Systemic risk and contagion in the commodity market: identifying volatility transmission during crisis periods
Abstract
The commodity market is a key element of the global economy. It is influenced by the political and economic situation of the major participants on the supply and demand side, as exemplified by the geopolitical and economic situation related to the conflict in Ukraine. Another aspect of this influence is the close relationship between commodity markets and financial markets. Both factors contribute to the possibility of the commodity market becoming subject to contagion, resulting in the transfer of supply and demand shocks and volatility. The aim of this article is to identify the commodities that are the source of contagion (volatility) during the transmission of shocks and the increase of systematic risk in selected periods. Combining traditional network theory with vector autoregression (VAR) model, we aim to estimate systemic linkages as a measure of systemic risk and the contagion process underlying it. We used time series of commodity returns from the Refinitiv Eikon database to observe the relationships between commodities during crisis periods, starting from 2006. The results suggest that the commodities with the largest increase in volatility transmission compared to the pre-crisis period acted as a transmission gate for market shocks.
First published online 12 December 2024
Keyword : contagion, volatility transmission, commodity market, systemic risk
How to Cite
Szturo, M., Włodarczyk, B., Ionescu, G. H., Firoiu, D., & Braga, V. (2024). Systemic risk and contagion in the commodity market: identifying volatility transmission during crisis periods. Technological and Economic Development of Economy, 1-19. https://doi.org/10.3846/tede.2024.22560
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Gimet, C., Lagoarde-Segot, T., & Reyes-Ortiz, L. (2019). Financialization and the macroeconomy. Theory and empirical evidence. Economic Modelling, 81, 89–110. https://doi.org/10.1016/j.econmod.2018.12.008
Hammoudeh, S., Nguyen, D. K., & Sousa, R. M. (2015). US monetary policy and sectoral commodity prices. Journal of International Money and Finance, 57, 61–85. https://doi.org/10.1016/j.jimonfin.2015.06.003
Issler, J. V., Rodrigues, C., & Burjack, R. (2014). Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons. Journal of International Money and Finance, 42, 310–335. https://doi.org/10.1016/j.jimonfin.2013.08.017
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Ji, Q., & Fan, Y. (2016). How do China’s oil markets affect other commodity markets both domestically and internationally? Finance Research Letters, 19, 247–254. https://doi.org/10.1016/j.frl.2016.08.009
Ji, Q., & Zhang, D. (2019). China’s crude oil futures: Introduction and some stylized facts. Finance Research Letters, 28, 376–380. https://doi.org/10.1016/j.frl.2018.06.005
Junttila, J., Pesonen, J., & Raatikainen, J. (2018). Commodity market based hedging against stock market risk in times of financial crisis: The case of crude oil and gold. Journal of International Financial Markets, Institutions and Money, 56, 255–280. https://doi.org/10.1016/j.intfin.2018.01.002
Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. https://doi.org/10.1016/0304-4076(95)01753-4
Lazonick, W. (2011). From innovation to financialization: How shareholder value ideology is destroying US economy. https://www.theairnet.org/files/research/lazonick/Lazonick%20Innovation%20Financialization%2020110616.pdf
López Cabrera, B., & Schulz, F. (2016). Volatility linkages between energy and agricultural commodity prices. Energy Economics, 54, 190–203. https://doi.org/10.1016/j.eneco.2015.11.018
Maneejuk, P., & Yamaka, W. (2021). The role of economic contagion in the inward investment of emerging economies: The dynamic conditional copula approach. Mathematics, 9(20), Article 2540. https://doi.org/10.3390/math9202540
Mellios, C., Six, P., & Lai, A. N. (2016). Dynamic speculation and hedging in commodity futures markets with a stochastic convenience yield. European Journal of Operational Research, 250(2), 493–504. https://doi.org/10.1016/j.ejor.2015.10.045
Mensi, W., Hammoudeh, S., Nguyen, D. K., & Yoon, S. M. (2014). Dynamic spillovers among major energy and cereal commodity prices. Energy Economics, 43, 225–243. https://doi.org/10.1016/j.eneco.2014.03.004
Ohashi, K., & Okimoto, T. (2016). Increasing trends in the excess comovement of commodity prices. Journal of Commodity Markets, 1(1), 48–64. https://doi.org/10.1016/j.jcomm.2016.02.001
Osei, P. M., & Adam, A. M. (2020). Quantifying the information flow between Ghana stock market index and its constituents using transfer entropy. Mathematical Problems in Engineering, 2020(1), Article 6183421. https://doi.org/10.1155/2020/6183421
Öztek, M. F., & Öcal, N. (2017). Financial crises and the nature of correlation between commodity and stock markets. International Review of Economics & Finance, 48, 56–68. https://doi.org/10.1016/j.iref.2016.11.008
Park, C.-Y., & Shin, K. (2017). A contagion through exposure to foreign banks during the global financial crisis (ADB Economica Working Paper Series No. 516). Asian Development Bank. https://doi.org/10.22617/WPS178929-2
Peetz, D., & Genreith, H. (2011). The financial sector and the real economy. Real-World Economics Review, 57, 41–47. http://rwer.wordpress.com/2011/09/06/rwer-issue-57-peetz-and-genreith/
Pritsker, M. (2001). The channels for financial contagion. In S. Claessens & K. J. Forbes (Eds.), International financial contagion (pp. 67–95). Springer. https://doi.org/10.1007/978-1-4757-3314-3_4
Refinitiv Eikon. (2022). Commodities daily prices – Time series data.
Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1–48. https://doi.org/10.2307/1912017
Śmiech, S., Papiez, M., & Dabrowski, M. A. (2015). Does the euro area macroeconomy affect global commodity prices? Evidence from a SVAR approach. International Review of Economics & Finance, 39, 485–503. https://doi.org/10.1016/j.iref.2015.07.012
Staugaitis, A. J., & Vaznonis, B. (2022). Financial speculation impact on agricultural and other commodity return volatility: Implications for sustainable development and food security. Agriculture, 12(11), Article 1892. https://doi.org/10.3390/agriculture12111892
Tadasse, G., Algieri, B., Kalkuhl, M., & von Braun, J. (2016). Drivers and triggers of international food price spikes and volatility. In M. Kalkuhl, J. von Braun, & Torero, M. (Eds.), Food price volatility and its implications for food security and policy (pp. 59–82). Springer. https://doi.org/10.1007/978-3-319-28201-5_3
Wang, K.-H., Su, C.-W., Umar, M., & Lobonţ, O.-R. (2023). Oil price shocks, economic policy uncertainty, and green finance: A case of China. Technological and Economic Development of Economy, 29(2), 500–517. https://doi.org/10.3846/tede.2022.17999
Wang, S. L., & McPhail, L. (2014). Impacts of energy shocks on US agricultural productivity growth and commodity prices – A structural VAR analysis. Energy Economics, 46, 435–444. https://doi.org/10.1016/j.eneco.2014.05.006
Wang, Y., Wu, C., & Yang, L. (2014). Oil price shocks and agricultural commodity prices. Energy Economics, 44, 22–35. https://doi.org/10.1016/j.eneco.2014.03.016
West, K. D., & Wong, K.-F. (2014). A factor model for co-movements of commodity prices. Journal of International Money and Finance, 42, 289–309. https://doi.org/10.1016/j.jimonfin.2013.08.016
Yang, Z., & Zhou, Y. (2016). Quantitative easing and volatility spillovers across countries and asset classes. Management Science, 63(2), 279–585. https://doi.org/10.1287/mnsc.2015.2305
Yin, L., & Han, L. (2015). Co-movements in commodity prices: Global, sectoral and commodity-specific factors. Economics Letters, 126, 96–100. https://doi.org/10.1016/j.econlet.2014.11.027
Yip, P. S., Brooks, R., & Do, H. X. (2017). Dynamic spillover between commodities and commodity currencies during United States Q.E. Energy Economics, 66, 399–410. https://doi.org/10.1016/j.eneco.2017.07.008
Zhang, D. (2017). Oil shocks and stock markets revisited: Measuring connectedness from a global perspective. Energy Economics, 62, 323–333. https://doi.org/10.1016/j.eneco.2017.01.009
Zhang, D., Shi, M., & Shi, X. (2018). Oil indexation, market fundamentals, and natural gas prices: An investigation of the Asian premium in natural gas trade. Energy Economics, 69, 33–41. https://doi.org/10.1016/j.eneco.2017.11.001
Zhang, H. J., Dufour, J.-M., & Galbraith, J. W. (2016). Exchange rates and commodity prices: Measuring causality at multiple horizons. Journal of Empirical Finance, 36, 100–120. https://doi.org/10.1016/j.jempfin.2015.10.005
Agénor, P. R., & Aizenman, J. (1998). Contagion and volatility with imperfect credit markets. IMF Staff Papers, 45(2), 207–235. https://doi.org/10.2307/3867389
Ahnert, T., & Bertsch, C. (2022). A wake-up call theory of Contagion (ECB Working Paper No. 2022/2658). European Central Bank. https://doi.org/10.2139/ssrn.4100188
Aït-Youcef, C. (2019). How index investment impacts commodities: A story about the financialization of agricultural commodities. Economic Modelling, 80, 23–33. https://doi.org/10.1016/j.econmod.2018.04.007
Alami, I. (2021). Money power and financial capital in emerging markets: Facing the liquidity tsunami. Routledge. https://www.routledge.com/Money-Power-and-Financial-Capital-in-Emerging-Markets-Facing-the-Liquidity/Alami/p/book/9781032082356
Antonakakis, N., Chatziantoniou, I., & Filis, G. (2014). Dynamic spillovers of oil price shocks and economic policy uncertainty. Energy Economics, 44, 433–447. https://doi.org/10.1016/j.eneco.2014.05.007
Arezki, R., Loungani, P., van der Ploeg, R., & Venables, A. J. (2014). Understanding international commodity price fluctuations. Journal of International Money and Finance, 42, 1–8. https://doi.org/10.1016/j.jimonfin.2013.08.002
Asafo-Adjei, E., Adam, A. M., Adu-Asare Idun, A., & Ametepi, P. Y. (2022). Dynamic interdependence of systematic risks in emerging markets economies: A recursive-based frequency-domain approach. Discrete Dynamics in Nature and Society, 2022(1), Article 1139869. https://doi.org/10.1155/2022/1139869
Beckmann, J., Belke, A., & Czudaj, R. (2014). Does global liquidity drive commodity prices? Journal of Banking & Finance, 48, 224–234. https://doi.org/10.1016/j.jbankfin.2014.04.007
Berger, T., & Uddin, G. S. (2016). On the dynamic dependence between equity markets, commodity futures and economic uncertainty indexes. Energy Economics, 56, 374–383. https://doi.org/10.1016/j.eneco.2016.03.024
Bodart, V., Candelon, B., & Carpantier, J.-F. (2012). Real exchanges rates in commodity producing countries: A reappraisal. Journal of International Money and Finance, 31(6), 1482–1502. https://doi.org/10.1016/j.jimonfin.2012.02.012
Byrne, J. P., Fazio, G., & Fiess, N. (2013). Primary commodity prices: Co-movements, common factors and fundamentals. Journal of Development Economics, 101(1), 16–26. https://doi.org/10.1016/j.jdeveco.2012.09.002
Chen, S., Huang, Y., & Ge, L. (2024). An early warning system for financial crises: A temporal convolutional network approach. Technological and Economic Development of Economy, 30(3), 688–711. https://doi.org/10.3846/tede.2024.20555
Cheng, I.-H., & Xiong, W. (2014). Financialization of commodity markets. Annual Review of Financial Economics, 6, 419–941. https://doi.org/10.1146/annurev-financial-110613-034432
Diebold, F. X., & Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119(534), 158–171. https://doi.org/10.1111/j.1468-0297.2008.02208.x
Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66. https://doi.org/10.1016/j.ijforecast.2011.02.006
Diebold, F. X., & Yilmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119–134. https://doi.org/10.1016/j.jeconom.2014.04.012
Fernández, A., González, A., & Rodríguez, D. (2018). Sharing a ride on the commodities roller coaster: Common factors in business cycles of emerging economies. Journal of International Economics, 111, 99–121. https://doi.org/10.1016/j.jinteco.2017.11.008
Foster, J. B., Jonna, R. J., & Clark, B. (2021). The contagion of capital. Financialized capitalism, COVID-19, and the great divide. Monthly Review, 72(8), 1–19. https://doi.org/10.14452/MR-072-08-2021-01_1
Fotiou, A., Bonk, A. I., & Manalis, G. (2022). Contagion as a dealmaker? The effect of financial spillovers on regional lending programs. (IMF Working Papers 2022(133)). International Monetary Fund. https://doi.org/10.5089/9798400204937.001
Gao, J., Mao, Y., Xu, Z., & Luo, Q. (2024). Quantitative investment decisions based on machine learning and investor attention analysis. Technological and Economic Development of Economy, 30(3), 527–561. https://doi.org/10.3846/tede.2023.18672
Gimet, C., Lagoarde-Segot, T., & Reyes-Ortiz, L. (2019). Financialization and the macroeconomy. Theory and empirical evidence. Economic Modelling, 81, 89–110. https://doi.org/10.1016/j.econmod.2018.12.008
Hammoudeh, S., Nguyen, D. K., & Sousa, R. M. (2015). US monetary policy and sectoral commodity prices. Journal of International Money and Finance, 57, 61–85. https://doi.org/10.1016/j.jimonfin.2015.06.003
Issler, J. V., Rodrigues, C., & Burjack, R. (2014). Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons. Journal of International Money and Finance, 42, 310–335. https://doi.org/10.1016/j.jimonfin.2013.08.017
Jajuga, K., & Jajuga, T. (2011). Inwestycje. Instrumenty finansowe, aktywa niefinansowe, ryzyko finansowe, inżynieria finansowa [Investments. Financial instruments, non-financial assets, financial risk, financial engineering]. PWN. https://ksiegarnia.pwn.pl/Inwestycje,68736511,p.html
Ji, Q., & Fan, Y. (2016). How do China’s oil markets affect other commodity markets both domestically and internationally? Finance Research Letters, 19, 247–254. https://doi.org/10.1016/j.frl.2016.08.009
Ji, Q., & Zhang, D. (2019). China’s crude oil futures: Introduction and some stylized facts. Finance Research Letters, 28, 376–380. https://doi.org/10.1016/j.frl.2018.06.005
Junttila, J., Pesonen, J., & Raatikainen, J. (2018). Commodity market based hedging against stock market risk in times of financial crisis: The case of crude oil and gold. Journal of International Financial Markets, Institutions and Money, 56, 255–280. https://doi.org/10.1016/j.intfin.2018.01.002
Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. https://doi.org/10.1016/0304-4076(95)01753-4
Lazonick, W. (2011). From innovation to financialization: How shareholder value ideology is destroying US economy. https://www.theairnet.org/files/research/lazonick/Lazonick%20Innovation%20Financialization%2020110616.pdf
López Cabrera, B., & Schulz, F. (2016). Volatility linkages between energy and agricultural commodity prices. Energy Economics, 54, 190–203. https://doi.org/10.1016/j.eneco.2015.11.018
Maneejuk, P., & Yamaka, W. (2021). The role of economic contagion in the inward investment of emerging economies: The dynamic conditional copula approach. Mathematics, 9(20), Article 2540. https://doi.org/10.3390/math9202540
Mellios, C., Six, P., & Lai, A. N. (2016). Dynamic speculation and hedging in commodity futures markets with a stochastic convenience yield. European Journal of Operational Research, 250(2), 493–504. https://doi.org/10.1016/j.ejor.2015.10.045
Mensi, W., Hammoudeh, S., Nguyen, D. K., & Yoon, S. M. (2014). Dynamic spillovers among major energy and cereal commodity prices. Energy Economics, 43, 225–243. https://doi.org/10.1016/j.eneco.2014.03.004
Ohashi, K., & Okimoto, T. (2016). Increasing trends in the excess comovement of commodity prices. Journal of Commodity Markets, 1(1), 48–64. https://doi.org/10.1016/j.jcomm.2016.02.001
Osei, P. M., & Adam, A. M. (2020). Quantifying the information flow between Ghana stock market index and its constituents using transfer entropy. Mathematical Problems in Engineering, 2020(1), Article 6183421. https://doi.org/10.1155/2020/6183421
Öztek, M. F., & Öcal, N. (2017). Financial crises and the nature of correlation between commodity and stock markets. International Review of Economics & Finance, 48, 56–68. https://doi.org/10.1016/j.iref.2016.11.008
Park, C.-Y., & Shin, K. (2017). A contagion through exposure to foreign banks during the global financial crisis (ADB Economica Working Paper Series No. 516). Asian Development Bank. https://doi.org/10.22617/WPS178929-2
Peetz, D., & Genreith, H. (2011). The financial sector and the real economy. Real-World Economics Review, 57, 41–47. http://rwer.wordpress.com/2011/09/06/rwer-issue-57-peetz-and-genreith/
Pritsker, M. (2001). The channels for financial contagion. In S. Claessens & K. J. Forbes (Eds.), International financial contagion (pp. 67–95). Springer. https://doi.org/10.1007/978-1-4757-3314-3_4
Refinitiv Eikon. (2022). Commodities daily prices – Time series data.
Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1–48. https://doi.org/10.2307/1912017
Śmiech, S., Papiez, M., & Dabrowski, M. A. (2015). Does the euro area macroeconomy affect global commodity prices? Evidence from a SVAR approach. International Review of Economics & Finance, 39, 485–503. https://doi.org/10.1016/j.iref.2015.07.012
Staugaitis, A. J., & Vaznonis, B. (2022). Financial speculation impact on agricultural and other commodity return volatility: Implications for sustainable development and food security. Agriculture, 12(11), Article 1892. https://doi.org/10.3390/agriculture12111892
Tadasse, G., Algieri, B., Kalkuhl, M., & von Braun, J. (2016). Drivers and triggers of international food price spikes and volatility. In M. Kalkuhl, J. von Braun, & Torero, M. (Eds.), Food price volatility and its implications for food security and policy (pp. 59–82). Springer. https://doi.org/10.1007/978-3-319-28201-5_3
Wang, K.-H., Su, C.-W., Umar, M., & Lobonţ, O.-R. (2023). Oil price shocks, economic policy uncertainty, and green finance: A case of China. Technological and Economic Development of Economy, 29(2), 500–517. https://doi.org/10.3846/tede.2022.17999
Wang, S. L., & McPhail, L. (2014). Impacts of energy shocks on US agricultural productivity growth and commodity prices – A structural VAR analysis. Energy Economics, 46, 435–444. https://doi.org/10.1016/j.eneco.2014.05.006
Wang, Y., Wu, C., & Yang, L. (2014). Oil price shocks and agricultural commodity prices. Energy Economics, 44, 22–35. https://doi.org/10.1016/j.eneco.2014.03.016
West, K. D., & Wong, K.-F. (2014). A factor model for co-movements of commodity prices. Journal of International Money and Finance, 42, 289–309. https://doi.org/10.1016/j.jimonfin.2013.08.016
Yang, Z., & Zhou, Y. (2016). Quantitative easing and volatility spillovers across countries and asset classes. Management Science, 63(2), 279–585. https://doi.org/10.1287/mnsc.2015.2305
Yin, L., & Han, L. (2015). Co-movements in commodity prices: Global, sectoral and commodity-specific factors. Economics Letters, 126, 96–100. https://doi.org/10.1016/j.econlet.2014.11.027
Yip, P. S., Brooks, R., & Do, H. X. (2017). Dynamic spillover between commodities and commodity currencies during United States Q.E. Energy Economics, 66, 399–410. https://doi.org/10.1016/j.eneco.2017.07.008
Zhang, D. (2017). Oil shocks and stock markets revisited: Measuring connectedness from a global perspective. Energy Economics, 62, 323–333. https://doi.org/10.1016/j.eneco.2017.01.009
Zhang, D., Shi, M., & Shi, X. (2018). Oil indexation, market fundamentals, and natural gas prices: An investigation of the Asian premium in natural gas trade. Energy Economics, 69, 33–41. https://doi.org/10.1016/j.eneco.2017.11.001
Zhang, H. J., Dufour, J.-M., & Galbraith, J. W. (2016). Exchange rates and commodity prices: Measuring causality at multiple horizons. Journal of Empirical Finance, 36, 100–120. https://doi.org/10.1016/j.jempfin.2015.10.005