IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v55y2020i4d10.1007_s10614-018-9857-y.html
   My bibliography  Save this article

Dynamic Correlation and Risk Contagion Between “Black” Futures in China: A Multi-scale Variational Mode Decomposition Approach

Author

Listed:
  • Qunwei Wang

    (Nanjing University of Aeronautics and Astronautics
    Nanjing University of Aeronautics and Astronautics)

  • Xingyu Dai

    (Nanjing University of Aeronautics and Astronautics
    Nanjing University of Aeronautics and Astronautics)

  • Dequn Zhou

    (Nanjing University of Aeronautics and Astronautics
    Nanjing University of Aeronautics and Astronautics)

Abstract

This paper explores the dynamic correlation and risk contagion between “black” futures in China at various time horizons. We employ the DCC-GARCH-t model and Granger causality in risk test jointly with variational modal decomposition. Our study covers the period from October 2013, to January 2018. The paper’s three key findings are as follows: first, a positive dynamic correlation exists between “black” futures across most sample period at each time scale. Secondly, dynamic correlation differs between “black” futures, which is largest during the medium-term time scale. What’s more, the correlation of coking coal futures and coke futures is consistently higher than other pairs at each time scale. Thirdly, the direction and the time lag of risk contagion varies across different time scales. The complexity of contagion will increase as the length of the time scale increases. We have also discovered some synchronic contagions between “black” futures.

Suggested Citation

  • Qunwei Wang & Xingyu Dai & Dequn Zhou, 2020. "Dynamic Correlation and Risk Contagion Between “Black” Futures in China: A Multi-scale Variational Mode Decomposition Approach," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1117-1150, April.
    • Handle: RePEc:kap:compec:v:55:y:2020:i:4:d:10.1007_s10614-018-9857-y
    DOI: 10.1007/s10614-018-9857-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-018-9857-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-018-9857-y?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. Khalfaoui, Rabeh, 2018. "Oil–gold time varying nexus: A time–frequency analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 86-104.
    2. Jiang, Yonghong & Nie, He & Monginsidi, Joe Yohanes, 2017. "Co-movement of ASEAN stock markets: New evidence from wavelet and VMD-based copula tests," Economic Modelling, Elsevier, vol. 64(C), pages 384-398.
    3. Vacha, Lukas & Barunik, Jozef, 2012. "Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis," Energy Economics, Elsevier, vol. 34(1), pages 241-247.
    4. Antonakakis, Nikolaos & Floros, Christos & Kizys, Renatas, 2016. "Dynamic spillover effects in futures markets: UK and US evidence," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 406-418.
    5. Zhang, Bing & Li, Xiao-Ming, 2016. "Recent hikes in oil-equity market correlations: Transitory or permanent?," Energy Economics, Elsevier, vol. 53(C), pages 305-315.
    6. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2013. "Conditional correlations and volatility spillovers between crude oil and stock index returns," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 116-138.
    7. Afanasyev, Dmitriy O. & Fedorova, Elena A. & Popov, Viktor U., 2015. "Fine structure of the price–demand relationship in the electricity market: Multi-scale correlation analysis," Energy Economics, Elsevier, vol. 51(C), pages 215-226.
    8. Jammazi, Rania, 2012. "Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach," Energy, Elsevier, vol. 37(1), pages 430-454.
    9. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.
    10. Huang, Shian-Chang, 2011. "Wavelet-based multi-resolution GARCH model for financial spillover effects," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(11), pages 2529-2539.
    11. Liu, Xueyong & An, Haizhong & Huang, Shupei & Wen, Shaobo, 2017. "The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 374-383.
    12. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    13. Lanza, Alessandro & Manera, Matteo & McAleer, Michael, 2006. "Modeling dynamic conditional correlations in WTI oil forward and futures returns," Finance Research Letters, Elsevier, vol. 3(2), pages 114-132, June.
    14. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Al-Yahyaee, Khamis Hamed & Shahbaz, Muhammad, 2017. "Oil and foreign exchange market tail dependence and risk spillovers for MENA, emerging and developed countries: VMD decomposition based copulas," Energy Economics, Elsevier, vol. 67(C), pages 476-495.
    15. Yu, Lean & Li, Jingjing & Tang, Ling & Wang, Shuai, 2015. "Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach," Energy Economics, Elsevier, vol. 51(C), pages 300-311.
    16. Mingyuan Guo & Xu Wang, 2016. "The dependence structure in volatility between Shanghai and Shenzhen stock market in China," China Finance Review International, Emerald Group Publishing Limited, vol. 6(3), pages 264-283, August.
    17. 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.
    18. Shahzad, Syed Jawad Hussain & Kumar, Ronald Ravinesh & Ali, Sajid & Ameer, Saba, 2016. "Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 8-33.
    19. Khalfaoui, R. & Boutahar, M. & Boubaker, H., 2015. "Analyzing volatility spillovers and hedging between oil and stock markets: Evidence from wavelet analysis," Energy Economics, Elsevier, vol. 49(C), pages 540-549.
    20. Du, Limin & He, Yanan, 2015. "Extreme risk spillovers between crude oil and stock markets," Energy Economics, Elsevier, vol. 51(C), pages 455-465.
    21. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    22. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Stanley, H. Eugene, 2016. "Extreme risk spillover effects in world gold markets and the global financial crisis," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 55-77.
    23. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2017. "Wavelet-based test of co-movement and causality between oil and renewable energy stock prices," Energy Economics, Elsevier, vol. 61(C), pages 241-252.
    24. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    25. Naccache, Théo, 2011. "Oil price cycles and wavelets," Energy Economics, Elsevier, vol. 33(2), pages 338-352, March.
    26. Roy, Rudra Prosad & Sinha Roy, Saikat, 2017. "Financial contagion and volatility spillover: An exploration into Indian commodity derivative market," Economic Modelling, Elsevier, vol. 67(C), pages 368-380.
    27. Benhmad, François, 2013. "Dynamic cyclical comovements between oil prices and US GDP: A wavelet perspective," Energy Policy, Elsevier, vol. 57(C), pages 141-151.
    28. Beckmann, Joscha & Czudaj, Robert, 2014. "Volatility transmission in agricultural futures markets," Economic Modelling, Elsevier, vol. 36(C), pages 541-546.
    29. Hong, Yongmiao, 2001. "A test for volatility spillover with application to exchange rates," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 183-224, July.
    30. Madaleno, Mara & Pinho, Carlos, 2014. "Wavelet dynamics for oil-stock world interactions," Energy Economics, Elsevier, vol. 45(C), pages 120-133.
    31. Shahzad, Syed Jawad Hussain & Nor, Safwan Mohd & Kumar, Ronald Ravinesh & Mensi, Walid, 2017. "Interdependence and contagion among industry-level US credit markets: An application of wavelet and VMD based copula approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 310-324.
    32. Balboa, Marina & López-Espinosa, Germán & Rubia, Antonio, 2015. "Granger causality and systemic risk," Finance Research Letters, Elsevier, vol. 15(C), pages 49-58.
    33. Raza, Naveed & Ali, Sajid & Shahzad, Syed Jawad Hussain & Raza, Syed Ali, 2018. "Do commodities effectively hedge real estate risk? A multi-scale asymmetric DCC approach," Resources Policy, Elsevier, vol. 57(C), pages 10-29.
    34. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    35. Tao, Juan & Green, Christopher J., 2012. "Asymmetries, causality and correlation between FTSE100 spot and futures: A DCC-TGARCH-M analysis," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 26-37.
    36. Pan, Zhiyuan & Wang, Yudong & Liu, Li, 2016. "The relationships between petroleum and stock returns: An asymmetric dynamic equi-correlation approach," Energy Economics, Elsevier, vol. 56(C), pages 453-463.
    37. Zhang, Yue-Jun & Fan, Ying & Tsai, Hsien-Tang & Wei, Yi-Ming, 2008. "Spillover effect of US dollar exchange rate on oil prices," Journal of Policy Modeling, Elsevier, vol. 30(6), pages 973-991.
    38. Ben-Salha, Ousama & Hkiri, Besma & Aloui, Chaker, 2018. "Sectoral energy consumption by source and output in the U.S.: New evidence from wavelet-based approach," Energy Economics, Elsevier, vol. 72(C), pages 75-96.
    39. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    40. He, Ling-Yun & Chen, Shu-Peng, 2011. "Nonlinear bivariate dependency of price–volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 297-308.
    41. Jia, Xiaoliang & An, Haizhong & Fang, Wei & Sun, Xiaoqi & Huang, Xuan, 2015. "How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective," Energy Economics, Elsevier, vol. 49(C), pages 588-598.
    42. de Araújo, André da Silva & Garcia, Maria Teresa Medeiros, 2013. "Risk contagion in the north-western and southern European stock markets," Journal of Economics and Business, Elsevier, vol. 69(C), pages 1-34.
    43. François Benhmad, 2012. "Modeling Nonlinear Granger Causality between the Oil price and U.S Dollar," Post-Print hal-03062497, HAL.
    44. Boubaker, Heni & Raza, Syed Ali, 2017. "A wavelet analysis of mean and volatility spillovers between oil and BRICS stock markets," Energy Economics, Elsevier, vol. 64(C), pages 105-117.
    45. Liu, Xiangli & Cheng, Siwei & Wang, Shouyang & Hong, Yongmiao & Li, Yi, 2008. "An empirical study on information spillover effects between the Chinese copper futures market and spot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 899-914.
    46. Reboredo, Juan Carlos & Rivera-Castro, Miguel A. & Zebende, Gilney F., 2014. "Oil and US dollar exchange rate dependence: A detrended cross-correlation approach," Energy Economics, Elsevier, vol. 42(C), pages 132-139.
    47. Geng, Jiang-Bo & Ji, Qiang & Fan, Ying, 2017. "The relationship between regional natural gas markets and crude oil markets from a multi-scale nonlinear Granger causality perspective," Energy Economics, Elsevier, vol. 67(C), pages 98-110.
    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. Ruiwen Yang & Pathairat Pastpipatkul & Chaiwat Nimanussornkul, 2020. "Dynamic Volatility Spillover Among Chinese Black Series Futures Under Structural Breaks," International Journal of Business and Administrative Studies, Professor Dr. Bahaudin G. Mujtaba, vol. 6(5), pages 236-246.
    2. Zhao, Yi & Dai, Xingyu & Zhang, Dongna & Wang, Qunwei & Cao, Yaru, 2023. "Do weather conditions drive China's carbon-coal-electricity markets systemic risk? A multi-timescale analysis," Finance Research Letters, Elsevier, vol. 51(C).
    3. Miao, Xiaoyu & Wang, Qunwei & Dai, Xingyu, 2022. "Is oil-gas price decoupling happening in China? A multi-scale quantile-on-quantile approach," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 450-470.
    4. Huang, Yumeng & Dai, Xingyu & Wang, Qunwei & Zhou, Dequn, 2021. "A hybrid model for carbon price forecastingusing GARCH and long short-term memory network," Applied Energy, Elsevier, vol. 285(C).
    5. Dai, Xingyu & Xiao, Ling & Wang, Qunwei & Dhesi, Gurjeet, 2021. "Multiscale interplay of higher-order moments between the carbon and energy markets during Phase III of the EU ETS," Energy Policy, Elsevier, vol. 156(C).
    6. Shi, Yangyan & Feng, Yu & Zhang, Qi & Shuai, Jing & Niu, Jiangxin, 2023. "Does China's new energy vehicles supply chain stock market have risk spillovers? Evidence from raw material price effect on lithium batteries," Energy, Elsevier, vol. 262(PA).
    7. Wang, Qunwei & Liu, Mengmeng & Xiao, Ling & Dai, Xingyu & Li, Matthew C. & Wu, Fei, 2022. "Conditional sovereign CDS in market basket risk scenario: A dynamic vine-copula analysis," International Review of Financial Analysis, Elsevier, vol. 80(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. Belhassine, Olfa & Karamti, Chiraz, 2021. "Volatility spillovers and hedging effectiveness between oil and stock markets: Evidence from a wavelet-based and structural breaks analysis," Energy Economics, Elsevier, vol. 102(C).
    2. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Stanley, H. Eugene, 2016. "Extreme risk spillover effects in world gold markets and the global financial crisis," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 55-77.
    3. Dai, Xingyu & Wang, Qunwei & Zha, Donglan & Zhou, Dequn, 2020. "Multi-scale dependence structure and risk contagion between oil, gold, and US exchange rate: A wavelet-based vine-copula approach," Energy Economics, Elsevier, vol. 88(C).
    4. Dimitrios Kartsonakis-Mademlis & Nikolaos Dritsakis, 2020. "Does the Choice of the Multivariate GARCH Model on Volatility Spillovers Matter? Evidence from Oil Prices and Stock Markets in G7 Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 164-182.
    5. Qing Peng & Fenghua Wen & Xu Gong, 2021. "Time‐dependent intrinsic correlation analysis of crude oil and the US dollar based on CEEMDAN," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 834-848, January.
    6. Hassan, Kamrul & Hoque, Ariful & Gasbarro, Dominic, 2019. "Separating BRIC using Islamic stocks and crude oil: dynamic conditional correlation and volatility spillover analysis," Energy Economics, Elsevier, vol. 80(C), pages 950-969.
    7. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    8. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    9. Yue-Jun Zhang & Shu-Hui Li, 2019. "The impact of investor sentiment on crude oil market risks: evidence from the wavelet approach," Quantitative Finance, Taylor & Francis Journals, vol. 19(8), pages 1357-1371, August.
    10. de Araújo, André da Silva & Garcia, Maria Teresa Medeiros, 2013. "Risk contagion in the north-western and southern European stock markets," Journal of Economics and Business, Elsevier, vol. 69(C), pages 1-34.
    11. Wang, Xinya & Lucey, Brian & Huang, Shupei, 2022. "Can gold hedge against oil price movements: Evidence from GARCH-EVT wavelet modeling," Journal of Commodity Markets, Elsevier, vol. 27(C).
    12. Das, Suman & Roy, Saikat Sinha, 2023. "Following the leaders? A study of co-movement and volatility spillover in BRICS currencies," Economic Systems, Elsevier, vol. 47(2).
    13. Mensi, Walid & Beljid, Makram & Boubaker, Adel & Managi, Shunsuke, 2013. "Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold," Economic Modelling, Elsevier, vol. 32(C), pages 15-22.
    14. Zhenhua Liu & Zhihua Ding & Rui Li & Xin Jiang & JyS. Wu & Tao Lv, 2017. "Research on differences of spillover effects between international crude oil price and stock markets in China and America," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(1), pages 575-590, August.
    15. Chen, Xiangyu & Tongurai, Jittima, 2022. "Spillovers and interdependency across base metals: Evidence from China's futures and spot markets," Resources Policy, Elsevier, vol. 75(C).
    16. Sun, Xiaolei & Chen, Xiuwen & Wang, Jun & Li, Jianping, 2020. "Multi-scale interactions between economic policy uncertainty and oil prices in time-frequency domains," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    17. Jiang, Yonghong & Jiang, Cheng & Nie, He & Mo, Bin, 2019. "The time-varying linkages between global oil market and China's commodity sectors: Evidence from DCC-GJR-GARCH analyses," Energy, Elsevier, vol. 166(C), pages 577-586.
    18. repec:ipg:wpaper:2014-456 is not listed on IDEAS
    19. Kim Hiang Liow & Xiaoxia Zhou & Qiang Li & Yuting Huang, 2019. "Time–Scale Relationship between Securitized Real Estate and Local Stock Markets: Some Wavelet Evidence," JRFM, MDPI, vol. 12(1), pages 1-23, January.
    20. Turhan, M. Ibrahim & Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "A comparative analysis of the dynamic relationship between oil prices and exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 397-414.
    21. Zheng, Biao & Zhang, Yuquan W. & Qu, Fang & Geng, Yong & Yu, Haishan, 2022. "Do rare earths drive volatility spillover in crude oil, renewable energy, and high-technology markets? — A wavelet-based BEKK- GARCH-X approach," Energy, Elsevier, vol. 251(C).

    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:kap:compec:v:55:y:2020:i:4:d:10.1007_s10614-018-9857-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.