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Year-end seasonality in one-month LIBOR derivatives

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Abstract

We examine the markets for one-month LIBOR futures contracts and options on those futures for a year-end price effect consistent with the previously identified year-end rate increase in one-month LIBOR. The cash market rate increase appears in forward rates and derivative prices, which allows the derivatives to properly hedge year-end interest rate risk. However, while the year-end effect appears in the derivative contract, these derivative contracts provide biased forecasts of both future interest rates and their volatility. The bias appears to be different at year's end for the LIBOR futures contract, but not for the options contract. The information in the derivatives almost always subsumes simple benchmark forecasts. ; Earlier title: Seasonality in one-month LIBOR derivatives

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  • Christopher J. Neely & Drew B. Winters, 2005. "Year-end seasonality in one-month LIBOR derivatives," Working Papers 2003-040, Federal Reserve Bank of St. Louis.
    • Handle: RePEc:fip:fedlwp:2003-040
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    1. James D. Hamilton & Oscar Jorda, 2002. "A Model of the Federal Funds Rate Target," Journal of Political Economy, University of Chicago Press, vol. 110(5), pages 1135-1167, October.
    2. Robert F. Engle & Joshua Rosenberg, 1966. "Testing the Volatility Term Structure Using Option Hedging Criteria," New York University, Leonard N. Stern School Finance Department Working Paper Seires 96-24, New York University, Leonard N. Stern School of Business-.
    3. Jorion, Philippe, 1995. "Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-528, June.
    4. Jones, Steven L & Singh, Manoj K, 1997. "The Distribution of Stock Returns Implied in Their Options at the Turn-of-the-Year: A Test of Seasonal Volatility," The Journal of Business, University of Chicago Press, vol. 70(2), pages 281-311, April.
    5. Jordan, Susan D. & Jordan, Bradford D., 1991. "Seasonality in Daily Bond Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 26(2), pages 269-285, June.
    6. Ogden, Joseph P., 1987. "The End of the Month as a Preferred Habitat: A Test of Operational Efficiency in the Money Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(3), pages 329-343, September.
    7. Allen, Linda & Saunders, Anthony, 1992. "Bank window dressing: Theory and evidence," Journal of Banking & Finance, Elsevier, vol. 16(3), pages 585-623, June.
    8. Canina, Linda & Figlewski, Stephen, 1993. "The Informational Content of Implied Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 659-681.
    9. Griffiths, Mark D & Winters, Drew B, 1996. "The Relation between the Federal Funds Cash and Futures Markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 19(3), pages 359-376, Fall.
    10. Johnston, Elizabeth Tashijan & Kracaw, William A. & McConnell, John J., 1991. "Day-of-the-Week Effects in Financial Futures: An Analysis of GNMA, T-Bond, T-Note, and T-Bill Contracts," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 26(1), pages 23-44, March.
    11. 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.
    12. Christopher J. Neely, 2004. "Implied volatility from options on gold futures: do statistical forecasts add value or simply paint the lilly?," Working Papers 2003-018, Federal Reserve Bank of St. Louis.
    13. Latane, Henry A & Rendleman, Richard J, Jr, 1976. "Standard Deviations of Stock Price Ratios Implied in Option Prices," Journal of Finance, American Finance Association, vol. 31(2), pages 369-381, May.
    14. Barone-Adesi, Giovanni & Whaley, Robert E, 1987. "Efficient Analytic Approximation of American Option Values," Journal of Finance, American Finance Association, vol. 42(2), pages 301-320, June.
    15. Lamoureux, Christopher G & Lastrapes, William D, 1993. "Forecasting Stock-Return Variance: Toward an Understanding of Stochastic Implied Volatilities," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 293-326.
    16. Mark D. Griffiths & Drew B. Winters, 1996. "The Relation Between The Federal Funds Cash And Futures Markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 19(3), pages 359-376, September.
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    Cited by:

    1. Bruce Mizrach & Christopher J. Neely, 2007. "The microstructure of the U.S. treasury market," Working Papers 2007-052, Federal Reserve Bank of St. Louis.
    2. Jens H. E. Christensen & Jose A. Lopez & Glenn D. Rudebusch, 2014. "Do Central Bank Liquidity Facilities Affect Interbank Lending Rates?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(1), pages 136-151, January.

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    Econometrics; Monetary policy; Finance;
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