Financial contagion of commodity markets from energy markets during the pandemic, energy crisis and SMO
https://doi.org/10.55959/MSU0130-0105-6-59-5-1
Abstract
The financialization of commodity markets leads to their integration with global financial markets and increasing inclusion in chains of transmission of systemic risk in the economy. Financial contagion is an atypical increase in the interdependence of financial markets under the influence of external shocks. The subject of this study is the financial contagion of global commodity markets (soft and agricultural goods) from the global energy market (oil and gas) during the pandemic, energy crisis and special military operation of Russia in Ukraine (SMO). The purpose of the study is to establish the facts of financial contagion, its dynamics and intensity for different groups of goods. The construction of the author's stress indices allows us to distinguish between periods of a calm market and increased market volatility. Testing for contagion is carried out using the construction of ARDL-GARCH models, dynamic method of co-moments of the returns distribution of the source market of contagion and the recipient market, including the calculation of conditional correlation, coskewness, cokurtosis and covolatility. A conclusion about possible contagion is made based on a comparison of test statistics with a critical value for a normal or asymptotically normal distribution. The study confirmed contagion of exchange-traded futures markets by oil and natural gas futures markets in all periods. Oil market showed greater contagiousness compared to the gas market; oil proved to be relatively uniformly contagious in different periods, while gas proved to be relatively more contagious during the SMO. Agricultural commodities have proven to be more susceptible to contagion from energy markets than soft commodities. Stronger market contagion occurs at higher co-moments of distribution (volatility contagion, return-volatility and return-asymmetry contagion) than at lower co-moments of distribution. The results obtained can be useful for investors in developing optimal hedging strategies and managing investment portfolios, and for the state in improving financial stabilization policies during periods of crisis.
Keywords
About the Author
M. Yu. MalkinaRussian Federation
Nizhny Novgorod
References
1. Malkina, M. Yu. (2023). Financial contagion from oil shocks during the pandemic: a cross-sector analysis. Terra Economicus, 21(2), 6–22. https://doi.org/10.18522/2073-6606-2023-21-2-6-22
2. Malkina, M. Yu., & Ovcharov, A. O. (2019). Financial stress index as a generalized indicator of fi nancial instability. Financial journal, 49(3), 38–54. http://dx.doi.org/10.31107/2075-1990-2019-3-38-54
3. Pivnickaya, N., & Teplova, T. (2021). DCC-GARCH-Model for identifying long-term and short-term eff ects of fi nancial contagion in response to the credit rating updates. Economics and Mathematical Methods, 57(1), 113–123. https://doi.org/10.31857/S042473880014080-7
4. Abdullah, M., Abakah, E. J. A., Ullah, G. M. W., Tiwari, A. K., & Khan, I. (2023). Tail risk contagion across electricity markets in crisis periods. Energy Economics, 127(B), 107100. https://doi.org/10.1016/j.eneco.2023.107100
5. Algieri, B., & Leccadito, A. (2017). Assessing contagion risk from energy and nonenergy commodity markets. Energy Economics, 62, 312–322. https://doi.org/10.1016/j.eneco.2017.01.006
6. Apergis, N., Christou, C., & Kynigakis, I. (2019). Contagion across US and European fi nancial markets: Evidence from the CDS markets. Journal of International Money and Finance, 96, 1–12. https://doi.org/10.1016/j.jimonfin.2019.04.006
7. Aye, G. C., Christou, C., Gupta, R., & Hassapis, C. (2022). High-Frequency Contagion between Aggregate and Regional Housing Markets of the United States with Financial Assets: Evidence from Multichannel Tests. The Journal of Real Estate Finance and Economics, 69, 253–276. https://doi.org/10.1007/s11146-022-09919-8
8. Boroumand, R. H., & Porcher, T. (2023). Volatility contagion and connectedness between WTI and commodity markets. Finance Research Letters, 58(A), 103959. https://doi.org/10.1016/j.frl.2023.103959
9. Cabrera, B. L., & 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.
10. Chalid, D. A., & Handika, R. (2022). Comovement and contagion in commodity markets. Cogent Economics and Finance, 10(1), 2064079., https://doi.org/10.1080/23322039.2022.2064079
11. Chang, T.-H., & Su, H.-M. (2010). The substitutive eff ect of biofuels on fossil fuels in the lower and higher crude oil price periods. Energy, 35(7), 2807–2813. https://doi.org/10.1016/j.energy.2010.03.006
12. Dajcman, S. (2013). Forbes and Rigobon’s Method of Contagion Analysis with Endogenously Defi ned Crisis Periods — an Application to Some of Eurozone’s Stock Markets. Inzinerine Ekonomika-Engineering Economics, 24(4), 291–299. https://doi.org/10.5755/j01.ee.24.4.5419
13. Domanski, D., & Heath, A. (2007). Financial Investors and Commodity Markets. BIS Quarterly Review, March 2007. https://ssrn.com/abstract=1600058
14. Dornbusch, R., Park, Y. C., & Claessens, S. (2000). Contagion: Understanding How It Spreads. The World Bank Research Observer, 15(2), 177–197. https://doi.org/10.1093/wbro/15.2.177
15. Erb, C. B., & Harvey, C. R. (2006). The Strategic and Tactical Value of Commodity Futures. Financial Analysts Journal, 62(2), 69–97. http://dx.doi.org/10.2469/faj.v62.n2.4084
16. Fengler, M. R., & Okhrin, O. (2016). Managing risk with a realized copula parameter. Computational Statistics & Data Analysis, 100, 131–152. https://doi.org/10.1016/j.csda.2014.07.011
17. Forbes, K., & Rigobon, R. (2002). No contagion, only interdependence: Measuring stock market comovements. Journal of Finance, 57(5), 2223–2261. https://www.jstor.org/stable/3094510
18. Fry, R., Martin, V. L., & Tang, C. (2010). A new class of tests of contagion with applications. Journal of Business & Economic Statistics, 28(3), 423–437. http://dx.doi.org/10.1198/jbes.2010.06060
19. Fry-McKibbin, R., & Hsiao, C. Y. L. (2018). Extremal dependence tests for contagion, Econometric Reviews, 37(6), 626–649. http://dx.doi.org/10.1080/07474938.2015.1122270
20. Fry-McKibbin, R., Hsiao, C. Y. -L., & Tang, C. (2014). Contagion and Global Financial Crises: Lessons from Nine Crisis Episodes. Open Economies Review, 25, 521–570. https://doi.org/10.1007/s11079-013-9289-1
21. Fry-McKibbin, R., Greenwood-Nimmo, M., Hsiao, C. Y. -L., & Qi, L. (2022). Higherorder comoment contagion among G20 equity markets during the COVID-19 pandemic. Finance Research Letters, 45, 102150. https://doi.org/10.1016/j.frl.2021.102150
22. Gallegati, M. (2012). A wavelet-based approach to test for fi nancial market contagion. Computational Statistics & Data Analysis, 56(11), 3491–3497. https://doi.org/10.1016/j.csda.2010.11.003
23. Gong, X., Jin, Y., & Liu, T. (2023). Analyzing pure contagion between crude oil and agricultural futures markets. Energy, 269, 126757. https://doi.org/10.1016/j.energy.2023.126757
24. Grillini, S., Ozkan, A., & Sharma, A. (2022). Static and dynamic liquidity spillovers in the Eurozone: The role of fi nancial contagion and the Covid-19 pandemic. International Review of Financial Analysis, 83, 102273. http://dx.doi.org/10.1016/j.irfa.2022.102273
25. Guidolin, M., & Pedio, M. (2017). Identifying and measuring the contagion channels at work in the European fi nancial crises. Journal of International Financial Markets, Institutions and Money, 48, 117–134. https://doi.org/10.1016/J.INTFIN.2017.01.001
26. Hassan, K., Hoque, A., Gasbarro, D., & Wong, W.-K. (2023). Are Islamic stocks immune from fi nancial crises? Evidence from contagion tests. International Review of Economics & Finance, 86, 919–948. https://doi.org/10.1016/j.iref.2020.08.004
27. Hui, E. C. M., & Chan, K. K. K. (2012). Are the global real estate markets contagious? International Journal of Strategic Property Management, 16(3), 219–235. https://doi.org/10.3846/1648715X.2011.645904
28. Jensen, G. R., Johnson, R. R., & Mercer, J. M. (2000). Effi cient use of commodity futures in diversifi ed portfolios. Journal of Futures Markets, 20, 489–506. https://doi.org/10.1002/(SICI).1096-9934(200005).20:5<489::AID-FUT5>3.0.CO;2-A
29. Ji, Q., & Fan, Y. (2012). How does oil price volatility aff ect non-energy commodity markets? Applied Energy, 89(1), 273–280. https://doi.org/10.1016/j.apenergy.2011.07.038
30. Kang, W., Tang, K., & Wang, N. (2023). Financialization of commodity markets ten years later. Journal of Commodity Markets, 30, 100313. https://doi.org/10.1016/j.jcomm.2023.100313
31. Marsiglio, S., Bucci, A., La Torre, D., & Liuzzi D. (2019). Financial contagion and economic development: an epidemiological approach. Journal of Economic Behavior & Organization, 162, 211–228. http://dx.doi.org/10.1016/j.jebo.2018.12.018
32. Nepp, A., Karpeko, F. (2022). Hype as a Factor on the Global Market: The Case of Bitcoin. Journal of Behavioral Finance, 25(1), 1–14. https://doi.org/10.1080/15427560.2022.2073593.
33. Nepp, A., Okhrin, O., Egorova, J., Dzhuraeva, Z., Zykov, A. (2022). What threatens stock markets more — The coronavirus or the hype around it? International Review of Economics & Finance, 78, 519–539. https://doi.org/10.1016/j.iref.2021.12.007
34. Roy, R. P., & Roy, S. S. (2017). Financial contagion and volatility spillover: An exploration into Indian commodity derivative market. Economic Modelling, 67, 368–380. https://doi.org/10.1016/j.econmod.2017.02.019
35. Silvennoinen, A., & Thorp, S. (2013). Financialization, crisis and commodity correlation dynamics, Journal of International Financial Markets, Institutions and Money, 24, 42–65. https://doi.org/10.1016/j.intfin.2012.11.007
36. Tang, K., & Xiong, W. (2012). Index investment and the fi nancialization of commodities. Financial Analysts Journal, 68 (6), 54–74. https://doi.org/10.2469/faj.v68.n6.5
37. Xue, J. Y., Hsiao, C. Y. -L., Li, P., & Chui, C. M. (2024). Higher-order contagion eff ects in Russian fuel export markets: Evidence from COVID-19 pandemic and Russia-Ukraine war. Energy Strategy Reviews, 53, 101419. https://doi.org/10.1016/j.esr.2024.101419
38. Ye, W., Zhu, Y., Wu, Y., & Miao, B. (2016). Markov regime-switching quantile regression models and fi nancial contagion detection. Insurance: Mathematics and Economics, 67, 21–26. https://doi.org/10.1016/j.insmatheco.2015.11.002
39. Zhu, Z., Ji Q., Sun, L., & Zhai, P. (2020). Oil price shocks, investor sentiment, and asset pricing anomalies in the oil and gas industry. International Review of Financial Analysis, 70, 101516. https://doi.org/10.1016/j.irfa.2020.101516
40.
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For citations:
Malkina M.Yu. Financial contagion of commodity markets from energy markets during the pandemic, energy crisis and SMO. Moscow University Economics Bulletin. 2024;(5):3-28. (In Russ.) https://doi.org/10.55959/MSU0130-0105-6-59-5-1