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A wavelet-based methodology to compare the impact of pandemic versus Russia–Ukraine conflict on crude oil sector and its interconnectedness with other energy and non-energy markets

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  • Roy, Archi
  • Soni, Anchal
  • Deb, Soudeep

Abstract

We address the important question of whether the COVID-19 pandemic and the Russia–Ukraine conflict have the same economic impact. Our study focuses on a comparative analysis of the crude oil markets with other energy and non-energy markets in terms of market efficiency and interconnectedness during the two crises. We deploy a novel methodology that utilizes the wavelet decomposition of time series, which facilitates capturing of information in both time and frequency domain, to evaluate the market efficiency. Subsequently, the wavelet coherence, along with a vector-valued GARCH model applied on the wavelet details, help us in quantifying the interconnectedness and spillover dynamics between different markets. Our analysis suggests that the energy sector is impacted more than the non-energy sector in times of both the crises, however the nature of the impact is different for different energy markets. Brent crude oil suffers more during the Russia–Ukraine war than during the pandemic, while natural gas suffers more during the pandemic than the war and WTI suffers equally during both the crises. We also report increased interconnectedness between markets during the pandemic and the war. This information would help investors to choose a safe market and plan their portfolio accordingly in a crisis period.

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  • Roy, Archi & Soni, Anchal & Deb, Soudeep, 2023. "A wavelet-based methodology to compare the impact of pandemic versus Russia–Ukraine conflict on crude oil sector and its interconnectedness with other energy and non-energy markets," Energy Economics, Elsevier, vol. 124(C).
  • Handle: RePEc:eee:eneeco:v:124:y:2023:i:c:s0140988323003286
    DOI: 10.1016/j.eneco.2023.106830
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    as
    1. Gharib, Cheima & Mefteh-Wali, Salma & Jabeur, Sami Ben, 2021. "The bubble contagion effect of COVID-19 outbreak: Evidence from crude oil and gold markets," Finance Research Letters, Elsevier, vol. 38(C).
    2. Baumöhl, Eduard & Kočenda, Evžen & Lyócsa, Štefan & Výrost, Tomáš, 2018. "Networks of volatility spillovers among stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1555-1574.
    3. Giovanni Valensisi, 2020. "COVID-19 and Global Poverty: Are LDCs Being Left Behind?," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 32(5), pages 1535-1557, December.
    4. Jarno Kiviaho & Jussi Nikkinen & Vanja Piljak & Timo Rothovius, 2014. "The Co†movement Dynamics of European Frontier Stock Markets," European Financial Management, European Financial Management Association, vol. 20(3), pages 574-595, June.
    5. Karali, Berna & Ramirez, Octavio A., 2014. "Macro determinants of volatility and volatility spillover in energy markets," Energy Economics, Elsevier, vol. 46(C), pages 413-421.
    6. Yıldırım, Durmuş Çağrı & Cevik, Emrah Ismail & Esen, Ömer, 2020. "Time-varying volatility spillovers between oil prices and precious metal prices," Resources Policy, Elsevier, vol. 68(C).
    7. Escanciano, J. Carlos & Lobato, Ignacio N., 2009. "An automatic Portmanteau test for serial correlation," Journal of Econometrics, Elsevier, vol. 151(2), pages 140-149, August.
    8. Okoroafor, Ugochi Chibuzor & Leirvik, Thomas, 2022. "Time varying market efficiency in the Brent and WTI crude market," Finance Research Letters, Elsevier, vol. 45(C).
    9. Cai, Yifei & Wu, Yanrui, 2021. "Time-varying interactions between geopolitical risks and renewable energy consumption," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 116-137.
    10. Francesco Guidi & Rakesh Gupta, 2013. "Market efficiency in the ASEAN region: evidence from multivariate and cointegration tests," Applied Financial Economics, Taylor & Francis Journals, vol. 23(4), pages 265-274, February.
    11. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    12. Kam C. Chan & Benton E. Gup & Ming-Shiun Pan, 1997. "International Stock Market Efficiency and Integration: A Study of Eighteen Nations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 24(6), pages 803-813.
    13. Lu, Feng-bin & Hong, Yong-miao & Wang, Shou-yang & Lai, Kin-keung & Liu, John, 2014. "Time-varying Granger causality tests for applications in global crude oil markets," Energy Economics, Elsevier, vol. 42(C), pages 289-298.
    14. Elsayed, Ahmed H. & Gozgor, Giray & Lau, Chi Keung Marco, 2022. "Risk transmissions between bitcoin and traditional financial assets during the COVID-19 era: The role of global uncertainties," International Review of Financial Analysis, Elsevier, vol. 81(C).
    15. Hong, Yongmiao, 1996. "Consistent Testing for Serial Correlation of Unknown Form," Econometrica, Econometric Society, vol. 64(4), pages 837-864, July.
    16. James J. Angel & Lawrence E. Harris & Chester S. Spatt, 2011. "Equity Trading in the 21stCentury," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 1-53.
    17. Muller, Ulrich A. & Dacorogna, Michel M. & Dave, Rakhal D. & Olsen, Richard B. & Pictet, Olivier V. & von Weizsacker, Jacob E., 1997. "Volatilities of different time resolutions -- Analyzing the dynamics of market components," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 213-239, June.
    18. Kam C. Chan & Benton E. Gup & Ming‐Shiun Pan, 1997. "International Stock Market Efficiency and Integration: A Study of Eighteen Nations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 24(6), pages 803-813, July.
    19. Liu, Tangyong & Gong, Xu, 2020. "Analyzing time-varying volatility spillovers between the crude oil markets using a new method," Energy Economics, Elsevier, vol. 87(C).
    20. Hakkio, Craig S. & Rush, Mark, 1989. "Market efficiency and cointegration: an application to the sterling and deutschemark exchange markets," Journal of International Money and Finance, Elsevier, vol. 8(1), pages 75-88, March.
    21. Smith, Jason, 2014. "Does the market matter for more than investment?," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 52-61.
    22. Rua, António & Nunes, Luís C., 2009. "International comovement of stock market returns: A wavelet analysis," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 632-639, September.
    23. Abdulnasser Hatemi-J, 2012. "Asymmetric causality tests with an application," Empirical Economics, Springer, vol. 43(1), pages 447-456, August.
    24. Tiwari, Aviral Kumar & Cunado, Juncal & Gupta, Rangan & Wohar, Mark E., 2018. "Volatility spillovers across global asset classes: Evidence from time and frequency domains," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 194-202.
    25. Shehzad, Khurram & Xiaoxing, Liu & Kazouz, Hayfa, 2020. "COVID-19’s disasters are perilous than Global Financial Crisis: A rumor or fact?," Finance Research Letters, Elsevier, vol. 36(C).
    26. Gong, Xu & Liu, Yun & Wang, Xiong, 2021. "Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method," International Review of Financial Analysis, Elsevier, vol. 76(C).
    27. Lobato, I.N. & Nankervis, John C. & Savin, N.E., 2002. "Testing For Zero Autocorrelation In The Presence Of Statistical Dependence," Econometric Theory, Cambridge University Press, vol. 18(3), pages 730-743, June.
    28. Bradley Ewing & Cynthia Lay Harter, 2000. "Co-movements of Alaska North Slope and UK Brent crude oil prices," Applied Economics Letters, Taylor & Francis Journals, vol. 7(8), pages 553-558.
    29. Mengya Liu & Fukang Zhu & Ke Zhu, 2022. "Multifrequency-Band Tests for White Noise Under Heteroscedasticity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 799-814, April.
    30. GIRAITIS, Liudas & KOKOSZKA, Piotr & LEIPUS, Remigijus & TEYSSIÈRE, Gilles, 2003. "Rescaled variance and related tests for long memory in volatility and levels," LIDAM Reprints CORE 1594, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    31. Md. Kausar Alam & Mosab I. Tabash & Mabruk Billah & Sanjeev Kumar & Suhaib Anagreh, 2022. "The Impacts of the Russia–Ukraine Invasion on Global Markets and Commodities: A Dynamic Connectedness among G7 and BRIC Markets," JRFM, MDPI, vol. 15(8), pages 1-20, August.
    32. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    33. Cui, Lianbiao & Weng, Shimei & Kirikkaleli, Dervis & Bashir, Muhammad Adnan & Rjoub, Husam & Zhou, Yuanxiang, 2021. "Exploring the role of natural resources, natural gas and oil production for economic growth of China," Resources Policy, Elsevier, vol. 74(C).
    34. Hasan, Md. Bokhtiar & Hassan, M. Kabir & Rashid, Md. Mamunur & Alhenawi, Yasser, 2021. "Are safe haven assets really safe during the 2008 global financial crisis and COVID-19 pandemic?," Global Finance Journal, Elsevier, vol. 50(C).
    35. Su, Chi-Wei & Khan, Khalid & Umar, Muhammad & Zhang, Weike, 2021. "Does renewable energy redefine geopolitical risks?," Energy Policy, Elsevier, vol. 158(C).
    36. Zhuang, Xiaoyang & Wei, Dan, 2022. "Asymmetric multifractality, comparative efficiency analysis of green finance markets: A dynamic study by index-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    37. Nikolaos A. Kyriazis, 2019. "A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets," JRFM, MDPI, vol. 12(4), pages 1-17, November.
    38. Rosenberg, Barr & Rudd, Andrew, 1982. "Factor-Related and Specific Returns of Common Stocks: Serial Correlation and Market Inefficiency," Journal of Finance, American Finance Association, vol. 37(2), pages 543-554, May.
    39. Huang, Jianbai & Ding, Qian & Zhang, Hongwei & Guo, Yaoqi & Suleman, Muhammad Tahir, 2021. "Nonlinear dynamic correlation between geopolitical risk and oil prices: A study based on high-frequency data," Research in International Business and Finance, Elsevier, vol. 56(C).
    40. Jan Bentzen, 2007. "Does OPEC influence crude oil prices? Testing for co-movements and causality between regional crude oil prices," Applied Economics, Taylor & Francis Journals, vol. 39(11), pages 1375-1385.
    41. Boubaker, Sabri & Goodell, John W. & Pandey, Dharen Kumar & Kumari, Vineeta, 2022. "Heterogeneous impacts of wars on global equity markets: Evidence from the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 48(C).
    42. de Jong, Robert M., 1997. "Central Limit Theorems for Dependent Heterogeneous Random Variables," Econometric Theory, Cambridge University Press, vol. 13(3), pages 353-367, June.
    43. Bravo Caro, José Manuel & Golpe, Antonio A. & Iglesias, Jesús & Vides, José Carlos, 2020. "A new way of measuring the WTI – Brent spread. Globalization, shock persistence and common trends," Energy Economics, Elsevier, vol. 85(C).
    44. Gençay, Ramazan & Signori, Daniele, 2015. "Multi-scale tests for serial correlation," Journal of Econometrics, Elsevier, vol. 184(1), pages 62-80.
    45. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    46. Li, Meiyu & Gençay, Ramazan, 2017. "Tests for serial correlation of unknown form in dynamic least squares regression with wavelets," Economics Letters, Elsevier, vol. 155(C), pages 104-110.
    47. Yu, Yang & Guo, SongLin & Chang, XiaoChen, 2022. "Oil prices volatility and economic performance during COVID-19 and financial crises of 2007–2008," Resources Policy, Elsevier, vol. 75(C).
    48. Panagiotis Mantalos & Ghazi Shukur, 2010. "The effect of spillover on the Granger causality test," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(9), pages 1473-1486.
    49. Cheima Gharib & Salma Mefteh-Wali & Vanessa Serret & Sami Ben Jabeur, 2021. "Impact of COVID-19 pandemic on crude oil prices: Evidence from Econophysics approach," Post-Print hal-03375164, HAL.
    50. Mensi, Walid & Sensoy, Ahmet & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices," Resources Policy, Elsevier, vol. 69(C).
    51. Das, Debojyoti & Kannadhasan, M. & Al-Yahyaee, Khamis Hamed & Yoon, Seong-Min, 2018. "A wavelet analysis of co-movements in Asian gold markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 192-206.
    52. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Yaya, OlaOluwa S. & Al-Faryan, Mamdouh Abdulaziz Saleh, 2022. "Does oil connect differently with prominent assets during war? Analysis of intra-day data during the Russia-Ukraine saga," Resources Policy, Elsevier, vol. 77(C).
    53. van Dijk, Dick & Osborn, Denise R. & Sensier, Marianne, 2005. "Testing for causality in variance in the presence of breaks," Economics Letters, Elsevier, vol. 89(2), pages 193-199, November.
    54. Fang, Yi & Shao, Zhiquan, 2022. "The Russia-Ukraine conflict and volatility risk of commodity markets," Finance Research Letters, Elsevier, vol. 50(C).
    55. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    56. Umar, Muhammad & Riaz, Yasir & Yousaf, Imran, 2022. "Impact of Russian-Ukraine war on clean energy, conventional energy, and metal markets: Evidence from event study approach," Resources Policy, Elsevier, vol. 79(C).
    57. Kumar, Anoop S. & Anandarao, S., 2019. "Volatility spillover in crypto-currency markets: Some evidences from GARCH and wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 448-458.
    58. Efstathios Paparoditis, 2000. "Spectral Density Based Goodness‐of‐Fit Tests for Time Series Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(1), pages 143-176, March.
    59. Wang, Jingjing & Wang, Xiaoyang, 2021. "COVID-19 and financial market efficiency: Evidence from an entropy-based analysis," Finance Research Letters, Elsevier, vol. 42(C).
    60. Wang, Yihan & Bouri, Elie & Fareed, Zeeshan & Dai, Yuhui, 2022. "Geopolitical risk and the systemic risk in the commodity markets under the war in Ukraine," Finance Research Letters, Elsevier, vol. 49(C).
    61. 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.
    62. Duchesne, Pierre, 2006. "On Testing For Serial Correlation With A Wavelet-Based Spectral Density Estimator In Multivariate Time Series," Econometric Theory, Cambridge University Press, vol. 22(4), pages 633-676, August.
    63. Le, Thai-Ha & Le, Anh Tu & Le, Ha-Chi, 2021. "The historic oil price fluctuation during the Covid-19 pandemic: What are the causes?," Research in International Business and Finance, Elsevier, vol. 58(C).
    64. Gençay, Ramazan & Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon J., 2001. "An Introduction to Wavelets and Other Filtering Methods in Finance and Economics," Elsevier Monographs, Elsevier, edition 1, number 9780122796708.
    65. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    66. Shahzad, Syed Jawad Hussain & Naeem, Muhammad Abubakr & Peng, Zhe & Bouri, Elie, 2021. "Asymmetric volatility spillover among Chinese sectors during COVID-19," International Review of Financial Analysis, Elsevier, vol. 75(C).
    67. Gu, Anthony Yanxiang & Finnerty, Joseph, 2002. "The Evolution of Market Efficiency: 103 Years Daily Data of the Dow," Review of Quantitative Finance and Accounting, Springer, vol. 18(3), pages 219-237, May.
    68. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    69. DIMA, Bogdan & DIMA, Ştefana Maria & IOAN, Roxana, 2021. "Remarks on the behaviour of financial market efficiency during the COVID-19 pandemic. The case of VIX," Finance Research Letters, Elsevier, vol. 43(C).
    70. Robert J. Weiner, 1991. "Is the World Oil Market "One Great Pool"?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 95-108.
    71. Hafner, Christian M. & Herwartz, Helmut, 2006. "A Lagrange multiplier test for causality in variance," Economics Letters, Elsevier, vol. 93(1), pages 137-141, October.
    72. Yongmiao Hong & Chihwa Kao, 2004. "Wavelet-Based Testing for Serial Correlation of Unknown Form in Panel Models," Econometrica, Econometric Society, vol. 72(5), pages 1519-1563, September.
    73. Ji, Qiang & Zhang, Dayong & Zhao, Yuqian, 2020. "Searching for safe-haven assets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 71(C).
    74. Gharib, Cheima & Mefteh-Wali, Salma & Serret, Vanessa & Ben Jabeur, Sami, 2021. "Impact of COVID-19 pandemic on crude oil prices: Evidence from Econophysics approach," Resources Policy, Elsevier, vol. 74(C).
    75. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
    76. He, Yanan & Wang, Shouyang & Lai, Kin Keung, 2010. "Global economic activity and crude oil prices: A cointegration analysis," Energy Economics, Elsevier, vol. 32(4), pages 868-876, July.
    77. Tanin, Tauhidul Islam & Sarker, Ashutosh & Brooks, Robert & Do, Hung Xuan, 2022. "Does oil impact gold during COVID-19 and three other recent crises?," Energy Economics, Elsevier, vol. 108(C).
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    Keywords

    Coherence; Efficient market hypothesis; Spillover dynamics; Volatility spillover; Wavelet analysis;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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