrea Berardi & Michael Markovich & Alberto Plazzi & Andrea Tamoni, 2021. "Mind the (Convergence) Gap: Bond Predictability Strikes Back!," Management Science, INFORMS, vol. 67(12), pages 7888-7911, December.
    13. Su, Hao & Ying, Chengwei & Zhu, Xiaoneng, 2022. "Disaster risk matters in the bond market," Finance Research Letters, Elsevier, vol. 47(PA).
    14. Guo, Bin & Huang, Fuzhe & Li, Kai, 2022. "Time to build and bond risk premia," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    15. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
    16. Tom Engsted & Stig V. Møller & Magnus Sander, 2013. "Bond return predictability in expansions and recessions," CREATES Research Papers 2013-13, Department of Economics and Business Economics, Aarhus University.
    17. Rui Liu, 2019. "Forecasting Bond Risk Premia with Unspanned Macroeconomic Information," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 9(01), pages 1-62, March.
    18. Çepni, Oğuzhan & Guney, I. Ethem & Gupta, Rangan & Wohar, Mark E., 2020. "The role of an aligned investor sentiment index in predicting bond risk premia of the U.S," Journal of Financial Markets, Elsevier, vol. 51(C).
    19. Huang, Dashan & Jiang, Fuwei & Li, Kunpeng & Tong, Guoshi & Zhou, Guofu, 2023. "Are bond returns predictable with real-time macro data?," Journal of Econometrics, Elsevier, vol. 237(2).
    20. Laborda, Ricardo & Olmo, Jose, 2014. "Investor sentiment and bond risk premia," Journal of Financial Markets, Elsevier, vol. 18(C), pages 206-233.

    More about this item

    Keywords

    Expectation hypothesis; Bond risk premia; Factor models; Excess return predictability; Out-of-sample forecasts;
    All these keywords.

    JEL classification:

    • 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
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:spr:empeco:v:59:y:2020:i:1:d:10.1007_s00181-019-01629-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.