Using Transfer entropy to measure the information flow in Sugar, Ethanol and Crude Oil price series

Authors

  • Joelma Mayara da Silva Universidade Federal Rural de Pernambuco
  • Mirelly Gonçalves Ferreira Universidade Federal Rural de Pernambuco
  • Íkaro Daniel de Carvalho Barreto Universidade Federal Rural de Pernambuco https://orcid.org/0000-0001-7253-806X
  • Tatijana Stosic Universidade Federal Rural de Pernambuco
  • Borko Stosic Universidade Federal Rural de Pernambuco

Keywords:

Transfer Entropy, Transfer Information, Agricultural market, Biofuel Market, Fuel Market.

Abstract

In the last years the ethanol production was grown up in the entire world, which also occurred in the Brazil, the second world production, the Brazilian product is classified was biofuel and derivate the sugarcane, it is also raw material of sugar. Furthermore, studies stand the influence in fuels from the foods prices, because the increase fuels prices increase the cost of transport and consequently the food production. On this, we study the direction of information flow between Brazilian ethanol and sugar prices and international crude oil prices using the Transfer entropy method. We find stronger information transfer from crude oil to sugar and crude oil to ethanol for return and volatility series while for original series the net information transfer was in opposite direction. There was no net information transfer between ethanol and sugar series, indicating that Brazilian biofuel and agricultural market are strongly related with international crude oil market.

Author Biographies

Joelma Mayara da Silva, Universidade Federal Rural de Pernambuco

Departamento de Estatística e Informática - Programa de Pós-Graduação em Biometria e Estatística Aplicada

Mirelly Gonçalves Ferreira, Universidade Federal Rural de Pernambuco

Departamento de Física

Íkaro Daniel de Carvalho Barreto, Universidade Federal Rural de Pernambuco

Departamento de Estatística e Informática - Programa de Pós-Graduação em Biometria e Estatística Aplicada

Tatijana Stosic, Universidade Federal Rural de Pernambuco

Departamento de Estatística e Informática - Programa de Pós-Graduação em Biometria e Estatística Aplicada

Borko Stosic, Universidade Federal Rural de Pernambuco

Departamento de Estatística e Informática - Programa de Pós-Graduação em Biometria e Estatística Aplicada

References

ABBOTT, P., Borot de Battisti, A. Recent global food price shocks: Causes, consequences and lessons for African governments and donors. Journal of African Economies, v. 20, n. suppl_1, p. i12-i62, 2011.

BAFFES, J. A framework for analyzing the interplay among food, fuels, and biofuels. Global Food Security, v. 2, n. 2, p. 110-116, 2013.

BEKIROS, S., Nguyen, D. K., Junior, L. S., & Uddin, G. S. Information diffusion, cluster formation and entropy-based network dynamics in equity and commodity markets. European Journal of Operational Research, v. 256, n. 3, p. 945-961, 2017.

BENTIVOGLIO, D., Finco, A., Bacchi, M. R. P., & Spedicato, G. . European biodiesel market and rapeseed oil: what impact on agricultural food prices. International Journal of Global Energy Issues, v. 37, n. 5-6, p. 220-235, 2014.

BORGE-HOLTHOEFER, J., Perra, N., Gonçalves, B., González-Bailón, S., Arenas, A., Moreno, Y., & Vespignani, A. The dynamics of information-driven coordination phenomena: A transfer entropy analysis. Science advances, v. 2, n. 4, p. e1501158, 2016.

BOSSOMAIER, T., Barnett, L., Steen, A., Harré, M., d'Alessandro, S., & Duncan, R. Information flow around stock market collapse. Accounting & Finance, v. 58, p. 45-58, 2018.

Center for Advanced Studies in Applied Economics/Luiz de Queiroz College of Agriculture/University of São Paulo – CEPEA/ESALQ/USP. Avaliable: < https://www.cepea.esalq.usp.br/br> (Accessed: 23 January 2019) .

CHEN, X., Tian, Y., Zhao, R.. Study of the cross-market effects of Brexit based on the improved symbolic transfer entropy GARCH model - An empirical analysis of stock–bond correlations. PloSone, v. 12, n. 8, p. e0183194, 2017.

CHIU, F. P., Hsu, C. S., Ho, A., & Chen, C. C. Modeling the price relationships between crude oil, energy crops and biofuels. Energy, v. 109, p. 845-857, 2016.

DIMPFL, T., Peter, F. J. Analyzing volatility transmission using group transfer entropy. Energy Economics, v. 75, p. 368-376, 2018.

DRABIK, D., De Gorter, H., Just, D. R., & Timilsina, G. R. . The economics of Brazil’s ethanol-sugar markets, mandates, and tax exemptions. American Journal of Agricultural Economics, v. 97, n. 5, p. 1433-1450, 2014.

FRATE, C. A., Brannstrom, C. Will Brazil's ethanol ambitions undermine its agrarian reform goals? A study of social perspectives using Q-method. Journal of Rural Studies, v. 38, p. 89-98, 2015.

HOCHMAN, G., Rajagopal, D., Timilsina, G., & Zilberman, D. Quantifying the causes of the global food commodity price crisis. Biomass and Bioenergy, v. 68, p. 106-114, 2014.

KALE, P., Acharya, J. V., Acharya, J., Subramanian, T., & Almekkawy, M. Normalized Transfer Entropy as a Tool to Identify Multisource Functional Epileptic Networks. In: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2018. p. 1218-1221.

KRISTOUFEK, L., Janda, K., Zilberman, D. Comovements of ethanol‐related prices: evidence from Brazil and the USA. Gcb Bioenergy, v. 8, n. 2, p. 346-356, 2016.

LIMA, C. R. A., de Melo, G. R., Stosic, B., Stosic, T. Cross-correlations between Brazilian biofuel and food market: Ethanol versus sugar. Physica A: Statistical Mechanics and its Applications, v. 513, p. 687-693, 2019.

Renewable Fuels Association – RFA (2019) Avaliable: <https://ethanolrfa.org/resources/industry/statistics/#1549569130196-da23898a-53d8> (Accessed 23 January 2019).

SCHREIBER, T. Measuring information transfer. Physical review letters, v. 85, n. 2, p. 461, 2000.

SERRA, T., Zilberman, D. Biofuel-related price transmission literature: A review. Energy Economics, v. 37, p. 141-151, 2013.

SERRA, T., Zilberman, D., Gil, J. Price volatility in ethanol markets. European review of agricultural economics, v. 38, n. 2, p. 259-280, 2010.

TENG, Y., Shang, P. Transfer entropy coefficient: Quantifying level of information flow between financial time series. Physica A: Statistical Mechanicsand its Applications, v. 469, p. 60-70, 2017.

TRUJILLO-BARRERA, A., Mallory, M., Garcia, P. Volatility spillovers in US crude oil, ethanol, and corn futures markets. Journal of Agricultural and Resource Economics, p. 247-262, 2012.

YAROVAYA, L., Lau, M. C. K. Stock market comovements around the Global Financial Crisis: Evidence from the UK, BRICS and MIST markets. Research in International Business and Finance, v. 37, p. 605-619, 2016.

Published

29-07-2019

How to Cite

da Silva, J. M., Gonçalves Ferreira, M., de Carvalho Barreto, Íkaro D., Stosic, T., & Stosic, B. (2019). Using Transfer entropy to measure the information flow in Sugar, Ethanol and Crude Oil price series. Sigmae, 8(2), 405–410. Retrieved from https://publicacoes.unifal-mg.edu.br/revistas/index.php/sigmae/article/view/997