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Market uncertainty and sentiment around USDA announcements

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  • An N. Q. Cao
  • Michel A. Robe

Abstract

We investigate forward‐looking commodity price volatility expectations (proxied by option‐implied volatilities or IVols) around scheduled US Department of Agriculture (USDA) reports. We show that corn and soybean IVols are significantly lower for several trading days after a report. The IVol response to a release depends on agricultural market experts' disagreement and sentiment before the USDA report, and on the extent to which the USDA information surprises the market. Whereas commodity IVols are generally positively related to financial‐market sentiment and macroeconomic uncertainty (jointly captured by the volatility index [VIX]), this comovement breaks down on report days—with the VIX and commodity IVols moving in opposite directions.

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  • 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.
    • Handle: RePEc:wly:jfutmk:v:42:y:2022:i:2:p:250-275
    DOI: 10.1002/fut.22283
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    5. Ben Chamberlain & Zhangxin (Frank) Liu & Lee A. Smales, 2023. "Short interest and the stock market relation with news sentiment from traditional and social media sources," Australian Economic Papers, Wiley Blackwell, vol. 62(2), pages 321-334, June.
    6. Capitani, Daniel H D & Mattos, Fabio L. & Cruz, Jose Cesar & Silva, Renato Moraes & Franco Da Silveira, Rodrigo Lanna, 2024. "The Reaction Of Corn Futures Prices To U.S. And Brazilian Crop Reports," 2024 Annual Meeting, July 28-30, New Orleans, LA 343571, Agricultural and Applied Economics Association.
    7. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    8. Akyildirim, Erdinc & Cepni, Oguzhan & Pham, Linh & Uddin, Gazi Salah, 2022. "How connected is the agricultural commodity market to the news-based investor sentiment?," Energy Economics, Elsevier, vol. 113(C).
    9. Ghosh, Bikramaditya & Pham, Linh & Gubareva, Mariya & Teplova, Tamara, 2023. "Energy transition metals and global sentiment: Evidence from extreme quantiles," Resources Policy, Elsevier, vol. 86(PA).
    10. Cao, An N.Q. & Gebrekidan, Bisrat Haile & Heckelei, Thomas & Robe, Michel A., 2022. "County-level USDA Crop Progress and Condition data, machine learning, and commodity market surprises," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322281, Agricultural and Applied Economics Association.

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