IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v523y2019icp933-941.html
   My bibliography  Save this article

Complexity analysis of Brazilian agriculture and energy market

Author

Listed:
  • Albarracín E., Eva Susana
  • Gamboa, Juan C. Rodríguez
  • Marques, Elaine C.M.
  • Stosic, Tatijana

Abstract

We investigate regularity and asynchrony in Brazilian energy (ethanol) and agriculture (sugar) market with focus on 2008 global economic crisis, using multiscale entropy method. We applied this method on sugar and ethanol return series for different temporal scales and in sliding windows to analyze temporal evolution of regularity of price dynamics. The results show that for both ethanol and sugar return series the entropy values increase after 2008 and 2012, indicating the increase of market efficiency in post-crisis periods. During the crisis periods sugar and ethanol return series present some deviations from the expected decreasing behavior for higher timescales, which is more evident for the ethanol. Overall, higher entropy values are found for ethanol series indicating less regularity and higher market efficiency in energy market.

Suggested Citation

  • Albarracín E., Eva Susana & Gamboa, Juan C. Rodríguez & Marques, Elaine C.M. & Stosic, Tatijana, 2019. "Complexity analysis of Brazilian agriculture and energy market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 933-941.
    • Handle: RePEc:eee:phsmap:v:523:y:2019:i:c:p:933-941
    DOI: 10.1016/j.physa.2019.04.134
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119304698
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.04.134?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Teresa Serra & David Zilberman & José Gil, 2011. "Price volatility in ethanol markets," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 38(2), pages 259-280, June.
    2. Nobi, Ashadun & Maeng, Seong Eun & Ha, Gyeong Gyun & Lee, Jae Woo, 2014. "Effects of global financial crisis on network structure in a local stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 135-143.
    3. Alvarez-Ramirez, Jose & Rodriguez, Eduardo & Alvarez, Jesus, 2012. "A multiscale entropy approach for market efficiency," International Review of Financial Analysis, Elsevier, vol. 21(C), pages 64-69.
    4. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & de Oliveira, Wilson & Stosic, Tatijana, 2016. "Foreign exchange rate entropy evolution during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 233-239.
    5. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    6. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Correlations between biofuels and related commodities before and during the food crisis: A taxonomy perspective," Energy Economics, Elsevier, vol. 34(5), pages 1380-1391.
    7. Dooley, Michael & Hutchison, Michael, 2009. "Transmission of the U.S. subprime crisis to emerging markets: Evidence on the decoupling-recoupling hypothesis," Journal of International Money and Finance, Elsevier, vol. 28(8), pages 1331-1349, December.
    8. Risso, Wiston Adrián, 2008. "The informational efficiency and the financial crashes," Research in International Business and Finance, Elsevier, vol. 22(3), pages 396-408, September.
    9. Deborah Bentivoglio & Adele Finco & Mirian Rumenos Piedade Bacchi, 2016. "Interdependencies between Biofuel, Fuel and Food Prices: The Case of the Brazilian Ethanol Market," Energies, MDPI, vol. 9(6), pages 1-16, June.
    10. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    11. Fengzhong Wang & Kazuko Yamasaki & Shlomo Havlin & H. Eugene Stanley, 2005. "Scaling and memory of intraday volatility return intervals in stock market," Papers physics/0511101, arXiv.org.
    12. Zunino, Luciano & Tabak, Benjamin M. & Serinaldi, Francesco & Zanin, Massimiliano & Pérez, Darío G. & Rosso, Osvaldo A., 2011. "Commodity predictability analysis with a permutation information theory approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 876-890.
    13. Kelvin Balcombe & George Rapsomanikis, 2008. "Bayesian Estimation and Selection of Nonlinear Vector Error Correction Models: The Case of the Sugar-Ethanol-Oil Nexus in Brazil," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(3), pages 658-668.
    14. B. M. Tabak & T. R. Serra & D. O. Cajueiro, 2010. "Topological properties of commodities networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 74(2), pages 243-249, March.
    15. Moreira, José Roberto & Romeiro, Viviane & Fuss, Sabine & Kraxner, Florian & Pacca, Sérgio A., 2016. "BECCS potential in Brazil: Achieving negative emissions in ethanol and electricity production based on sugar cane bagasse and other residues," Applied Energy, Elsevier, vol. 179(C), pages 55-63.
    16. Liu, Li-Zhi & Qian, Xi-Yuan & Lu, Heng-Yao, 2010. "Cross-sample entropy of foreign exchange time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4785-4792.
    17. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & Stosic, Tatijana, 2016. "Correlations of multiscale entropy in the FX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 52-61.
    18. Khatiwada, Dilip & Leduc, Sylvain & Silveira, Semida & McCallum, Ian, 2016. "Optimizing ethanol and bioelectricity production in sugarcane biorefineries in Brazil," Renewable Energy, Elsevier, vol. 85(C), pages 371-386.
    19. Martina, Esteban & Rodriguez, Eduardo & Escarela-Perez, Rafael & Alvarez-Ramirez, Jose, 2011. "Multiscale entropy analysis of crude oil price dynamics," Energy Economics, Elsevier, vol. 33(5), pages 936-947, September.
    20. Hernández-Pérez, R. & Guzmán-Vargas, L. & Ramírez-Rojas, A. & Angulo-Brown, F., 2010. "Pattern synchrony in electrical signals related to earthquake activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(6), pages 1239-1252.
    21. Costa, M. & Peng, C.-K. & L. Goldberger, Ary & Hausdorff, Jeffrey M., 2003. "Multiscale entropy analysis of human gait dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(1), pages 53-60.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alves Xavier, Sílvio Fernando & Xavier, Érika Fialho Morais & Jale, Jader Silva & Stosic, Tatijana & Santos, Carlos Antonio Costa dos, 2021. "Multiscale entropy analysis of monthly rainfall time series in Paraíba, Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    2. de Araujo, Fernando Henrique Antunes & Bejan, Lucian & Stosic, Borko & Stosic, Tatijana, 2020. "An analysis of Brazilian agricultural commodities using permutation – information theory quantifiers: The influence of food crisis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Saud, Shah & Haseeb, Abdul & Zafar, Muhammad Wasif & Li, Huiyun, 2023. "Articulating natural resource abundance, economic complexity, education and environmental sustainability in MENA countries: Evidence from advanced panel estimation," Resources Policy, Elsevier, vol. 80(C).
    4. Maurya, Garima & Sahu, Sohini, 2022. "Cross-country variations in economic complexity: The role of individualism," Economic Modelling, Elsevier, vol. 115(C).
    5. Jia, Linlu & Ke, Jinchuan & Wang, Jun, 2020. "Fluctuation behavior analysis of stochastic exclusion financial dynamics with random jump," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    6. Xiao, Di & Wang, Jun, 2020. "Dynamic complexity and causality of crude oil and major stock markets," Energy, Elsevier, vol. 193(C).
    7. Ben Saad, Myriam & Brahim, Mariem & Schaffar, Alexandra & Guesmi, Khaled & Ben Saad, Rym, 2023. "Economic complexity, diversification and economic development: The strategic factors," Research in International Business and Finance, Elsevier, vol. 64(C).
    8. Nguyen, Canh Phuc, 2022. "Does economic complexity matter for the shadow economy?," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 210-227.
    9. Nguyen, Canh Phuc & Schinckus, Christophe & Su, Thanh Dinh, 2020. "The drivers of economic complexity: International evidence from financial development and patents," International Economics, Elsevier, vol. 164(C), pages 140-150.
    10. Yin, Jiuli & Zhu, Yan & Fan, Xinghua, 2021. "Correlation analysis of China’s carbon market and coal market based on multi-scale entropy," Resources Policy, Elsevier, vol. 72(C).
    11. Canh, Nguyen Phuc & Schinckus, Christophe & Thanh, Su Dinh, 2020. "The natural resources rents: Is economic complexity a solution for resource curse?," Resources Policy, Elsevier, vol. 69(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lima, Cristiane Rocha Albuquerque & de Melo, Gabriel Rivas & Stosic, Borko & Stosic, Tatijana, 2019. "Cross-correlations between Brazilian biofuel and food market: Ethanol versus sugar," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 687-693.
    2. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Aurelio F. Bariviera & Luciano Zunino & M. Belen Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "Efficiency and credit ratings: a permutation-information-theory analysis," Papers 1509.01839, arXiv.org.
    4. Hassouneh, Islam & Serra, Teresa & Goodwin, Barry K. & Gil, José M., 2012. "Non-parametric and parametric modeling of biodiesel, sunflower oil, and crude oil price relationships," Energy Economics, Elsevier, vol. 34(5), pages 1507-1513.
    5. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    6. Liu, Jian & Jiang, Ting & Ye, Ze, 2021. "Information efficiency research of China's carbon markets," Finance Research Letters, Elsevier, vol. 38(C).
    7. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    8. Serra, Teresa & Zilberman, David, 2013. "Biofuel-related price transmission literature: A review," Energy Economics, Elsevier, vol. 37(C), pages 141-151.
    9. Ladislav Kristoufek & Karel Janda & David Zilberman, 2013. "Regime-dependent topological properties of biofuels networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(2), pages 1-12, February.
    10. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Correlations between biofuels and related commodities before and during the food crisis: A taxonomy perspective," Energy Economics, Elsevier, vol. 34(5), pages 1380-1391.
    11. Zeng, Yayun & Wang, Jun & Xu, Kaixuan, 2017. "Complexity and multifractal behaviors of multiscale-continuum percolation financial system for Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 364-376.
    12. Niu, Hongli & Wang, Jun, 2017. "Return volatility duration analysis of NYMEX energy futures and spot," Energy, Elsevier, vol. 140(P1), pages 837-849.
    13. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.
    14. Ahmed Ghorbel & Wajdi Hamma & Anis Jarboui, 2017. "Dependence between oil and commodities markets using time-varying Archimedean copulas and effectiveness of hedging strategies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(9), pages 1509-1542, July.
    15. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & de Oliveira, Wilson & Stosic, Tatijana, 2016. "Foreign exchange rate entropy evolution during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 233-239.
    16. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & Stosic, Tatijana, 2016. "Correlations of multiscale entropy in the FX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 52-61.
    17. Bentivoglio, Deborah & Finco, Adele & Bacchi, Mirian, 2015. "Examining Price Transmission between Fuels and Food Prices: the Brazilian Sugar-Ethanol Market," 2015 Conference, August 9-14, 2015, Milan, Italy 211327, International Association of Agricultural Economists.
    18. Gardebroek, Cornelis & Hernandez, Manuel A., 2013. "Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets," Energy Economics, Elsevier, vol. 40(C), pages 119-129.
    19. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    20. Peri, Massimo & Baldi, Lucia, 2013. "The effect of biofuel policies on feedstock market: Empirical evidence for rapeseed oil prices in EU," Resource and Energy Economics, Elsevier, vol. 35(1), pages 18-37.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:523:y:2019:i:c:p:933-941. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.