Risk analysis model and agricultural derivative market use: a conceptual review
Main Article Content
Abstract
This research aims to build conceptual guidelines regarding price risk management through the agricultural derivatives market. Specifically, to identify the common price risk management methods and strategies employed, the risk analysis models of derivative markets, and the barriers to agricultural risk management. This is an integrative review, the search for literature on the models of risk management analysis of agricultural derivatives started by listing the largest possible number of keywords on the topic, in the Scopus and Web of Science. Forty-five publications were found meeting the pre-established criteria that served as the basis for this research. Based on the literature review, we list the main information on the subject and we also propose a theoretical model for analyzing the market risks of agricultural derivatives. Still, it was possible to notice that among the methodologies for measuring market risk, Value at Risk (VaR) stands out. We exemplify and demonstrate the existence of several statistical analyzes and mathematical models, as well as software available for the management of price risks. It is concluded that strategies with the futures and options market, even though they are the most efficient for risk management, lack incentives to become practical.
Downloads
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
1. Proposal of Policy for Free Access Periodics
Authors whom publish in this magazine should agree to the following terms:
a. Authors should keep the copyrights and grant to the magazine the right of the first publication, with the work simultaneously permitted under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 that allows the sharing of the work with recognition of the authorship of the work and initial publication in this magazine.
b. Authors should have authorization for assuming additional contracts separately, for non-exclusive distribution of the version of the work published in this magazine (e.g.: to publish in an institutional repository or as book chapter), with recognition of authorship and initial publication in this magazine.
c. Authors should have permission and should be stimulated to publish and to distribute its work online (e.g.: in institutional repositories or its personal page) to any point before or during the publishing process, since this can generate productive alterations, as well as increasing the impact and the citation of the published work (See The Effect of Free Access).
Proposal of Policy for Periodic that offer Postponed Free Access
Authors whom publish in this magazine should agree to the following terms:
a. Authors should keep the copyrights and grant to the magazine the right of the first publication, with the work simultaneously permitted under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 [SPECIFY TIME HERE] after the publication, allowing the sharing of the work with recognition of the authorship of the work and initial publication in this magazine.
b. Authors should have authorization for assuming additional contracts separately, for non-exclusive distribution of the version of the work published in this magazine (e.g.: to publish in institutional repository or as book chapter), with recognition of authorship and initial publication in this magazine.
c. Authors should have permission and should be stimulated to publish and to distribute its work online (e.g.: in institutional repositories or its personal page) to any point before or during the publishing process, since this can generate productive alterations, as well as increasing the impact and the citation of the published work (See The Effect of Free Access).
d. They allow some kind of open dissemination. Authors can disseminate their articles in open access, but with specific conditions imposed by the editor that are related to:
Version of the article that can be deposited in the repository:
Pre-print: before being reviewed by pairs.
Post-print: once reviewed by pairs, which can be:
The version of the author that has been accepted for publication.
The editor's version, that is, the article published in the magazine.
At which point the article can be made accessible in an open manner: before it is published in the magazine, immediately afterwards or if a period of seizure is required, which can range from six months to several years.
Where to leave open: on the author's personal web page, only departmental websites, the repository of the institution, the file of the research funding agency, among others.
References
Ali, M., Man, N., & Muharam, F. M. (2019). Perceptions of Malaysian farmers regarding their knowledge in agricultural risk management. J. Agric. Plant Sci, 29(4). http://www.thejaps.org.pk/docs/v-29-04/34.pdf
Amin, F. A. M., Yahya, S. F., Ibrahim, S. A. S., & Kamari, M. S. M. (2018). Portfolio risk measurement based on value at risk (VaR). In AIP Conference Proceedings, 1974(1), 020012. AIP Publishing LLC.
Antón, J., Cattaneo, A., Kimura, S., & Lankoski, J. (2013). Agricultural risk management policies under climate uncertainty. Global environmental change, 23(6), 1726-1736. https://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/1044224
Assa, H. (2016). Financial engineering in pricing agricultural derivatives based on demand and volatility. Agricultural Finance Review. https://doi.org/10.1108/AFR-11-2015-0053
Barnes, A. P., Islam, M. M., & Toma, L. (2013). Heterogeneity in climate change risk perception amongst dairy farmers: A latent class clustering analysis. Applied Geography, 41, 105-115. https://doi.org/10.1016/j.apgeog.2013.03.011
Calegari, I. P., Baigorri, M. C., & Freire, F. D. S. (2012). Agricultural derivatives as a price risk management tool [Portuguese]. Custos e @gronegócio online, 8(1). http://www.custoseagronegocioonline.com.br/especialv8/Derivativos.pdf
Chen, S., Härdle, W. K., & Cabrera, B. L. (2019). Regularization approach for network modeling of German power derivative market. Energy Economics, 83, 180-196.
Clapp, J., & Helleiner, E. (2012). Troubled futures? The global food crisis and the politics of agricultural derivatives regulation. Review of International Political Economy, 19(2), 181-207. https://doi.org/10.1080/09692290.2010.514528
Crane, T. A., Roncoli, C., Paz, J., Breuer, N., Broad, K., Ingram, K. T., & Hoogenboom, G. (2010). Forecast skill and farmers’ skills: Seasonal climate forecasts and agricultural risk management in the southeastern United States. Weather, Climate and Society, 2(1), 44-59. https://doi.org/10.1175/2009WCAS1006.1
Cresti, B. (2005). US domestic barter: An empirical investigation. Applied Economics, 37(17), 1953-1966. https://doi.org/10.1080/00036840500193559
Dase, R. K., & Pawar, D. D. (2010). Application of Artificial Neural Network for stock market predictions: A review of literature. International Journal of Machine Intelligence, 2(2), 14-17.
Duong, T. T., Brewer, T., Luck, J., & Zander, K. (2019). A global review of farmers’ perceptions of agricultural risks and risk management strategies. Agriculture, 9(1), 10. https://doi.org/10.3390/agriculture9010010
Fraisse, C. W., Breuer, N. E., Zierden, D., Bellow, J. G., Paz, J., Cabrera, V. E., & Jones, J. W. (2006). AgClimate: A climate forecast information system for agricultural risk management in the southeastern USA. Computers and electronics in agriculture, 53(1), 13-27. https://doi.org/10.1016/j.compag.2006.03.002
Finger, M. I. F., & Waquil, P. D. (2013). Perception and risk management measures by irrigated rice producers on the Western Frontier of Rio Grande do Sul [Portuguese]. Ciência Rural, 43 (5), 930-936. https://doi.org/10.1590/S0103-84782013005000033
Ghorbel, A., & Trabelsi, A. (2009). Measure of financial risk using conditional extreme value copulas with EVT margins. Journal of Risk, 11(4), 51.
Gudendorf, G., & Segers, J. (2010). Copulas of extreme values. In Copula Theory and its applications. Springer, Berlin, Heidelberg, 127-145.
Guilleminot, B., Ohana, J., & Ohana, S. (2014) The interaction of speculators and index investors in agricultural derivatives markets. Agricultural economics, 45(6), 767-792. https://doi.org/10.1111/agec.12122
Gródek-Szostak, Z., Malik, G., Kajrunajtys, D., Szeląg-Sikora, A., Sikora, J., Kuboń, M., & Kapusta-Duch, J. (2019). Modeling the dependency between extreme prices of selected agricultural products on the derivatives market using the linkage function. Sustainability, 11(15), 4144.
Hart, C. E., Lence, S. H., Hayes, D. J., & Jin, N. (2016). Price mean reversion, seasonality, and options markets. American Journal of Agricultural Economics, 98(3), 707-725. https://doi.org/10.1093/ajae/aav045
Hazell, P. B., & Hess, U. (2010). Drought insurance for agricultural development and food security in dryland areas. Food Security, 2(4), 395-405. https://doi.org/10.1007/s12571-010-0087y
He, L. Y., Yang, S., Xie, W. S., & Han, Z. H. (2014). Contemporaneous and asymmetric properties in the price-volume relationships in China's agricultural futures markets. Emerging Markets Finance and Trade, 50(sup1), 148-166. https://doi.org/10.2753/REE1540-496X5001S110
Hosseini, Y. S., Zibaei, M., & Allen, D. E. (2010). The Initial Specification of Viable Futures Contracts: The Use of a New Computational Method of Value at Risk in Iranian Agricultural Commodities Market.
Huh, S. W., Lin, H., & Mello, A. S. (2015). Options market makers׳ hedging and informed trading: Theory and evidence. Journal of Financial Markets, 23, 26-58. https://doi.org/10.1016/j.finmar.2015.01.001
Jackson, E., Quaddus, M., Islam, N., & Stanton, J. (2009). Sociological factors affecting agricultural price risk management in Australia. Rural sociology, 74(4), 546-572. https://doi.org/10.1111/j.1549-0831.2009.tb00704.x
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
Jiang, H., Todorova, N., Roca, E., & Su, J. J. (2017). Dynamics of volatility transmission between the US and the Chinese agricultural futures markets. Applied Economics, 49(34), 3435-3452. https://doi.org/10.1080/00036846.2016.1262517
Klopper, E., Vogel, C. H., & Landman, W. A. (2006). Seasonal climate forecasts–potential agricultural-risk management tools? Climatic Change, 76(1-2), 73-90. DOI: https://doi.org/10.1007/s10584-005-9019-9
Kumar, R. (2020). Predicting Wheat Futures Prices in India. Asia-Pacific Financial Markets, 1-20.
Linsmeier, T. J. E., & Pearson, N. D. (2000). Value at risk. Financial Analysts Journal, 56(2), 47–67.
Lorant, A., & Farkas, M. F. (2015). Risk management in the agricultural sector with special attention to insurance. Polish journal of management studies, 11(2), 71-82.
Marston, J. M. (2011). Archaeological markers of agricultural risk management. Journal of Anthropological Archaeology, 30(2), 190-205. https://doi.org/10.1016/j.jaa.2011.01.002
Meinke, H., Sivakumar, M. V. K., Motha, R. P., & Nelson, R. (2007). Preface: Climate predictions for better agricultural risk management. Australian Journal of Agricultural Research, 58(10), 935-938. https://doi.org/10.1071/ARv58n10_PR
Miao, X., Yu, B., Xi, B., & Tang, Y. H. (2011). Risk and regulation of emerging price volatility of non-staple agricultural commodity in China. African Journal of Agricultural Research, 6(5), 1251-1256.
Morgan, W., Cotter, J., & Dowd, K. (2012). Extreme measures of agricultural financial risk. Journal of Agricultural Economics, 63(1), 65-82. https://doi.org/10.1111/j.1477-9552.2011.00322.x
Myers, R. J., Sexton, R. J., & Tomek, W. G. (2010). A century of research on agricultural markets. American Journal of Agricultural Economics, 92(2), 376-403. https://doi.org/10.1093/ajae/aaq014
Mühlen, A. S. R. W., Cezar, I. M., & Costa, F. P. (2013). Price risk in soy commercialization: use of derivatives by rural producers in Maracaju-MS, Brazil [Portuguese]. Ciencia Rural, 43 (5), 937-943. https://doi.org/10.1590/S0103-84782013005000031
Paris, Q. (2018). Positive Mathematical Programming and Risk Analysis. Bio-based and Applied Economics, 7(3), 191-215. https://doi.org/10.22004 / ag.econ.301892
Porth, L., & Assa, H. (2015). A financial engineering approach to pricing agricultural insurances. Agricultural Finance Review, 75(1), 63-76. https://www.emerald.com/insight/content/doi/10.1108/AFR-12-2014-0041/full/html
Ryu, D., & Yang, H. (2020). Noise traders, mispricing, and price adjustments in derivatives markets. The European Journal of Finance, 26(6), 480-499. https://doi.org/10.1080/1351847X.2019.1692887
Severini, S., Biagini, L., & Finger, R. (2019). Modeling agricultural risk management policies–The implementation of the Income Stabilization Tool in Italy. Journal of Policy Modeling, 41(1), 140-155. https://doi.org/10.1016/j.jpolmod.2018.03.003
Souza, I. A. (2017). Gestão de risco de mercado: mensuração do Value-at-Risk (VaR) comparando a exigência de capital em diferentes abordagens.
Thilmany, D., & Blank, S. C. (1996). FLCs: An analysis of labor management transfers among California agricultural producers. Agribusiness: An International Journal, 12(1), 37-49.
Triantafyllou, A., Dotsis, G., & Sarris, A. (2020). Assessing the vulnerability to price spikes in agricultural commodity markets. Journal of Agricultural Economics, 71(3), 631-651. https://doi.org/10.1111/1477-9552.12377
Toledo Filho, J. R., Cardoso, A. F., & Santos, C. C. (2009). Custo e benefícios dos derivativos agropecuários: utilização de butterfly de put no incremento do resultado em contratos de café. Custos e @gronegócio online, 3(5), 36-54. http://www.custoseagronegocioonline.com.br/numero3v5/derivativos.pdf
Torraco, R. J. (2016). Writing integrative literature reviews: Using the past and present to explore the future. Human Resource Development Review, 15(4), 404-428. https://doi.org/10.1177/1534484316671606
Vedenov, D. V., & Barnett, B. J. (2004). Efficiency of weather derivatives as primary crop insurance instruments. Journal of Agricultural and Resource Economics, 387-403. https:/doi.org/10.22004/ag.econ.30916
Vogel, C., & O’brien, K. (2006). Who can eat information? Examining the effectiveness of seasonal climate forecasts and regional climate-risk management strategies. Climate Research, 33(1), 111-122. https:/doi.org/10.3354/CR033111
Xi, W., Hayes, D., & Lence, S. H. (2019). Variance risk premia for agricultural commodities. Agricultural Finance Review. https://doi.org/10.1108/AFR-07-2018-0056
Xu, Y., Pan, F., Wang, C., & Li, J. (2019). Dynamic Price Discovery Process of Chinese Agricultural Futures Markets: An Empirical Study Based on the Rolling Window Approach. Journal of Agricultural and Applied Economics, 51(4), 664-681. https://doi.org/10.1017/aae.2019.23
Wauters, E., Van Winsen, F., De Mey, Y., & Lauwers, L. (2014). Risk perception, attitudes towards risk and risk management: evidence and implications. Agricultural Economics, 60(9), 389-405. http://hdl.handle.net/1854/LU-5757619
Zhang, H., & Watada, J. (2019). An analysis of the arbitrage efficiency of the Chinese SSE 50ETF options market. International Review of Economics & Finance, 59, 474-489. https://doi.org/10.1016/j.iref.2018.10.011