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Forecasting in efficient bond markets: Do experts know better?

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  • Baghestani, Hamid

Abstract

Term structure theory suggests that bond rates in efficient markets approximately follow a random walk. We show that the random walk forecasts of 10-year U.S. Treasury and Moody's Aaa corporate bond rates for 1988-2005 are generally unbiased. Blue Chip forecasts, however, are both biased and inferior to random walk forecasts. Both models produce unbiased forecasts of the default spread, with the random walk again outperforming the Blue Chip. In addition, Blue Chip fails to accurately predict directional change. Emphasizing that the success of the random walk model is theoretically expected, we discuss why experts fail to beat random walk predictions.

Suggested Citation

  • Baghestani, Hamid, 2009. "Forecasting in efficient bond markets: Do experts know better?," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 624-630, October.
  • Handle: RePEc:eee:reveco:v:18:y:2009:i:4:p:624-630
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    References listed on IDEAS

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    1. Greer, Mark, 2003. "Directional accuracy tests of long-term interest rate forecasts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 291-298.
    2. Pesando, James E, 1979. "On the Random Walk Characteristics of Short- and Long-Term Interest Rates in an Efficient Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 11(4), pages 457-466, November.
    3. Batchelor, Roy & Dua, Pami, 1991. "Blue Chip Rationality Tests," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 23(4), pages 692-705, November.
    4. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    5. 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.
    6. Joutz, Fred & Stekler, H. O., 2000. "An evaluation of the predictions of the Federal Reserve," International Journal of Forecasting, Elsevier, vol. 16(1), pages 17-38.
    7. Pesando, James E., 1981. "On forecasting interest rates : An efficient markets perspective," Journal of Monetary Economics, Elsevier, vol. 8(3), pages 305-318.
    8. Scharfstein, David S & Stein, Jeremy C, 1990. "Herd Behavior and Investment," American Economic Review, American Economic Association, vol. 80(3), pages 465-479, June.
    9. Yvon Fauvel & Alain Paquet & Christian Zimmermann, 1999. "A Survey on Interest Rate Forecasting," Cahiers de recherche CREFE / CREFE Working Papers 87, CREFE, Université du Québec à Montréal.
    10. David H. Romer & Christina D. Romer, 2000. "Federal Reserve Information and the Behavior of Interest Rates," American Economic Review, American Economic Association, vol. 90(3), pages 429-457, June.
    11. Mark R. Greer, 1999. "Assessing the Soothsayers: An Examination of the Track Record of Macroeconomic Forecasting," Journal of Economic Issues, Taylor & Francis Journals, vol. 33(1), pages 77-94, March.
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    Cited by:

    1. Hamid Baghestani, 2022. "Mortgage rate predictability and consumer home-buying assessments," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 593-603, July.
    2. van Ommeren, Bernard J.F. & Allers, Maarten A. & Vellekoop, Michel H., 2017. "Choosing the optimal moment to arrange a loan," Research Report 17007-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    3. Hamid Baghestani, 2017. "Do US consumer survey data help beat the random walk in forecasting mortgage rates?," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1343017-134, January.

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