IDEAS home Printed from https://ideas.repec.org/p/ags/asea26/404810.html

How Economic News Drives Implied Volatility in Agricultural Commodity Markets

Author

Listed:
  • Yan, Hongqiang
  • Manfredo, Mark
  • Mishra, Ashok

Abstract

We examine whether broad economic news Granger-causes implied volatility derived from options on agricultural futures markets. Using approximately 1.5 million Wall Street Journal articles (1984–2026), we construct 180 daily news topic attention series via Latent Dirichlet Allocation and apply a high-dimensional Granger causality framework that combines sparse-group LASSO variable selection with debiased inference and HAC standard errors. Using implied volatility measures provided by Bloomberg, we find that financial and macroeconomic news topics systematically Granger-cause implied volatility across corn, soybeans, soybean meal, and soybean oil markets and across Bloomberg constant-maturity horizons of 30 days, 60 days, and 3 months. Topics related to program trading and index arbitrage, investment banking, and the 2008 financial crisis are the most robust across commodities, consistent with the financialization of agricultural futures markets. The number of significant news topics declines from 23 at the 30-day maturity to 10 at the 3-month maturity, suggesting that financial news primarily influences short-term uncertainty. A crop-specific news topic is not selected for any commodity-maturity combination. This may be due to crop fundamentals being transmitted to implied volatility through scheduled USDA report releases rather than through ongoing national media coverage.

Suggested Citation

  • Yan, Hongqiang & Manfredo, Mark & Mishra, Ashok, 2026. "How Economic News Drives Implied Volatility in Agricultural Commodity Markets," 3rd ASEAN University Symposium for Sustainable Food Systems, Faculty of Agriculture, Chiang Mai University, Thailand, May 21-22, 2026 404810, Association of Southeast Asian Nations (ASEAN).
    • Handle: RePEc:ags:asea26:404810
    DOI: 10.22004/ag.econ.404810
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/404810/files/Hongqiang_Yan_Yan_Manfredo_Mishra_NCCC_134_2026.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.404810?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Raghav Goyal & Michael K. Adjemian, 2023. "Information rigidities in USDA crop production forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(5), pages 1405-1425, October.
    2. Irwin, Scott H. & Sanders, Dwight R., 2012. "Financialization and Structural Change in Commodity Futures Markets," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(3), pages 371-396, August.
    3. Luca Barbaglia & Sergio Consoli & Sebastiano Manzan, 2023. "Forecasting with Economic News," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 708-719, July.
    4. Xinyue He & Siyu Bian, 2025. "The Announcement Volatility Risk Premium in Agricultural Markets: Evidence From USDA Report Releases," Journal of Agricultural Economics, Wiley Blackwell, vol. 76(3), pages 651-665, September.
    5. Ardia, David & Bluteau, Keven, 2026. "Optimal text-based time-series indices," International Journal of Forecasting, Elsevier, vol. 42(1), pages 44-60.
    6. 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.
    7. Yongmiao Hong & Fuwei Jiang & Lingchao Meng & Bowen Xue, 2025. "Forecasting Inflation Using Economic Narratives," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 43(1), pages 216-231, January.
    8. Ke Tang & Wei Xiong, 2012. "Index Investment and the Financialization of Commodities," Financial Analysts Journal, Taylor & Francis Journals, vol. 68(6), pages 54-74, November.
    9. Yao Yang & Andrew McKenzie, 2025. "Do Corn Options Update Volatility Expectations in the Wake of USDA Reports?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(10), pages 1852-1868, October.
    10. Constant Aka & Marie‐Hélène Gagnon & Gabriel J. Power, 2025. "Commodity Option Return Predictability," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(10), pages 1544-1578, October.
    11. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2024. "High-Dimensional Granger Causality Tests with an Application to VIX and News," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 605-635.
    12. Rogmann, Jennifer & Beckmann, Joscha & Gaschler, Robert & Landmann, Helen, 2024. "Media sentiment emotions and consumer energy prices," Energy Economics, Elsevier, vol. 130(C).
    13. Leif Anders Thorsrud, 2020. "Words are the New Numbers: A Newsy Coincident Index of the Business Cycle," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 393-409, April.
    14. Baker, Scott R. & Bloom, Nicholas & Davis, Steven J. & Kost, Kyle, 2026. "Policy news and stock market volatility," Journal of Financial Economics, Elsevier, vol. 175(C).
    15. Trujillo-Barrera, Andres & Mallory, Mindy L. & Garcia, Philip, 2012. "Volatility Spillovers in U.S. Crude Oil, Ethanol, and Corn Futures Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-16, August.
    16. Philipp Adämmer & Rainer A Schüssler, 2020. "Forecasting the Equity Premium: Mind the News!," Review of Finance, European Finance Association, vol. 24(6), pages 1313-1355.
    17. Chi, Yeguang & El-Jahel, Lina & Vu, Thanh, 2024. "Novel and old news sentiment in commodity futures markets," Energy Economics, Elsevier, vol. 140(C).
    18. Cao, An N.Q. & Heckelei, Thomas & Ionici, Octavian & Robe, Michel A., 2024. "USDA reports affect the stock market, too," Journal of Commodity Markets, Elsevier, vol. 34(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Etienne, Xiaoli L. & Irwin, Scott H. & Garcia, Philip, 2013. "Dissecting Corn Price Movements with Directed Acyclic Graphs," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151279, Agricultural and Applied Economics Association.
    2. Filimonov, Vladimir & Bicchetti, David & Maystre, Nicolas & Sornette, Didier, 2014. "Quantification of the high level of endogeneity and of structural regime shifts in commodity markets," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 174-192.
    3. Chi, Yeguang & El-Jahel, Lina & Vu, Thanh, 2025. "Media emotion intensity and commodity futures pricing," Journal of Commodity Markets, Elsevier, vol. 37(C).
    4. Chi, Yeguang & El-Jahel, Lina & Vu, Thanh, 2024. "Novel and old news sentiment in commodity futures markets," Energy Economics, Elsevier, vol. 140(C).
    5. Adämmer, Philipp & Prüser, Jan & Schüssler, Rainer A., 2025. "Forecasting macroeconomic tail risk in real time: Do textual data add value?," International Journal of Forecasting, Elsevier, vol. 41(1), pages 307-320.
    6. Etienne, Xiaoli L. & Irwin, Scott H., 2014. "A Structural Approach to Disentangling Speculative and Fundamental Influences on the Price of Corn," 2014 Conference, April 21-22, 2014, St. Louis, Missouri 285810, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    7. Abeyie, Gabriel Appau, 2026. "Beyond news headlines and TF-IDF: Enhancing text-based forecasting models with validated collocations and improved attention," International Journal of Forecasting, Elsevier, vol. 42(3), pages 752-773.
    8. Steen, Marie & Gjolberg, Ole, 2016. "Commodity Price Co-Movements: Back to Normal," 2016 Conference, April 18-19, 2016, St. Louis, Missouri 285863, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    9. Dejan Živkov & Jovan Njegić & Marko Pećanac, 2019. "Multiscale interdependence between the major agricultural commodities," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 65(2), pages 82-92.
    10. Yao, Wei, 2025. "The US Quantitative Easing Monetary Policy and Commodities’ Prices," Other publications TiSEM 185d14d3-9dc2-4276-82ec-e, Tilburg University, School of Economics and Management.
    11. Yin, Libo & Zhou, Yimin, 2016. "What drives long-term oil market volatility? Fundamentals versus speculation," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy, vol. 10, pages 1-26.
    12. Syed Shehzad Hassan, 2022. "Unveiling Worldwide Fossil Fuel Demands and the Dynamics of the Carbon Market," Magna Carta: Contemporary Social Science, 50sea, vol. 1(2), pages 82-90, June.
    13. Chiarucci, Riccardo & Loffredo, Maria I. & Ruzzenenti, Franco, 2017. "Evidences for a structural change in the oil market before a financial crisis: The flat horizon effect," Research in International Business and Finance, Elsevier, vol. 42(C), pages 912-921.
    14. Ma, Richie & Serra, Teresa, 2026. "Fast but noisy: Why options react first in agricultural derivatives markets," 2026 Annual Meeting, July 26 - 28, 2026, Kansas City, Missouri 404352, Agricultural and Applied Economics Association.
    15. Ana I. Sanjuán-López & Philip J. Dawson, 2017. "Volatility Effects of Index Trading and Spillovers on US Agricultural Futures Markets: A Multivariate GARCH Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(3), pages 822-838, September.
    16. Enmao Liu & Cong Sui, 2026. "Does Sentiment Measured Through Language Models Encompass a Broader Expanse of Information From the Options Market?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 46(3), pages 489-510, March.
    17. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
    18. Pinto-Ávalos, Francisco & Bowe, Michael & Hyde, Stuart, 2024. "Revisiting the pricing impact of commodity market spillovers on equity markets," Journal of Commodity Markets, Elsevier, vol. 33(C).
    19. Luca Barbaglia & Sergio Consoli & Sebastiano Manzan & Luca Tiozzo Pezzoli & Elisa Tosetti, 2025. "Sentiment analysis of economic text: A lexicon‐based approach," Economic Inquiry, Western Economic Association International, vol. 63(1), pages 125-143, January.
    20. Amagbo, Roland & Geman, Hélyette, 2026. "Dynamic and asymmetric spillovers between crude oil, biofuels and agricultural commodities: Evidence from periods of geopolitical tensions and energy policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 108(C).

    More about this item

    Keywords

    ;
    ;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:asea26:404810. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aseanid.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.