Analysing White Maize Derivatives: Performance and Volatility in the SAFEX Market
Keywords:
Agricultural markets, GARCH models, Price risk management, South Africa, SAFEXAbstract
Objectives: to analyse risk management tools for market participants, specifically, white maize derivatives, focusing on performance and volatility in the SAFEX market. Prior work: The comprehension of the existing literature for the application of the GARCH model within the scope where the SAFEX has a role in the white maize serving as a commodity for food purposes and a base for a derivatives instrument. Approach: the research used a quantitative study design that involved using descriptive statistics, tests for stationarity, and an EGARCH model on futures prices from the months of 2009 to 2024. Implications: the market shows high persistence of volatility with strong negative leverage effects (bad news affects volatility more) and weak form efficiency with hedging efficiency of 81.96%. Results: this will be helpful for farmers and agri-businesses in ensuring revenue stability; for traders in pricing; and for policymakers in facilitating market-based risk management tools usage. Value: This study presents new evidence to support the high efficacy of the regional food product for which such asymmetrical welfare models are necessary and confirms the important place of SAFEX in the field of economics and the resilience of food security
References
Algieri, B. (2019). A Journey Through the History of Commodity Derivatives Markets and the Political Economy of (De)Regulation. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3301143
Antoniou, A., & Holmes, P. (1996). Futures market efficiency, the unbiasedness hypothesis and variance-bounds tests: the case of the FTSE 100 futures contract. Bulletin of Economic Research, 48(2), 115-128. https://doi.org/10.1111/j.1467-8586.1996.tb00820.x
Areal, F. J., Balcombe, K., & Rapsomanikis, G. (2013). Testing the law of one price in the international soybean market: a multiple threshold cointegration analysis. Journal of Agricultural Economics, 64(3), 703-713. https://doi.org/10.1111/1477-9552.12019
Auret, C. J., & Sayed, A. (2022). Modelling extreme price risk in agricultural futures: beyond traditional GARCH models. Journal of Risk and Financial Management, 15(3), 141. https://doi.org/10.3390/jrfm15030141
Aye, G. C., & Mungatana E. D. (2011). Technological innovation and efficiency in the Nigerian maize sector: Parametric stochastic and non-parametric distance function approaches (Vol 50). https://doi-org.nwulib.idm.oclc.org/10.1080/03031853.2011.617870
Aysan, A. F., Demir, E., & Mustafa, H. (2025). The impact of geopolitical risks on food security: evidence from the Russia-Ukraine crisis. Food Security, 17(1), 45-62. https://doi.org/10.1007/978-3-031-80574-5
Banda, H., Ng’ombe, J. N., & Tembo, G. (2017). Price discovery in the South African white maize futures market. African Journal of Agricultural and Resource Economics, 12(4). https://www.afare.org/journal
Beidas-Strom, S., & Pescatori, A. (2014). Oil price volatility and the role of speculation. IMF Working Paper: 14/218. https://www.imf.org/external/pubs/ft/wp/2014/wp14218.pdf
BFA. (2023). South African Agricultural Commodities Market Review. https://www.bfa.co.za
Bohl, M. T., Siklos, P. L., & Wellenreuther, C. (2019). Speculative activity and returns volatility of agricultural commodities: a heterogeneous agent approach. Journal of Commodity Markets, 15. https://doi.org/10.1016/j.jcomm.2018.12.002
Bollerslev. (1986). Generalised Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3). https://www.sciencedirect.com/science/article/pii/0304407686901631
Bown, A., Van Schalkwyk, H. D., & Van Zyl, J. (1999). The impact of the futures market on the cash price of maize in South Africa. Agrekon, 38(4). https://doi.org/10.1080/03031853.1999.9523480
Breger Bush, S. (2012). Derivatives and Development: A political economy of global finance, farming, and poverty. Palgrave Macmillan. https://north.on.worldcat.org/oclc/808422246
Brooks, C. (2019). Introductory Econometrics for Finance (4th ed.). Cambridge University Press. https://www.cambridge.org>highereducation>books>
Ceballos, F., Hernandez, M. A., Minot, N., and Robles, M. (2017). Grain price and volatility transmission from international to domestic markets in developing countries. World Development, 94, 305-320. https://doi.org/10.1016/j.worlddev.2017.01.015
Chabane, T., Jooste, A., & Meyer, F. (2020). The risk-return trade-off in the South African white maize futures market. South African Journal of Economic and Management Sciences, 23(1), 3491. https://doi.org/10.4102/sajems.v23i1.3491
Engle, R. F. (1982). Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4). https://www.jstor.org/stable/1912773
Engle, R. F. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate Generalised Autoregressive Conditional Heteroskedasticity Models. Journal of Business & Economic Statistics, 20(3). https://www.jstor.org/stable/1392121
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2). https://www.jstor.org/stable/2325486
Flavell, R. (2010). Swaps and Other Derivatives (2nd ed.). John Wiley & Sons. https://ebookcentral.proquest.com/lib/northwu-ebooks/detail.action?docID=826862
Geldenhuys, S. M. (2013). Timing a hedge decision: the development of a composite technical indicator for white maize. MCom dissertation, North-West University. http://hdl.handle.net/10394/11546
Geyser, M., & Cutts, M. (2007). SAFEX maize price volatility scrutinized. Agrekon, 46(3), 291–305. https://doi.org/10.1080/03031853.2007.9523773
Gilbert, C. L., & Morgan, C. W. (2010). Food price volatility. Philosophical Transactions of the Royal Society B. Biological Sciences, 365(1554). https://doi.org/10.1098/rstb.2010.0139
Global Risk Management. (2005). The U.S. White Maize Market: A Speciality Crop. https://www.global-riskmanagement.co
Gozgor, G. (2019). Effects of the agricultural commodity and the food price volatility on economic integration: an empirical assessment. https://doi.org/10.1007/s00181-017-1359-6
Gulati, A., & Saini, S. (2015). Taming Food Inflation in India. https://www.icrier.org
Hao, Y., Gai, Z., & Wu, H. (2024). How do geopolitical risks affect commodity prices? Evidence from the Russia-Ukraine conflict. Resources Policy, 88, 104460. https://doi.org/10.1016/j.resourpol.2023.104460
Harika, K., & Rani, S. U. (2025). Price Discovery, Hedging, and Regulatory Measures in Commodity Markets. https://www.researchgate.net/publication/393003084
Hedge, L. (2024). Risk-Adjusted Returns in Agricultural Futures. https://www.agrifinancejournal.com
Henrik Dahlqvis, C., & Wen, F. (2018). Cross-country information transmissions and the role of commodity markets: A multichannel Markov switching approach. https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0202251&type=printable
Hokkanen, M. (2020). Derivatives and the European VAT System: Derivatives in the Context of the Scope of Taxable Supplies. IBFD Publications USA, Incorporated. https://ebookcentral.proquest.com/lib/northwu-ebooks/detail.action?docID=6372021
Huang, Y., & Sayed, A. (2025). A comparative analysis of volatility in SAFEX agricultural futures. Journal of African Business, 26(1). https://onlinlibrary.wiley.com
Irwin, S. H., & Sanders, D. R. (2012). Financialization and structural change in commodity futures markets. Journal of Agricultural and Applied Economics, 44(3), 371-396. https://doi.org/10.1017/S1074070800000481
Jia, R. L., Wang, D. H., Tu, J. Q., & Li, S. P. (2016). Correlation between agricultural markets in dynamic perspective- Evidence from China and the US futures markets. Physica A: Statistical mechanics and its applications, 464, 83-92. https://doi.org/10.1016/j.physa.2016.07.048
JSE. (2001). JSE Annual Report 2001. https://www.jse.co.za
JSE. (2022). JSE Commodity Derivatives Market Statistics. https://www.jse.co.za
Kevin, S. (2024). Commodity and Financial Derivatives. https://books.google.co.za/books?hl=en&lr=&id=2SsFEQAAQBAJ&oi=fnd&pg=PP1&dq=commodity+derivatives+market&ots=V08e5PgJtI&sig=5gu9TKg0E8T6wnO8MLO4WnsGye8&redir_esc=y#v=onepage&q&f=false
Kirsten, J., & Geyser (2009). The Functioning Of The Agricultural Futures Market For Grains And Oilseeds In The Light Of Concerns Expressed By Grainsa. https://www.namc.co.za/wp-content/uploads/2017/09/Functioning-of-the-Agricultural-Futures-Market-in-South-Africa.pdf
Kirsten, J., & Sartorius, K. (2002). Linking agribusiness and small-scale farmers in developing countries: is there a new role for contract farming? Development Southern Africa, 19(4), 503-529. https://doi.org/10.1080/0376835022000019428
Kroner, K. F., & Sultan, J. (1993). Time-varying distributions and dynamic hedging with foreign currency futures. Journal of financial and quantitative analysis, 28(4), 535-551. https://www.jstor.org/stable/2331164
Küblböck, K., & Staritz, C. (2014). Regulation of commodity derivative markets: Critical assessment of reforms in the EU. Research papers in Economics. https://hdl.handle.net/10419/106403
Kumar M. R., Singh, K., & Sharma, R. (2024). Monetary policy shocks and agricultural commodity price volatility in emerging economies. Economic Modelling, 131, 106621. https://doi.org/10.1016/j.econmod.2024.106621
Langgo, W., & Faesal, A. (2015). The impact of changing consumption patterns on maize prices in Southern Africa. Journal of Development and Agricultural Economics, 7(9), 308-315. https://doi.org/10.5897/JDAE2015.0659
Lombard, A., & Warnock, V. (2018). The pass-through of oil price volatility to agricultural commodity prices in South Africa. South African Journal of Economics, 86(3), 367-385. https://doi.org/10.1111/saje.12192
Lundberg, A., & Abman, R. (2021). Does market access mitigate the impact of seasonality on child growth? Panel data evidence from northern Ethiopia. Journal of Development Studies, 57(2), 246-264. https://doi.org/10.1080/00220388.2020.1786062
Lutkepohl, H. (2005). New introduction to multiple time-series analysis. https://link.springer.com/book/10.1007/978-3-540-27752-1
Makanza, R., Zivanomoyo, J., & Chapwanya, M. (2018). Modelling and forecasting volatility of white maize futures prices in South Africa: A GARCH approach. African Journal of Agricultural and Resource Economics, 13(2), 134-147. https://www.afare.org/journal
Malkina, M. (2024). The stabilizing effect of investor sentiment during supply shocks in commodity markets. Finance Research Letters, 60, 104898. https://doi.org/10.1016/j.frl.2024.104898
Masunda, M. T., & Meyer, W. H. (2018). Price transmission between South African and global maize markets: The role of SAFEX in price discovery. Agrekon, 57(3), 232-248. https://doi.org/10.1080/03031853.2018.1528274
Misund, B., & Oglend, A. (2015). The dynamics of commodity price volatility. Energy Economics, 52(51), 51-52. https://doi.org/10.1016/j.eneco.2015.08.026
Moctar, C., Bationo, B. A., & Zidouemba, P. (2015). Transaction costs and price transmission on cereal markets: the case of Burkina Faso. https://www.ferdi.fr
Motengwe, C. T. (2013). Price Volatility Effectson Trading Returns in Agricultural Commodity Derivatives in South Africa. Masters Thesis, University of the Witwatersrand, Johannesburg. https://nwilib.idm.oclc.org/login?url=https://www.proquest.com/dissertations-theses/price-volatility-effects-on-trading-returns/docview/3153375698/se-2?accountid=12865
Muriuki, M. W., Olweny, T., & Mwangi, M. (2018). The impact of weather shocks on maize price volatility in Kenya. African Journal of Agricultural and Resource Economics, 13(4), 287-302. https://www.afare.org/journal
Muzinda, O., & Mashamba, T. (2020). The role of white maize futures in portfolio diversification in Southern Africa. Investment Analysis Journal, 49(3), 181-197. https://doi.org/10.1080/10293523.2020.1777851
Ndlovu, P., & Greyling, C. (2020). Price discovery and market efficiency in the South African white maize futures market: a threshold cointegration approach. Agrekon, 59(3), 301-317. https://doi.org/10.1080/03031853.2020.1783719
Nuss, E. T., & Tanumihardjo, S. A. (2010). Maize: a paramount staple crop in the context of global nutrition. Comprehensive Reviews in Food Science and Food Safety, 9(4), 417-436. https://doi.org/10.1111/j.1541-4337.2010.00117.x
Nweke, F. I. (2006). The White Maize Economy in Southern Africa: A Review. https://www.ifpri.org
Ott, H. (2014). Volatility in cereal prices: Intra- versus inter-annual volatility. Journal of Agricultural Economics, 65(3), 557–578. https://doi.org/10.1111/1477-9552.12073
Paientko, T., & Amakude, K. (2024). Geopolitical risk and food commodity prices: a GARCH-MIDAS approach. Empirical Economics, 66(4), 1789-1812. https://doi.org/10.1007/s00181-023-02515-6
Penone, C., Gardebroek, C., & Ihle, R. (2021). Risk management in European and North American grain markets: a comparative study. Agricultural Finance Review, 81(5), 673-691. https://doi.org/10.1108/AFR-06-2020-0085
Piesse, J., Thirtle, C., & Turk, J. (2015). The role of liquidity in price discovery: evidence from the South African white maize market. Journal of Agricultural Economics, 66(1), 203-223. https://doi.org/10.1111/1477-9552.12085
Pindyck, R. S. (2021). Commodity price volatility in a world of climate change. The Energy Journal, 42(4). https://doi.org/10.5547/01956574.42.4.rpin
Priolon, J. (2019). Financial Markets for Commodities (1st ed.). Wisely- ISTE. https://north.on.worldcat.org/oclc/1081304182
Rees, J., Williams, B., & Thompson, W. (2024). U.S. Corn: Identity-Preserved and Specialty Contracts. https://www.ers.usda.gov
SAFEX. (2022). SAFEX Market Rules and Regulations. https://www.jse.co.za/trade/derivatives-market/commodity-derivatives-market/safex
Santos, J. M. (2009). Grain Futures Markets: What Have They Learned? Proceedings of the NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting and Market Risk Management (pp. 1-10), St. Louis, MO, 2009 April. https://www.farmdoc.illinois.edu.nccc134/ conf_2009/pdf/confp06-09.pdf
Sayed, A., & Auret, C. J. (2019). The impact of climate variability on the efficiency of the South African white maize futures market. Climate Risk Management, 26, 100205. https://doi.org/10.1016/j.crm.2019.100205
Sayed, A., & Auret, C. J. (2020). Market efficiency and price discovery in the South African white maize futures market. South African Journal of Economics, 88(4), 499-522. https://doi.org/10.1111/saje.12247
Sayed, A., & Auret, C. J. (2021). Volatility transmission between South African grain futures markets: a multivariate GARCH analysis. Agricultural Finance Review, 81(3), 365-384. https://doi.org/10.1108/AFR-05-2020-0065
Sayed, A., & Auret, C. J. (2022). Speculative ratios and returns volatility in the South African white maize futures market. Cogent Economics & Finance, 11(1), 2160127. https://doi.org/10.1080/23322039.2022.2160127
Scheepers, C. F. (2005). An analysis of the efficiency of the South African Futures Exchange (SAFEX) with reference to the white maize contract. Masters Thesis, University of the Free State. https://www.ufs.ac.za
Schofield, N. C. (2007). Commodity Derivatives: Markets and Applications (2nd edition). John Wiley & Sons. https://north.on.worldcat.org/oclc/85897862
Statistics South Africa. (2017). Poverty trends in South Africa: An examination of absolute poverty between 2006 and 2015. https://www.statssa.gov.za/?p=10341
Strydom, P. D., & McCullough, K. (2013). The efficiency of the South African white maize futures market: a nonlinear approach. Agrekon, 52(4). https://doi.org/10.1080/03031853.2013.847957
Tang, K., & Xiong, W. (2021). The financialization of commodity markets. Annual Review of Financial Economics, 4, 447-466. https://doi.org/10.1146/annurev-financial-110613-034312
Torero, M. (2016). Enabling food price volatility and its effects: A focus on market functioning and financialization. https://www.ifpri.org
USDA WASDE. (2022). World Agricultural Supply and Demand Estimates Report. https://www.usda.gov/oce/commodity/wasde
Van der Merwe, J., & Kirsten, J. (2017). The impact of drought on wheat price volatility in South Africa. Agrekon, 56(3), 243-258. https://doi.org/10.1080/03031853.2017.1360454
Van der Vyver, A. (2023). Determining whether the number of Cape wheat producers trading directly on SAFEX is declining and the reasons for this: Has producer hedging entered a new era? Grains SA. https://www.grainsa.co.za/upload/report_files/Determining-whether-the-no-of-Cape-wheat-producers-trading-directly-on-Safex-is-declining.pdf
Watugala, S. W. (2015). Volatility spillovers between energy and agricultural commodity markets. Ph.D. Thesis, University of Illinois at Urbana-Champaign. https://repub.eur.nl>pub
Weiermans, H., & Mokatsanyane, D. (2025). Weather derivatives and maize yield risk in the South African agricultural market. https://www.DOI:10.48077/scihor4.2025.58
Were, M., Wainaina, J., & Kiprop, S. (2020). Development of the Derivatives Market at the Nairobi Securities Exchange. https://www.cbd.int
Zhang, Q., & Li, Y. (2021). The impact of Chinese demand on global soybean price volatility. China Agricultural Economic Review, 13(2), 427-446. https://doi.org/10.1108/CAER-12-2019-0232
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