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Do federal funds futures need adjustment for excess returns? a state-dependent approach

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  • Brent Bundick

Abstract

This paper utilizes a Markov-switching framework to model excess returns in federal funds futures contracts. This framework identifies a high-volatility state where excess returns are large, positive, and volatile and a low-volatility state where excess returns have a lower volatility and are small in absolute value. Federal funds futures rates require adjustment for excess returns only in the high-volatility state. Intermeeting rate cuts of the federal funds rate target always correspond with the high-volatility regime and can explain much of the variation in excess returns. This paper also examines previous return models and helps clarify the relationship between excess returns, business cycles, and intermeeting rate cuts. In real-time forecasting, however, the unadjusted futures rates outperform three different forecasting models. This result strengthens the case for unadjusted futures rates as a measure of monetary policy expectations.

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File URL: http://www.kansascityfed.org/Publicat/Reswkpap/PDF/RWP07-08.pdf
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Bibliographic Info

Paper provided by Federal Reserve Bank of Kansas City in its series Research Working Paper with number RWP 07-08.

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Date of creation: 2007
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Handle: RePEc:fip:fedkrw:rwp07-08

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Keywords: Federal funds;

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References

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  1. Refet Gurkaynak & Brian Sack & Eric Swanson, 2005. "Do Actions Speak Louder than Words? The Response of Asset Prices to Monetary Policy Actions and Statements," Macroeconomics 0504013, EconWPA.
  2. Monika Piazzesi & Eric Swanson, 2004. "Future prices as risk-adjusted forecasts of monetary policy," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  3. Ben S. Bernanke & Kenneth N. Kuttner, 2003. "What explains the stock market's reaction to Federal Reserve policy?," Staff Reports 174, Federal Reserve Bank of New York.
  4. Hansen, Lars Peter & Hodrick, Robert J, 1980. "Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric Analysis," Journal of Political Economy, University of Chicago Press, vol. 88(5), pages 829-53, October.
  5. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  6. Bessec Marie & Bouabdallah Othman, 2005. "What Causes The Forecasting Failure of Markov-Switching Models? A Monte Carlo Study," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-24, June.
  7. Troy Davig & Jeffrey R. Gerlach, 2006. "State-Dependent Stock Market Reactions to Monetary Policy," International Journal of Central Banking, International Journal of Central Banking, vol. 2(4), December.
  8. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388.
  9. Craig S. Hakkio, 1980. "Expectations and the Forward Exchange Rate," NBER Working Papers 0439, National Bureau of Economic Research, Inc.
  10. J. Benson Durham, 2003. "Estimates of the term premium on near-dated federal funds futures contracts," Finance and Economics Discussion Series 2003-19, Board of Governors of the Federal Reserve System (U.S.).
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Cited by:
  1. Lapp, John S. & Pearce, Douglas K., 2012. "The impact of economic news on expected changes in monetary policy," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 362-379.

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