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

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  • 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
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    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.
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    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

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