Revista de Economia e Sociologia Rural
https://revistasober.org/article/doi/10.1590/1806-9479.2021.250643
Revista de Economia e Sociologia Rural
ORIGINAL ARTICLE

Impacts of El Niño southern oscillation on hedge strategies for Brazilian corn and soybean futures contracts1

El Niño Oscilação Sul, razão de preços soja-milho e estratégia de hedge

George Lucas Máximo Ferreira; Julyerme Matheus Tonin; Alexandre Florindo Alves

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Abstract

Abstract: Climate influences the variations in soybean and corn prices; thus, we assessed the relationship between the El Niño Southern Oscillation (ENSO) with soybean-to-corn price ratio to determine potential impacts on price risk management. The commercial areas of Passo Fundo (RS), Cascavel (PR), Maringá (PR), Uberlândia (Triângulo Mineiro), and Sorriso (MT) covered in the study were chosen according to the MAPA edaphoclimatic classification. To estimate the effectiveness and optimal hedge ratio, the static and generalized model by Myers and Thompson (1989), adapted by Lien and Tse (2000), was used to include the cointegration approach in the analysis. The innovation of this study is the inclusion of the climate variable ENSO in this hedging approach. The findings showed that ENSO, especially La Niña, affects soybean-to-corn price ratio and hedge strategies. These results highlight the need to expand the use of futures contracts to reduce the price risk during the occurrence of ENSO events.

Keywords

soybean, corn, effectiveness, optimal hedge ratio, cross hedge

Resumo

Resumo:: O clima influencia as variações nos preços da soja e do milho. Assim, avaliamos a relação entre a variável climática Oscilação Sul do El Niño (ENSO) com a razão de preços entre soja e milho para identificar os possíveis impactos no gerenciamento de riscos de preços. As regiões de comercialização de Passo Fundo (RS), Cascavel (PR), Maringá (PR), Uberlândia (Triângulo Mineiro) e Sorriso (MT) abordadas no estudo foram escolhidas de acordo com a classificação edafoclimática do MAPA. Para a estimação da efetividade e razão ótima de hedge, foi utilizado o modelo estático e generalizado de Myers e Thompson (1989) adaptado por Lien e Tse (2000) para incluir na análise a abordagem de cointegração. A inovação desse estudo é a inclusão da variável climática ENSO nessa abordagem de hedge. Os achados da pesquisa demonstram que a ocorrência do ENSO, especialmente a La Nina, exerce influência na razão de preços soja e milho e nas estratégias de hedge. Tal fato destaca a necessidade de ampliar a utilização de contratos futuros para reduzir o risco de preços principalmente na ocorrência de eventos climáticos extremos.
 

Palavras-chave

soja, milho, efetividade, razão ótima de hedge, cross hedge

Referências

Abdolrahimi, M. (2016). The effect of El Niño Southern Oscillation (ENSO) on world cereal production (Master’s thesis). University of Sydney, Sydney. Retrieved in 2021, April 3, from https://ses.library.usyd.edu.au/bitstream/handle/2123/15498/Abdolrahimi-ma-thesis.pdf.

Adams, R. M., Chen, C.-C., McCarl, B. A., & Weiher, R. F. (1999). The economic consequences of ENSO events for agriculture. Climate Research, 13(3), 165-172. http://dx.doi.org/10.3354/cr013165.

Anderson, R. W., & Danthine, J.-P. (1983). The time pattern of hedging and the volatility of futures prices. The Review of Economic Studies, 50(2), 249-266. http://dx.doi.org/10.2307/2297415.

Banco Central do Brasil – BCB. (2019). BCB [10813 – Taxa de Câmbio-Livre-Dólar americano (compra).]. Sistema Gerenciador de Séries Temporais. Retrieved in 2021, April 3, from https://www.bcb.gov.br.

Baum, C. (2010). Stata Tip 88: efficiently evaluating elasticities with the margins command. The Journal of Finance, 10(2), 309-312. http://dx.doi.org/10.1177/1536867X1001000212.

Berlato, M. A., & Fontana, D. C. (2003). El Niño e La Niña: impactos no clima, na vegetação e na agricultura do Rio Grande do Sul: aplicações de previsões climáticas na agricultura. Editora da UFRGS.

Brasil. (2012). Instrução normativa 02, 7. Diário Oficial [da] República Federativa do Brasil, Brasília. Retrieved in 2021, April 3, from http://sistemasweb.agricultura.gov.br/conjurnormas.

Castelino, M. (1992). Hedge effectiveness: basis risk and minimum-variance hedging - ProQuest. Retrieved in 2021, April 3, from http://www.master-eddee.fr/wp-content/uploads/2011/12/Castelino.pdf

Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427-431. http://dx.doi.org/10.2307/2286348

Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057-1072. http://dx.doi.org/10.2307/1912517

Deng, X., Huang, J., Qiao, F., Naylor, R. L., Falcon, W. P., Burke, M., Rozelle, M. & Battisti, D. (2010). Impacts of El Niño-Southern Oscillation events on China’s rice production. Journal of Geographical Sciences, 20(1), 3-16. http://dx.doi.org/10.1007/s11442-010-0003-6.

Ederington, L. (1979). The hedging performance of the new futures markets. The Journal of Finance, 34(1), 1057-1072. http://dx.doi.org/10.1111/j.1540-6261.1979.tb02077.x

Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4), 813-836. http://dx.doi.org/10.2307/2171846

Grimm, A. M., Barros, V. R., & Doyle, M. E. (2000). Climate variability in southern South America associated with El Niño and La Niña events. Journal of Climate, 13(1), 35-58. http://dx.doi.org/10.1175/1520-0442(2000)013<0035:CVISSA>2.0.CO;2

Grimm, A. M., Ferraz, S. E. T., & Gomes, J. (1998). Precipitation anomalies in southern Brazil associated with El Niño and La Niña Events. Journal of Climate, 11(11), 2863-2880. http://dx.doi.org/10.1175/1520-0442(1998)011<2863:PAISBA>2.0.CO;2

Jiang, J., & Fortenbery, T. R. (2019). El Niño and La Niña induced volatility spillover effects in the US soybean and water equity markets. Applied Economics, 51(11), 1133-1150. http://dx.doi.org/10.1080/00036846.2018.1524980

Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12, 231-254. http://dx.doi.org/10.1016/0165-1889(88)90041-3.

Johnson, L. (1960). The theory of hedging and speculation in commodity futures. The Review of Economic Studies, 27(3), 139-151. http://dx.doi.org/10.2307/2296076

Keppenne, C. L. (1995). An ENSO signal in soybean futures prices. Journal of Climate, 8(6), 1685-1689. http://dx.doi.org/10.1175/1520-0442(1995)008<1685:AESISF>2.0.CO;2

KNMI. (2020). KNMI Climate Explorer, select a time series daily climate index. Retrieved in 2021, April 3, from https://climexp.knmi.nl/start.cgi

Lence, S. H. (1995). The economic value of minimum‐variance hedges. American Journal of Agricultural Economics, 77(2), 353-364. http://dx.doi.org/10.2307/1243545

Lien, D.-H. D. (1996). The effect of the cointegration relationship on futures hedging: a note. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 16(7), 773-780. http://dx.doi.org/10.1002/(SICI)1096-9934(199610)16:7<773::AID-FUT3>3.0.CO;2-L

Lien, D.-H. D., & Tse, Y. K. (2002). Some recent developments in futures hedging. Journal of Economic Surveys, 16(3), 357-396. http://dx.doi.org/10.1111/1467-6419.00172

Lin, W., & Riley, P. A. (1998). Special article rethinking the soybeans-to-corn price ratio: is it still a good indicator for planting decisions? Economic Research Service, US Department of Agriculture: Feed Situation and Outlook Yearbook. Retrieved in 2021, April 3, from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.199.5228&rep=rep1&type=pdf

Ma, C. K., Mercer, J. M., & Walker, M. A. (1992). Rolling over futures contracts: a note. Journal of Futures Markets, 12(2), 203-217. http://dx.doi.org/10.1002/fut.3990120208

Maia, F. N. C. S., & Aguiar, D. R. D. (2010). Hedging strategies with Chicago Board of Trade soybeans futures contracts. Gestão & Produção, 17(3), 617-626. http://dx.doi.org/10.1590/S0104-530X2010000300014

Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91. http://dx.doi.org/10.2307/2975974

Martins, A. G., & Aguiar, D. R. (2004). Efetividade do hedge de soja em grão brasileira contratos futuros de diferentes vencimentos na chicago board of trade. Revista de Economia e Agronegócio, 2(4), 449-472. http://dx.doi.org/10.25070/rea.v2i4.43

Minaki, C., & Montanher, O. C. (2019). Influência do El Niño-Oscilação Sul na precipitação em Maringá-PR, no período de 1980 a 2016. Caminhos de Geografia, 20(69), 266-281. https://doi.org/10.14393/RCG206941220

Myers, R. J., & Thompson, S. R. (1989). Generalized Optimal Hedge Ratio Estimation. American Journal of Agricultural Economics, 71(4), 858-868. http://dx.doi.org/10.2307/1242663

Oliveira, A. F. (2000) Modelos para estimar razão ótima de hedge de variância mínima: aplicação para contratos futuros agropecuários (Dissertação de mestrado). Escola Superior de Agricultura “Luiz de Queiroz”, Universidade de São Paulo, Piracicaba. https://doi.org/10.11606/D.11.2018.tde-20181127-161811

Peri, M. (2017). Climate variability and the volatility of global maize and soybean prices. Food Security, 9(4), 673-683. http://dx.doi.org/10.1007/s12571-017-0702-2

Podestá, G., Letson, D., Messina, C., Royce, F., Ferreyra, R. A., Jones, J., Hansen, J., Llovet, I., Grondona, M., & O’Brien, J. J. (2002). Use of ENSO-related climate information in agricultural decision making in Argentina: a pilot experience. Agricultural Systems, 74(3), 371-392. http://dx.doi.org/10.1016/S0308-521X(02)00046-X

Sanches, A. L. R., Zanin, V., Alves, L. R. A., & Jacomini, R. L. (2016). Formação de preços no mercado de milho da Região de Chapecó/SC – Brasil. Revista Espacios, 37(18). Retrieved in 2021, April 3, from http://www.revistaespacios.com/a16v37n18/16371820.html

Shah, A. (1997). Black, Merton and Scholes: their work and its consequences. Economic and Political Weekly, 32(52), 3337-3342.

Stein, J. L. (1961). The simultaneous determination of spot and futures prices. The American Economic Review, 51(5), 1012-1025. http://dx.doi.org/10.2307/1885530

Tabony, R. (1983). The estimation of missing climatological data. Journal of Climatology, 3(3), 297-314. http://dx.doi.org/10.1002/joc.3370030308

Teracines, E. B. (2000). Impactos econômicos do El Niño 97/98 na produção agrícola brasileira. In Anais do 4º Simpósio Brasileiro de Climatologia Geográfica: Clima e Ambiente (Sustentabilidade, Riscos, Impactos). Retrieved in 2021, April 3, from http://www.cbmet.org.br

Tonin, J. M. (2019). Transbordamento de risco de preço entre os mercados de milho e soja no Brasil (Doctoral dissertation). Escola Superior de Agronomia “Luiz de Queiroz”, Universidade de São Paulo. http://dx.doi.org/10.11606/T.11.2019.tde-29032019-112429

Trenberth, K. E. (1997). Short-Term climate variations: recent accomplishments and issues for future progress. Bulletin of the American Meteorological Society, 78(6), 1081-1096. http://dx.doi.org/10.1175/1520-0477(1997)078<1081:STCVRA>2.0.CO;2

Ubilava, D. (2008). Analysis of the soybean-to-corn price ratio and its impact on farmers’ planting decision-making in Indiana. In 2008 Annual Meetingi.https://doi.org/10.22004/ag.econ.6783

Ubilava, D. (2017). The ENSO effect and asymmetries in wheat price dynamics. World Development, 96, 490-502. http://dx.doi.org/10.1016/j.worlddev.2017.03.031

Williams, R. (2012). Using the margins command to estimate and interpret adjusted predictions and marginal effects. The Stata Journal, 12(2), 308-331. http://dx.doi.org/10.1177/1536867X1201200209

Working, H. (1953). Futures trading and hedging. The American Economic Review, 43(3), 314-343. http://dx.doi.org/10.2307/1811346

Zulauf, C. (2013). Corn price ratio since 1975. Illinois: Farmdoc Daily, Departament of Agricultural and Consumer Economics, University of Illinois. Retrieved in 2021, April 3, from http://farmdocdaily.illinois.edu/2013/09/soybean-corn-price-ratios-since-1975
 


Submetido em:
03/04/2021

Aceito em:
05/07/2021

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