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Trend and cycle in bond premia


  • Monika Piazzesi
  • Martin Schneider


Common statistical measures of bond risk premia are volatile and countercyclical. This paper uses survey data on interest rate forecasts to construct subjective bond risk premia. Subjective premia are less volatile and not very cyclical; instead they are high, only around the early 1980s. The reason for the discrepancy is that survey forecasts of interest rates are made as if both the level and the slope of the yield curve are more persistent than under common statistical models. The paper then proposes a consumption based asset pricing model with learning to explain jointly the difference between survey and statistical forecasts, and the evolution of subjective premia. Adaptive learning gives rise to inertia in forecasts, as well as changes in conditional volatility that help understand both features. ; This paper is an extension of Monika Piazzesi's and Martin Schneider's work while they were in the Research Department of the Federal Reserve Bank of Minneapolis.

Suggested Citation

  • Monika Piazzesi & Martin Schneider, 2009. "Trend and cycle in bond premia," Staff Report 424, Federal Reserve Bank of Minneapolis.
  • Handle: RePEc:fip:fedmsr:424

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    References listed on IDEAS

    1. Krainer, John, 2001. "A Theory of Liquidity in Residential Real Estate Markets," Journal of Urban Economics, Elsevier, vol. 49(1), pages 32-53, January.
    2. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    3. Wheaton, William C, 1990. "Vacancy, Search, and Prices in a Housing Market Matching Model," Journal of Political Economy, University of Chicago Press, vol. 98(6), pages 1270-1292, December.
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    Cited by:

    1. Yu-chin Chen & Kwok Ping Tsang & Wen Jen Tsay, 2010. "Home Bias in Currency Forecasts," Working Papers e07-18, Virginia Polytechnic Institute and State University, Department of Economics.
    2. Zhu, Xiaoneng, 2011. "Revisiting the expectations hypothesis: The Japanese term structure and regime shifts," Journal of Economics and Business, Elsevier, vol. 63(3), pages 237-249, May.
    3. 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.
    4. Taeyoung Doh, 2013. "Long‐Run Risks In The Term Structure Of Interest Rates: Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(3), pages 478-497, April.
    5. Kristoffer Nimark, 2009. "Speculative dynamics in the term structure of interest rates," Economics Working Papers 1194, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2012.
    6. Zhu, Xiaoneng, 2011. "A note on the predictability of excess bond returns and regime shifts," Finance Research Letters, Elsevier, vol. 8(2), pages 101-109, June.

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