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Implied volatility forecasts in the grains complex

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  • David P. Simon

Abstract

This article finds that the implied volatilities of corn, soybean, and wheat futures options 4 weeks before option expiration have significant predictive power for the underlying futures contract return volatilities through option expiration from January 1988 through September 1999. These implied volatilities also encompass the information in out‐of‐sample seasonal Glosten, Jagannathan, and Runkle (GJR;1993) volatility forecasts. Evidence also demonstrates that when corn‐implied volatility rises relative to out‐of‐sample seasonal GJR volatility forecasts, implied volatility substantially overpredicts realized volatility. However, simulations of trading rules that involve selling corn option straddles when corn‐implied volatility is high relative to out‐of‐sample GJR volatility forecasts indicate that none of the trading rules would have been significantly profitable. This finding suggests that these options are not necessarily overpriced. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:959–981, 2002

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  • David P. Simon, 2002. "Implied volatility forecasts in the grains complex," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(10), pages 959-981, October.
    • Handle: RePEc:wly:jfutmk:v:22:y:2002:i:10:p:959-981
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    Cited by:

    1. Riza Emekter & Benjamas Jirasakuldech & Peter Went, 2012. "Rational speculative bubbles and commodities markets: application of duration dependence test," Applied Financial Economics, Taylor & Francis Journals, vol. 22(7), pages 581-596, April.
    2. Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(11), pages 1141-1152, November.
    3. Athanasios Triantafyllou & George Dotsis & Alexandros Sarris, 2020. "Assessing the Vulnerability to Price Spikes in Agricultural Commodity Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 631-651, September.
    4. Awartani, Basel & Aktham, Maghyereh & Cherif, Guermat, 2016. "The connectedness between crude oil and financial markets: Evidence from implied volatility indices," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 56-69.
    5. Barr, Kanlaya Jintanakul, 2009. "The implied volatility bias and option smile: is there a simple explanation?," ISU General Staff Papers 200901010800002026, Iowa State University, Department of Economics.
    6. Prokopczuk, Marcel & Symeonidis, Lazaros & Wese Simen, Chardin, 2017. "Variance risk in commodity markets," Journal of Banking & Finance, Elsevier, vol. 81(C), pages 136-149.
    7. Finta, Marinela Adriana & Ornelas, José Renato Haas, 2022. "Commodity return predictability: Evidence from implied variance, skewness, and their risk premia☆☆," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    8. Dominik Boos, 2024. "Risky times: Seasonality and event risk of commodities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(5), pages 767-783, May.
    9. Maghyereh, Aktham & Abdoh, Hussein & Awartani, Basel, 2022. "Have returns and volatilities for financial assets responded to implied volatility during the COVID-19 pandemic?," Journal of Commodity Markets, Elsevier, vol. 26(C).

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