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The Term Structure of Implied Forward Volatility: Recovery and Informational Content in the Corn Options Market

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  • Thorsten M. Egelkraut
  • Philip Garcia
  • Bruce J. Sherrick
Abstract
Using a flexible method, we develop the term structure of volatility implied by corn futures options with differing maturities, and evaluate its ability to predict subsequent realized price volatility. The implied forward volatilities anticipate realized volatility well. For the nearby interval, the implied forward volatilities provide unbiased forecasts, and are superior to forecasts based on historical volatilities. For more distant intervals, early-year options predict the direction and magnitude of future volatility changes about as well as a three-year moving average and better than a naïve forecast. However, later-year options display less forecast power in part due to reduced trading activity. Copyright 2007, Oxford University Press.

Suggested Citation

  • Thorsten M. Egelkraut & Philip Garcia & Bruce J. Sherrick, 2007. "The Term Structure of Implied Forward Volatility: Recovery and Informational Content in the Corn Options Market," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(1), pages 1-11.
    • Handle: RePEc:oup:ajagec:v:89:y:2007:i:1:p:1-11
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    File URL: http://hdl.handle.net/10.1111/j.1467-8276.2007.00958.x
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    1. Egelkraut, Thorsten M. & Garcia, Philip, 2006. "Intermediate Volatility Forecasts Using Implied Forward Volatility: The Performance of Selected Agricultural Commodity Options," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 31(3), pages 1-21, December.
    2. Chang, Chia-Lin & Huang, Biing-Wen & Chen, Meng-Gu & McAleer, Michael, 2011. "Modelling the asymmetric volatility in hog prices in Taiwan: The impact of joining the WTO," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1491-1506.
    3. Andres Trujillo-Barrera & Philip Garcia & Mindy L Mallory, 2018. "Short-term price density forecasts in the lean hog futures market," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 121-142.
    4. Adjemian, Michael K. & Bruno, Valentina & Robe, Michel A. & Wallen, Jonathan, 2017. "What Drives Volatility Expectations in Grain and Oilseed Markets?," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258452, Agricultural and Applied Economics Association.
    5. Marin Bozic, 2010. "Pricing Options on Commodity Futures: The Role of Weather and Storage," Working Papers 1003, The Institute of Economics, Zagreb.
    6. Li, Xingyi & Zakamulin, Valeriy, 2020. "The term structure of volatility predictability," International Journal of Forecasting, Elsevier, vol. 36(2), pages 723-737.
    7. Chad E. Hart & Sergio H. Lence & Dermot J. Hayes & Na Jin, 2016. "Price Mean Reversion, Seasonality, and Options Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(3), pages 707-725.
    8. Chang, Chia-Lin & McAleer, Michael & Wang, Yu-Ann, 2018. "Modelling volatility spillovers for bio-ethanol, sugarcane and corn spot and futures prices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1002-1018.
    9. Paolo Libenzio Brignoli & Alessandro Varacca & Cornelis Gardebroek & Paolo Sckokai, 2024. "Machine learning to predict grains futures prices," Agricultural Economics, International Association of Agricultural Economists, vol. 55(3), pages 479-497, May.
    10. Zhiguang Wang & Scott W. Fausti & Bashir A. Qasmi, 2012. "Variance risk premiums and predictive power of alternative forward variances in the corn market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(6), pages 587-608, June.
    11. An N. Q. Cao & Michel A. Robe, 2022. "Market uncertainty and sentiment around USDA announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(2), pages 250-275, February.
    12. Bozic, Marin & Newton, John & Thraen, Cameron S. & Gould, Brian W., 2014. "Parametric Bootstrap Tests for Futures Price and Implied Volatility Biases With Application to Rating Dairy Margin Insurance," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170416, Agricultural and Applied Economics Association.
    13. Xiaoyang Wang & Philip Garcia & Scott H. Irwin, 2014. "The Behavior of Bid-Ask Spreads in the Electronically-Traded Corn Futures Market," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(2), pages 557-577.
    14. Choe, Kyoungin & Goodwin, Barry K., 2024. "The Informational Role of Trading Volume in Thinly Traded Options Markets," 2024 Annual Meeting, July 28-30, New Orleans, LA 343732, Agricultural and Applied Economics Association.
    15. Chia-Lin Chang & Michael McAleer & Yu-Ann Wang, 2016. "Modelling volatility spillovers for bio-ethanol, sugarcane and corn," Documentos de Trabajo del ICAE 2016-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    16. Huang, Biing-Wen & Chen, Meng-Gu & Chang, Chia-Lin & McAleer, Michael, 2009. "Modelling risk in agricultural finance: Application to the poultry industry in Taiwan," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1472-1487.
    17. Covindassamy, Genevre & Robe, Michel A. & Wallen, Jonathan, 2016. "Sugar With Your Coffee?: Financials, Fundamentals, and Soft Price Uncertainty," IDB Publications (Working Papers) 8588, Inter-American Development Bank.
    18. Power, Gabriel J. & Turvey, Calum G., 2008. "On Term Structure Models of Commodity Futures Prices and the Kaldor-Working Hypothesis," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37608, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    19. Wu, Feng & Myers, Robert J. & Guan, Zhengfei & Wang, Zhiguang, 2015. "Risk-adjusted implied volatility and its performance in forecasting realized volatility in corn futures prices," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 260-274.
    20. Thomsen, Michael R. & McKenzie, Andrew M. & Power, Gabriel J., 2009. "Volatility Surface and Skewness in Live Cattle Futures Price Distributions with Application to North American BSE Announcements," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49354, Agricultural and Applied Economics Association.
    21. Giovanni Campisi & Silvia Muzzioli, 2021. "Designing volatility indices for Austria, Finland and Spain," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 369-455, September.
    22. Bozic, Marin & Newton, John & Thraen, Cameron S. & Gould, Brian W., 2012. "Parametric Bootstrap Tests for Futures Price and Implied Volatility Biases with Application to Rating Livestock Margin Insurance for Dairy Cattle," Staff Papers 135077, University of Minnesota, Department of Applied Economics.
    23. Anabelle Couleau & Teresa Serra & Philip Garcia, 2020. "Are Corn Futures Prices Getting “Jumpy”?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 569-588, March.
    24. Guimaraes, Jonathan S. & Cruz, Jose Cesar, 2017. "Future volatility forecast in agricultural commodity markets," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258480, Agricultural and Applied Economics Association.
    25. Chang, C-L. & Huang, B-W. & Chen, M-G., 2010. "Modelling the Asymmetric Volatility in Hog Prices in Taiwan," Econometric Institute Research Papers EI 2010-46, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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