IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/202516.html

Forecasting Spot and Futures Price Volatility of Agricultural Commodities: The Role of Climate-Related Migration Uncertainty

Author

Listed:
  • Afees A. Salisu

    (Centre for Econometrics and Applied Research, Ibadan, Nigeria; Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Ahamuefula E. Ogbonna

    (Centre for Econometrics and Applied Research, Ibadan, Nigeria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Elie Bouri

    (School of Business, Lebanese American University, Lebanon)

Abstract

We evaluate the predictive ability of the newly developed climate-related migration uncertainty index (CMUI) and its two components, the climate uncertainty index (CUI) and the migration uncertainty index (MUI), for the return volatility of agricultural commodity prices in both futures and spot markets. Employing a GARCH-MIDAS model, based on mixed data frequencies covering the period from 1977Q4 (with the earliest daily observation on October 3, 1977) to 2024Q1 (with the latest daily observation on March 29, 2024), we conduct both statistical and economic evaluations, including the Modified Diebold-Mariano test, Model Confidence Set procedure, and risk-adjusted performance metrics. The results demonstrate that integrating CUI, MUI, and CMUI into the predictive model of the return volatility of agricultural commodity prices significantly improves forecast accuracy relative to the conventional GARCH-MIDAS-RV benchmark. These findings suggest that the climate and migration related uncertainty indices are both statistically significant and economically relevant, offering enhanced predictive power and investment performance.

Suggested Citation

  • Afees A. Salisu & Ahamuefula E. Ogbonna & Rangan Gupta & Elie Bouri, 2025. "Forecasting Spot and Futures Price Volatility of Agricultural Commodities: The Role of Climate-Related Migration Uncertainty," Working Papers 202516, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202516
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chia‐Hsien Tang & Yen‐Hsien Lee & Hung‐Chun Liu & Guan‐Gzhe Zeng, 2024. "Exploring the unpredictable nature of climate policy uncertainty: An empirical analysis of its impact on commodity futures returns in the United States," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(7), pages 1277-1292, July.
    2. Emanuele Campiglio & Louis Daumas & Pierre Monnin & Adrian von Jagow, 2023. "Climate‐related risks in financial assets," Journal of Economic Surveys, Wiley Blackwell, vol. 37(3), pages 950-992, July.
    3. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2024. "Financial stress and realized volatility: The case of agricultural commodities," Research in International Business and Finance, Elsevier, vol. 71(C).
    4. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
    5. Salisu, Afees A. & Gupta, Rangan & Demirer, Riza, 2022. "Global financial cycle and the predictability of oil market volatility: Evidence from a GARCH-MIDAS model," Energy Economics, Elsevier, vol. 108(C).
    6. Ioannis Chatziantoniou & Stavros Degiannakis & George Filis & Tim Lloyd, 2021. "Oil Price Volatility is Effective in Predicting Food Price Volatility. Or is it?," The Energy Journal, , vol. 42(6), pages 25-48, November.
    7. Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2022. "Forecasting realized volatility of agricultural commodities," International Journal of Forecasting, Elsevier, vol. 38(1), pages 74-96.
    8. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Ji, Qiang, 2024. "Energy market uncertainties and exchange rate volatility: A GARCH-MIDAS approach," Finance Research Letters, Elsevier, vol. 67(PB).
    9. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
    10. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    11. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    12. Yang, Ke & Tian, Fengping & Chen, Langnan & Li, Steven, 2017. "Realized volatility forecast of agricultural futures using the HAR models with bagging and combination approaches," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 276-291.
    13. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2088-2125, September.
    14. Jiawen Luo & Qun Zhang, 2024. "Air pollution, weather factors, and realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 151-217, February.
    15. Colacito, Riccardo & Engle, Robert F. & Ghysels, Eric, 2011. "A component model for dynamic correlations," Journal of Econometrics, Elsevier, vol. 164(1), pages 45-59, September.
    16. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    17. Nam, Kyungsik, 2021. "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, vol. 96(C).
    18. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    19. Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
    20. Bayaa, Yasmeen & Qadan, Mahmoud, 2024. "The shape of the Treasury yield curve and commodity prices," International Review of Financial Analysis, Elsevier, vol. 94(C).
    21. Liu, Jing & Ma, Feng & Tang, Yingkai & Zhang, Yaojie, 2019. "Geopolitical risk and oil volatility: A new insight," Energy Economics, Elsevier, vol. 84(C).
    22. Peter R. Hansen & Asger Lunde & James M. Nason, 2011. "The Model Confidence Set," Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
    23. Kirsty Lewis & Claire Witham, 2012. "Agricultural commodities and climate change," Climate Policy, Taylor & Francis Journals, vol. 12(sup01), pages 53-61, September.
    24. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2021. "The realized volatility of commodity futures: Interconnectedness and determinants#," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 139-151.
    25. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Lasisi, Lukman & Olaniran, Abeeb, 2022. "Geopolitical risk and stock market volatility in emerging markets: A GARCH – MIDAS approach," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    26. Sisa Shiba & Goodness C. Aye & Rangan Gupta & Samrat Goswami, 2022. "Forecastability of Agricultural Commodity Futures Realised Volatility with Daily Infectious Disease-Related Uncertainty," JRFM, MDPI, vol. 15(11), pages 1-15, November.
    27. repec:aen:journl:ej42-6-filis is not listed on IDEAS
    28. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    29. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    30. Rangan Gupta & Christian Pierdzioch, 2024. "Multi-Task Forecasting of the Realized Volatilities of Agricultural Commodity Prices," Mathematics, MDPI, vol. 12(18), pages 1-26, September.
    31. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.
    32. Hardik A. Marfatia & Qiang Ji & Jiawen Luo, 2022. "Forecasting the volatility of agricultural commodity futures: The role of co‐volatility and oil volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 383-404, March.
    33. Fengping Tian & Ke Yang & Langnan Chen, 2017. "Realized Volatility Forecasting of Agricultural Commodity Futures Using Long Memory and Regime Switching," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(4), pages 421-430, July.
    34. Ordu, Beyza Mina & Oran, Adil & Soytas, Ugur, 2018. "Is food financialized? Yes, but only when liquidity is abundant," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 82-96.
    35. Lukman Lasisi & Philip C. Omoke & Afees A. Salisu, 2024. "Climate Policy Uncertainty and Stock Market Volatility," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 5(2), pages 1-6.
    36. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    37. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    38. Jacobus Nel & Rangan Gupta & Mark E. Wohar & Christian Pierdzioch, 2024. "Climate Risks And Predictability Of Commodity Returns And Volatility: Evidence From Over 750 Years Of Data," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 1-40, November.
    39. Lukman A. Lasisi & Franklin N. Ngwu & Mohammed K. Taliat & Abeeb O. Olaniran & Kelechi C. Nnamdi, 2025. "Modelling commodity market volatility with climate policy uncertainty: a GARCH-MIDAS approach," SN Business & Economics, Springer, vol. 5(3), pages 1-21, March.
    40. Qadan, Mahmoud, 2019. "Risk appetite and the prices of precious metals," Resources Policy, Elsevier, vol. 62(C), pages 136-153.
    41. Christian Conrad & Anessa Custovic & Eric Ghysels, 2018. "Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis," JRFM, MDPI, vol. 11(2), pages 1-12, May.
    42. Faccini, Renato & Matin, Rastin & Skiadopoulos, George, 2023. "Dissecting climate risks: Are they reflected in stock prices?," Journal of Banking & Finance, Elsevier, vol. 155(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. Rangan Gupta & Christian Pierdzioch, 2024. "Multi-Task Forecasting of the Realized Volatilities of Agricultural Commodity Prices," Mathematics, MDPI, vol. 12(18), pages 1-26, September.
    2. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2024. "Financial stress and realized volatility: The case of agricultural commodities," Research in International Business and Finance, Elsevier, vol. 71(C).
    3. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2088-2125, September.
    4. Fava, Santino Del & Gupta, Rangan & Pierdzioch, Christian & Rognone, Lavinia, 2024. "Forecasting international financial stress: The role of climate risks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
    7. Afees A. Salisu & Riza Demirer & Rangan Gupta, 2023. "Policy uncertainty and stock market volatility revisited: The predictive role of signal quality," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2307-2321, December.
    8. Zheng, Qingying & Wu, Jintao & Lin, Boqiang, 2025. "Performance of systemic stress in agricultural commodities and its implication for volatility prediction in SSA equities," Journal of Commodity Markets, Elsevier, vol. 39(C).
    9. Afees A. Salisu & Rangan Gupta & Oguzhan Cepni & Petre Caraiani, 2024. "Oil shocks and state-level stock market volatility of the United States: a GARCH-MIDAS approach," Review of Quantitative Finance and Accounting, Springer, vol. 63(4), pages 1473-1510, November.
    10. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    11. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun, 2023. "The effect of uncertainty on stock market volatility and correlation," Journal of Banking & Finance, Elsevier, vol. 154(C).
    12. Li, Xiafei & Liang, Chao & Chen, Zhonglu & Umar, Muhammad, 2022. "Forecasting crude oil volatility with uncertainty indicators: New evidence," Energy Economics, Elsevier, vol. 108(C).
    13. Dutta, Anupam & Uddin, Gazi Salah & Sheng, Lin Wen & Park, Donghyun & Zhu, Xuening, 2024. "Volatility dynamics of agricultural futures markets under uncertainties," Energy Economics, Elsevier, vol. 136(C).
    14. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Bouri, Elie, 2024. "Energy-related uncertainty and international stock market volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 280-293.
    15. Afees A. Salisu & Ahamuefula E.Oghonna & Rangan Gupta & Oguzhan Cepni, 2024. "Energy Market Uncertainties and US State-Level Stock Market Volatility: A GARCH-MIDAS Approach," Working Papers 202409, University of Pretoria, Department of Economics.
    16. Gong, Jue & Wang, Gang-Jin & Zhou, Yang & Xie, Chi, 2025. "Cross-market volatility forecasting with attention-based spatial–temporal graph convolutional networks," Journal of Empirical Finance, Elsevier, vol. 83(C).
    17. Salisu, Afees A. & Demirer, Riza & Gupta, Rangan, 2024. "Technological shocks and stock market volatility over a century," Journal of Empirical Finance, Elsevier, vol. 79(C).
    18. Liu, Jing & Ma, Feng & Tang, Yingkai & Zhang, Yaojie, 2019. "Geopolitical risk and oil volatility: A new insight," Energy Economics, Elsevier, vol. 84(C).
    19. Lu, Xinjie & Su, Yuandong & Huang, Dengshi, 2023. "Chinese agricultural futures volatility: New insights from potential domestic and global predictors," International Review of Financial Analysis, Elsevier, vol. 89(C).
    20. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • F22 - International Economics - - International Factor Movements and International Business - - - International Migration
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness

    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:pre:wpaper:202516. 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: Rangan Gupta (email available below). General contact details of provider: https://edirc.repec.org/data/decupza.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.