HEDGING STRATEGIES INVOLVING AGRICULTURAL COMMODITIES: A SYSTEMATIC REVIEW OF LITERATURE
DOI:
https://doi.org/10.66104/444v3066Keywords:
Agricultural commodities, futures markets, systematic reviewAbstract
Purpose – To synthesize recent evidence on hedge effectiveness in agricultural commodity futures and clarify how futures-based strategies and models are used to manage price and basis risk. Design/methodology/approach – Systematic literature review using PRISMA in Web of Science and Scopus (2015–2024); 66 articles classified in a six-dimension framework (context, data source, commodity, hedge type, and modeling approach). Findings: futures contracts, especially for grains, predominate; GARCH-type models are most commonly used for volatility and hedge ratios; VAR/VEC models capture spot–futures dynamics; whereas machine learning, frontier/emerging markets, logistics, fuel costs, cross-hedging, and alternative assets are rarely examined. Research limitations/implications – Restricted to two databases and to articles in English and Portuguese; supports a focused agenda on neglected markets, risks, and methods. Originality/value – Provides a transparent, code-based map of recent studies on agricultural hedge effectiveness, highlighting overlooked markets, risk drivers, and methodological gaps.
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Anas, M., Bouri, E., & Shahzad, S. J. H. (2024). A Bibliometric analysis of literature on hedge and haven assets. Journal of Economic Surveys. https://doi.org/10.1111/joes.12677 DOI: https://doi.org/10.1111/joes.12677
Białkowski, J., Bohl, M. T., & Perera, D. (2023). Commodity futures hedge ratios: A meta-analysis. Journal of Commodity Markets, 30. https://doi.org/10.1016/j.jcomm.2022.100276 DOI: https://doi.org/10.1016/j.jcomm.2022.100276
Bolandifar, E., & Chen, Z. (2020). Hedging through index-based price contracts in commodity-based supply chains. Omega (United Kingdom), 90. https://doi.org/10.1016/j.omega.2018.10.006 DOI: https://doi.org/10.1016/j.omega.2018.10.006
Cardillo, M. A. dos R., & Basso, L. F. C. (2025). Revisiting knowledge on ESG/CSR and financial performance: A bibliometric and systematic review of moderating variables. Journal of Innovation and Knowledge, 10(1). https://doi.org/10.1016/j.jik.2024.100648 DOI: https://doi.org/10.1016/j.jik.2024.100648
Demiralay, S., Gencer, H. G., & Bayraci, S. (2022). Carbon credit futures as an emerging asset: Hedging, diversification, and downside risks. Energy Economics, 113. https://doi.org/10.1016/j.eneco.2022.106196 DOI: https://doi.org/10.1016/j.eneco.2022.106196
Diego Pitta de Jesus, Felipe Araújo de Oliveira, & Sinézio Fernandes Maia. (2021). Avaliação da razão ótima e efetividade do hedge das commodities agrícolas negociadas na B3 com o uso do modelo Garch-Bekk. Revista Evidenciação Contábil & Finanças, 9(2), 61–81. https://doi.org/10.22478/ufpb.2318-1001.2021v9n2.50483 DOI: https://doi.org/10.22478/ufpb.2318-1001.2021v9n2.50483
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070 DOI: https://doi.org/10.1016/j.jbusres.2021.04.070
Gairola, G., & Dey, K. (2023). Price discovery and risk management in asset classes: a bibliometric analysis and research agenda. Applied Economics Letters, 30(17), 2320–2331. https://doi.org/10.1080/13504851.2022.2096859 DOI: https://doi.org/10.1080/13504851.2022.2096859
Goswami, A., Karali, B., & Adjemian, M. K. (2023). Hedging with futures during nonconvergence in commodity markets. Journal of Commodity Markets, 32. https://doi.org/10.1016/j.jcomm.2023.100364 DOI: https://doi.org/10.1016/j.jcomm.2023.100364
Hazelkorn, T. M., Moskowitz, T. J., & Vasudevan, K. (2023). Beyond Basis Basics: Liquidity Demand and Deviations from the Law of One Price. Journal of Finance, 78(1), 301–345. https://doi.org/10.1111/jofi.13198 DOI: https://doi.org/10.1111/jofi.13198
Hrabynska, I., Kosarchyn, M., Dąbrowska, A., 2022. Economic imperatives of financialization of agricultural commodity markets. Agric. Resour. Econ. 8, 5–25. https://doi.org/10.51599/are.2022.08.03.01 DOI: https://doi.org/10.51599/are.2022.08.03.01
Hendry, D. F. ., & Doornik, J. A. . (2014). Empirical model discovery and theory evaluation : automatic selection methods in econometrics. The MIT Press. DOI: https://doi.org/10.7551/mitpress/9780262028356.001.0001
Huang, H., & Xiong, T. (2023). A good hedge or safe haven? The hedging ability of China’s commodity futures market under extreme market conditions. Journal of Futures Markets, 43(7), 968–1035. https://doi.org/10.1002/fut.22423 DOI: https://doi.org/10.1002/fut.22423
Huang, H., & Xiong, T. (2024). Are Chinese live hog futures useful hedging tools? Applied Economics. https://doi.org/10.1080/00036846.2024.2323023 DOI: https://doi.org/10.1080/00036846.2024.2323023
Huidan Xue (2024). Spatial price Transmission and Dynamic in Grain Markets: A TPV-VAR-Connectedness Approach. Foods 13,3317. https://doi.org/10.3390/foods13203317 DOI: https://doi.org/10.3390/foods13203317
Izadi, S., & Hassan, M. K. (2018). Portfolio and hedging effectiveness of financial assets of the G7 countries. Eurasian Economic Review, 8(2), 183–213. https://doi.org/10.1007/s40822-017-0090-0 DOI: https://doi.org/10.1007/s40822-017-0090-0
Jabbour, C. J. C. (2013). Environmental training in organisations: From a literature review to a framework for future research. Resources, Conservation and Recycling, 74, 144–155. https://doi.org/10.1016/j.resconrec.2012.12.017 DOI: https://doi.org/10.1016/j.resconrec.2012.12.017
Kang, S. H., McIver, R., & Yoon, S. M. (2017). Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets. Energy Economics, 62, 19–32. https://doi.org/10.1016/j.eneco.2016.12.011 DOI: https://doi.org/10.1016/j.eneco.2016.12.011
Lien, D., Shrestha, K., & Wu, J. (2016). Quantile Estimation of Optimal Hedge Ratio. Journal of Futures Markets, 36(2), 194–214. https://doi.org/10.1002/fut.21712 DOI: https://doi.org/10.1002/fut.21712
Linnenluecke, M. K., Marrone, M., & Singh, A. K. (2020). Conducting systematic literature reviews and bibliometric analyses. In Australian Journal of Management (Vol. 45, Issue 2, pp. 175–194). SAGE Publications Ltd. https://doi.org/10.1177/0312896219877678 DOI: https://doi.org/10.1177/0312896219877678
Louhichi, W., & Rais, H. (2019). Refinement of the hedging ratio using copula-GARCH models. Journal of Asset Management, 20(5), 403–411. https://doi.org/10.1057/s41260-019-00133-5 DOI: https://doi.org/10.1057/s41260-019-00133-5
Mandal, N., Agarwal, A.K., 2014. Arbitrage, Convergence, and long run equilibrium between futures and spot markets: a cointegration approach. Indian J. Appl. Res. 125, 125–128.
Markowitz, H., 1952. Portfolio selection. J. Financ. 7, 77–91. https://doi.org/10.2307/2975974 DOI: https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
Nardino, F. P., & Figueiredo, A. M. R. (2022). Basis risk and its volatility on the soya trade at Mato grosso (2009 to 2019). Revista de Economia e Sociologia Rural, 60(3), 1–21. https://doi.org/10.1590/1806-9479.2021.240267 DOI: https://doi.org/10.1590/1806-9479.2021.240267
Olson, E., Vivian, A., & Wohar, M. E. (2017). Do commodities make effective hedges for equity investors? Research in International Business and Finance, 42, 1274–1288. https://doi.org/10.1016/j.ribaf.2017.07.064 DOI: https://doi.org/10.1016/j.ribaf.2017.07.064
Ouzan, S., & Six, P. (2024). The demand for hedging of oil producers: A tale of risk and regret. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2024.09.036 DOI: https://doi.org/10.1016/j.ejor.2024.09.036
Palazzi, R. B., Assaf, A., & Klotzle, M. C. (2024). Dynamic connectedness between energy markets and the Brazilian cash market: An empirical analysis pre- and post-COVID-19. Journal of Futures Markets, 44(1), 27–56. https://doi.org/10.1002/fut.22463 DOI: https://doi.org/10.1002/fut.22463
Penone, C., Giampietri, E., & Trestini, S. (2021). Hedging effectiveness of commodity futures contracts to minimize price risk: Empirical evidence from the Italian field crop sector. Risks, 9(12). https://doi.org/10.3390/risks9120213 DOI: https://doi.org/10.3390/risks9120213
Pinto, S. O., & Sobreiro, V. A. (2022). Literature review: Anomaly detection approaches on digital business financial systems. Digital Business, 2(2). https://doi.org/10.1016/j.digbus.2022.100038 DOI: https://doi.org/10.1016/j.digbus.2022.100038
Protopapadakis, A., Stoll, H.R., 1983. Spot and futures prices and the law of one price. J. Financ. 38, 1431–1455. https://doi.org/10.1111/j.1540-6261.1983.tb03833.x DOI: https://doi.org/10.1111/j.1540-6261.1983.tb03833.x
Roll, R., Schwartz, E., & Subrahmanyam, A. (2007). Liquidity and the Law of One Price: The Case of the Futures–Cash Basis. The Journal of Finance, 62(5), 2201–2234. https://doi.org/10.1111/j.1540-6261.2007.01273.x DOI: https://doi.org/10.1111/j.1540-6261.2007.01273.x
Rout, B. S., Das, N. M., & Rao, K. C. (2021). Competence and efficacy of commodity futures market: Dissection of price discovery, volatility, and hedging. IIMB Management Review, 33(2), 146–155. https://doi.org/10.1016/j.iimb.2021.03.014 DOI: https://doi.org/10.1016/j.iimb.2021.03.014
Sadefo Kamdem, J., & Moumouni, Z. (2020a). Comparison of Some Static Hedging Models of Agricultural Commodities Price Uncertainty. Journal of Quantitative Economics, 18(3), 631–655. https://doi.org/10.1007/s40953-020-00206-y DOI: https://doi.org/10.1007/s40953-020-00206-y
Spencer, S., Bredin, D., & Conlon, T. (2018). Energy and agricultural commodities revealed through hedging characteristics: Evidence from developing and mature markets. Journal of Commodity Markets, 9, 1–20. https://doi.org/10.1016/j.jcomm.2017.12.001 DOI: https://doi.org/10.1016/j.jcomm.2017.12.001
Thenmozhi, M., & Maurya, S. (2020). Crude Oil Volatility Transmission Across Food Commodity Markets: A Multivariate BEKK-GARCH Approach. Journal of Emerging Market Finance, 20(2), 131–164. https://doi.org/10.1177/0972652720927623 DOI: https://doi.org/10.1177/0972652720927623
Tonin, J. M., Vieira, C. M. R., de Sousa Fragoso, R. M., & Martines Filho, J. G. (2020). Conditional correlation and volatility between spot and futures markets for soybean and corn. Agribusiness, 36(4), 707–724. https://doi.org/10.1002/agr.21664 DOI: https://doi.org/10.1002/agr.21664
Vollmer, T., & Von Cramon-Taubadel, S. (2020). The Optimal Wheat Futures Hedge at the Euronext Paris from a Farmer’s Perspective. In GJAE (Vol. 69, Issue 1). DOI: https://doi.org/10.30430/69.2020.1.49-63
Zhao, Y., & Ju, R. (2025). Investor Structure and Corn Futures Price Volatility in China: Evidence Based on the Agent-Based Model. Computational Economics, 65(2), 937–961. https://doi.org/10.1007/s10614-024-10613-5 DOI: https://doi.org/10.1007/s10614-024-10613-5
Živkov, D., Balaban, P., & Kuzman, B. (2021). How to combine precious metals with corn in a risk-minimizing two-asset portfolio? Agricultural Economics (Czech Republic), 67(2), 60–69. https://doi.org/10.17221/411/2020-AGRICECON DOI: https://doi.org/10.17221/411/2020-AGRICECON
Zuppiroli, M., & Revoredo-Giha, C. (2016). Hedging effectiveness of European wheat futures markets: An application of multivariate GARCH models. International Journal of Applied Management Science, 8(2), 132–148. https://doi.org/10.1504/IJAMS.2016.077006 DOI: https://doi.org/10.1504/IJAMS.2016.077006
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