IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v85y2020icp381-389.html
   My bibliography  Save this article

Financialization of agricultural commodities: Evidence from China

Author

Listed:
  • Ouyang, Ruolan
  • Zhang, Xuan

Abstract

Speculation in the commodity futures market distorts commodity prices, driving them away from rational levels. This phenomenon, which is known as the financialization of commodities, has raised significant concerns in recent years. Particularly, in the agricultural market, ‘financialized’ commodities have been blamed for high world food prices. In this paper, we examine the financialization of agricultural commodities in China. To do so, a time-varying copula is employed to investigate the dependence structure between commodities and stock markets. Four insightful results are obtained. First, positive correlations between agricultural commodities and stock markets demonstrate the financialization of agricultural commodities. Second, the identified correlations are time-varying and idiosyncratic with respect to products. Third, the agricultural commodity market is more closely correlated with the domestic stock market than with the overseas market. Fourth, a growing dependence between commodities and the stock markets is detected and the co-movement became stronger after the global financial crisis.

Suggested Citation

  • Ouyang, Ruolan & Zhang, Xuan, 2020. "Financialization of agricultural commodities: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 381-389.
  • Handle: RePEc:eee:ecmode:v:85:y:2020:i:c:p:381-389
    DOI: 10.1016/j.econmod.2019.11.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999319309964
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econmod.2019.11.009?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. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andr� Lucas, 2014. "Observation-Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 898-915, December.
    2. Irwin, Scott H. & Sanders, Dwight R., 2012. "Financialization and Structural Change in Commodity Futures Markets," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(3), pages 371-396, August.
    3. Ing-Haw Cheng & Wei Xiong, 2014. "Financialization of Commodity Markets," Annual Review of Financial Economics, Annual Reviews, vol. 6(1), pages 419-441, December.
    4. Davide Meneguzzo & Walter Vecchiato, 2004. "Copula sensitivity in collateralized debt obligations and basket default swaps," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(1), pages 37-70, January.
    5. Büyükşahin, Bahattin & Robe, Michel A., 2014. "Speculators, commodities and cross-market linkages," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 38-70.
    6. Genèvre Covindassamy & Michel A. Robe & Jonathan Wallen, 2017. "Sugar with your Coffee? Fundamentals, Financials, and Softs Price Uncertainty," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(8), pages 744-765, August.
    7. Dong Hwan Oh & Andrew J. Patton, 2018. "Time-Varying Systemic Risk: Evidence From a Dynamic Copula Model of CDS Spreads," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(2), pages 181-195, April.
    8. Christiane Baumeister & Lutz Kilian, 2014. "Do oil price increases cause higher food prices? [Biofuels, binding constraints, and agricultural commodity price volatility]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 29(80), pages 691-747.
    9. Daniele Girardi, 2015. "Financialization of food . Modelling the time-varying relation between agricultural prices and stock market dynamics," International Review of Applied Economics, Taylor & Francis Journals, vol. 29(4), pages 482-505, July.
    10. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
    11. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2017. "Can energy commodity futures add to the value of carbon assets?," Economic Modelling, Elsevier, vol. 62(C), pages 194-206.
    12. Delatte, Anne-Laure & Lopez, Claude, 2013. "Commodity and equity markets: Some stylized facts from a copula approach," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5346-5356.
    13. Christoffersen, Peter & Lunde, Asger & Olesen, Kasper V., 2019. "Factor Structure in Commodity Futures Return and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(3), pages 1083-1115, June.
    14. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
    15. André Lucas & Bernd Schwaab & Xin Zhang, 2014. "Conditional Euro Area Sovereign Default Risk," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 271-284, April.
    16. Luc Bauwens & Nikolaus Hautsch, 2006. "Stochastic Conditional Intensity Processes," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 450-493.
    17. De Lira Salvatierra, Irving & Patton, Andrew J., 2015. "Dynamic copula models and high frequency data," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 120-135.
    18. Panos Fousekis & Vasilis Grigoriadis, 2019. "How well can investors diversify with commodities? Evidence from a flexible copula approach," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 36(2), pages 183-206, April.
    19. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    20. Giesecke, Kay, 2004. "Correlated default with incomplete information," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1521-1545, July.
    21. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    22. Sanjiv R. Das & Darrell Duffie & Nikunj Kapadia & Leandro Saita, 2007. "Common Failings: How Corporate Defaults Are Correlated," Journal of Finance, American Finance Association, vol. 62(1), pages 93-117, February.
    23. Covindassamy, Genevre & Robe, Michel A. & Wallen, Jonathan, 2016. "Sugar With Your Coffee?: Financials, Fundamentals, and Soft Price Uncertainty," IDB Publications (Working Papers) 8588, Inter-American Development Bank.
    24. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    25. Dietrich Domanski & Alexandra Heath, 2007. "Financial investors and commodity markets," BIS Quarterly Review, Bank for International Settlements, March.
    26. Suleyman Basak & Anna Pavlova, 2016. "A Model of Financialization of Commodities," Journal of Finance, American Finance Association, vol. 71(4), pages 1511-1556, August.
    27. Myers, Robert J., 2006. "On the costs of food price fluctuations in low-income countries," Food Policy, Elsevier, vol. 31(4), pages 288-301, August.
    28. Paul Glasserman & Jingyi Li, 2005. "Importance Sampling for Portfolio Credit Risk," Management Science, INFORMS, vol. 51(11), pages 1643-1656, November.
    29. Scott H. Irwin & Dwight R. Sanders, 2011. "Index Funds, Financialization, and Commodity Futures Markets," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 1-31.
    30. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    31. Wen, Xiaoqian & Nguyen, Duc Khuong, 2017. "Can investors of Chinese energy stocks benefit from diversification into commodity futures?," Economic Modelling, Elsevier, vol. 66(C), pages 184-200.
    32. Drew Creal & Siem Jan Koopman & André Lucas, 2013. "Generalized Autoregressive Score Models With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 777-795, August.
    33. David Hirshleifer, 1988. "Residual Risk, Trading Costs, and Commodity Futures Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 1(2), pages 173-193.
    34. James D. Hamilton & Jing Cynthia Wu, 2015. "Effects Of Index‐Fund Investing On Commodity Futures Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 187-205, February.
    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. Lin Xie & Jiahua Liao & Haiting Chen & Xuefei Yan & Xinyan Hu, 2021. "Is Futurization the Culprit for the Violent Fluctuation in China’s Apple Spot Price?," Agriculture, MDPI, vol. 11(4), pages 1-14, April.
    2. Hussein Abdoh & Michael Chitavi, 2024. "The impact of deviations from soybean product crushing estimates on return and risk," Agricultural Economics, International Association of Agricultural Economists, vol. 55(2), pages 181-199, March.
    3. Wen, Danyan & Wang, Yudong, 2021. "Volatility linkages between stock and commodity markets revisited: Industry perspective and portfolio implications," Resources Policy, Elsevier, vol. 74(C).
    4. Ding, Shusheng & Cui, Tianxiang & Zheng, Dandan & Du, Min, 2021. "The effects of commodity financialization on commodity market volatility," Resources Policy, Elsevier, vol. 73(C).
    5. Dejan Živkov & Jasmina Đurašković & Marina Gajić‐Glamočlija, 2022. "Multiscale downside risk interdependence between the major agricultural commodities," Agribusiness, John Wiley & Sons, Ltd., vol. 38(4), pages 990-1011, October.
    6. Ouyang, Ruolan & Chen, Xiang & Fang, Yi & Zhao, Yang, 2022. "Systemic risk of commodity markets: A dynamic factor copula approach," International Review of Financial Analysis, Elsevier, vol. 82(C).
    7. Wang, Haiying & Yuan, Ying & Li, Yiou & Wang, Xunhong, 2021. "Financial contagion and contagion channels in the forex market: A new approach via the dynamic mixture copula-extreme value theory," Economic Modelling, Elsevier, vol. 94(C), pages 401-414.
    8. Zhu, Xuehong & Chen, Ying & Chen, Jinyu, 2021. "Effects of non-ferrous metal prices and uncertainty on industry stock market under different market conditions," Resources Policy, Elsevier, vol. 73(C).
    9. El Montasser, Ghassen & Malek Belhoula, Mohamed & Charfeddine, Lanouar, 2023. "Co-explosivity versus leading effects: Evidence from crude oil and agricultural commodities," Resources Policy, Elsevier, vol. 81(C).
    10. Niu, Hongli & Hu, Ziang, 2021. "Information transmission and entropy-based network between Chinese stock market and commodity futures market," Resources Policy, Elsevier, vol. 74(C).
    11. Li, Houjian & Li, Yanjiao & Guo, Lili, 2023. "Extreme risk spillover effect and dynamic linkages between uncertainty and commodity markets: A comparison between China and America," Resources Policy, Elsevier, vol. 85(PA).
    12. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    13. Borgards, Oliver & Czudaj, Robert L. & Hoang, Thi Hong Van, 2021. "Price overreactions in the commodity futures market: An intraday analysis of the Covid-19 pandemic impact," Resources Policy, Elsevier, vol. 71(C).
    14. Zhuo Chen & Bo Yan & Hanwen Kang, 2023. "Price bubbles of agricultural commodities: evidence from China’s futures market," Empirical Economics, Springer, vol. 64(1), pages 195-222, January.
    15. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
    16. Krzysztof Drachal & Michał Pawłowski, 2024. "Forecasting Selected Commodities’ Prices with the Bayesian Symbolic Regression," IJFS, MDPI, vol. 12(2), pages 1-56, March.
    17. Ruano, Fábio & Barros, Victor, 2022. "Commodities and portfolio diversification: Myth or fact?," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 281-295.
    18. Idilbi-Bayaa, Yasmeen & Qadan, Mahmoud, 2022. "What the current yield curve says, and what the future prices of energy do," Resources Policy, Elsevier, vol. 75(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. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Correlated Defaults of UK Banks: Dynamics and Asymmetries," Working Papers 2015_24, Business School - Economics, University of Glasgow.
    2. Ouyang, Ruolan & Chen, Xiang & Fang, Yi & Zhao, Yang, 2022. "Systemic risk of commodity markets: A dynamic factor copula approach," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Wen, Xiaoqian & Xie, Yuxin & Pantelous, Athanasios A., 2022. "Extreme price co-movement of commodity futures and industrial production growth: An empirical evaluation," Energy Economics, Elsevier, vol. 108(C).
    4. Yao, Wei & Alexiou, Constantinos, 2024. "On the transmission mechanism between the inventory arbitrage activity, speculative activity and the commodity price under the US QE policy: Evidence from a TVP-VAR model," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1054-1072.
    5. Zhang, Xuan & Kim, Minjoo & Yan, Cheng & Zhao, Yang, 2024. "Default dependence in the insurance and banking sectors: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    6. Bianchi, Robert J. & Fan, John Hua & Todorova, Neda, 2020. "Financialization and de-financialization of commodity futures: A quantile regression approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    7. Bahloul, Walid & Balcilar, Mehmet & Cunado, Juncal & Gupta, Rangan, 2018. "The role of economic and financial uncertainties in predicting commodity futures returns and volatility: Evidence from a nonparametric causality-in-quantiles test," Journal of Multinational Financial Management, Elsevier, vol. 45(C), pages 52-71.
    8. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    9. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    10. Xiao, Qin & Yan, Meilan & Zhang, Dalu, 2023. "Commodity market financialization, herding and signals: An asymmetric GARCH R-vine copula approach," International Review of Financial Analysis, Elsevier, vol. 89(C).
    11. Haase, Marco & Seiler Zimmermann, Yvonne & Zimmermann, Heinz, 2016. "The impact of speculation on commodity futures markets – A review of the findings of 100 empirical studies," Journal of Commodity Markets, Elsevier, vol. 3(1), pages 1-15.
    12. Nevrla, Matěj, 2020. "Systemic risk in European financial and energy sectors: Dynamic factor copula approach," Economic Systems, Elsevier, vol. 44(4).
    13. Ordu, Beyza Mina & Oran, Adil & Soytas, Ugur, 2018. "Is food financialized? Yes, but only when liquidity is abundant," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 82-96.
    14. Sercan Demiralay & Selcuk Bayraci & H. Gaye Gencer, 2019. "Time-varying diversification benefits of commodity futures," Empirical Economics, Springer, vol. 56(6), pages 1823-1853, June.
    15. Boyd, Naomi E. & Harris, Jeffrey H. & Li, Bingxin, 2018. "An update on speculation and financialization in commodity markets," Journal of Commodity Markets, Elsevier, vol. 10(C), pages 91-104.
    16. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    17. Filippo Natoli, 2018. "Analyzing the structural transformation of commodity markets: financialization revisited," Questioni di Economia e Finanza (Occasional Papers) 419, Bank of Italy, Economic Research and International Relations Area.
    18. Wu, Nan & Wen, Fenghua & Gong, Xu, 2022. "Marionettes behind co-movement of commodity prices: Roles of speculative and hedging activities," Energy Economics, Elsevier, vol. 115(C).
    19. Amar, Amine Ben & Goutte, Stéphane & Isleimeyyeh, Mohammad & Benkraiem, Ramzi, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    20. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-78, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    More about this item

    Keywords

    Financialization; Agricultural commodities; Stock market;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

    Statistics

    Access and download statistics

    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:ecmode:v:85:y:2020:i:c:p:381-389. 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.elsevier.com/locate/inca/30411 .

    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.