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Küresel Sektörel Endeksler Arasındaki Dinamik Bağlantılılık ve Risk Aktarımı: COVID-19 ve Rusya-Ukrayna Savaşından Bulgular

Year 2025, Volume: 7 Issue: 2, 154 - 172, 31.12.2025

Abstract

Bu çalışmada Covid-19 pandemisi ve Rusya-Ukrayna savaşı döneminde küresel sektörel endeksler arasındaki dinamik ilişkiler ve oynaklık etkileşimleri araştırılmıştır. Her iki kriz döneminde sektörel endeksler arasındaki bağlantılılık ilişkisinde değişimler değerlendirilmiştir. MSCI ACWI endeksleri kapsamında yer alan finansal, malzeme, sanayi, sağlık, enerji, temel tüketim malları sektörleri ele alınarak TVP-VAR-SV modeli ile incelenmiştir. Sonuçlar hem pandemi hem de savaş döneminde küresel sektörel endeksler arasındaki bağlantılılıklarda önemli artışlar yaşandığını göstermektedir. Pandemi döneminde sağlık sektörü bağlantılılık yapısının merkezinde yer almış, diğer sektörler ile güçlü bağlantılılık ilişkisi geliştirmiştir. Savaş döneminde ise enerji sektörünün bağlantılılık ilişkisinin merkezinde yer almış; enerji sektörü ile sağlık, finansal ve sanayi sektörleri arasındaki etkileşim güçlenmiştir. Pandemi döneminde sağlık ve finans; savaş döneminde ise enerji ve malzeme sektörlerine yüksek volatilite artışları yaşanmıştır. Savaş döneminde finansal sektöründe kısa vadeli şoklar baskınken, enerji ve sağlık sektörlerinde savaşın ilk dönemlerinde kısa vadeli şoklar, ilerleyen dönemlerde yerini uzun vadeli kalıcı şoklara bırakmıştır. Zamanla değişen etki tepki analiz sonuçları, pandemi döneminde sağlık ve sanayi sektörlerinde kısa vadeli şokların, finansal ve temel tüketim malları sektörlerinde uzun vadeli etkilerin baskın olduğunu göstermektedir. Ayrıca bulgular, finansal sektörünün her iki kriz döneminde de risk aktarımındaki öncü rolünü vurgulamaktadır.

Ethical Statement

Bu çalışmanın, özgün bir çalışma olduğunu; çalışmanın hazırlık, veri toplama, analiz ve bilgilerin sunumu olmak üzere tüm aşamalarından bilimsel etik ilke ve kurallarına uygun davrandığımı; bu çalışma kapsamında elde edilmeyen tüm veri ve bilgiler için kaynak gösterdiğimi ve bu kaynaklara kaynakçada yer verdiğimi; kullanılan verilerde herhangi bir değişiklik yapmadığımı, çalışmanın Committee on Publication Ethics (COPE)' in tüm şartlarını ve koşullarını kabul ederek etik görev ve sorumluluklara riayet ettiğimi beyan ederim. Herhangi bir zamanda, çalışmayla ilgili yaptığım bu beyana aykırı bir durumun saptanması durumunda, ortaya çıkacak tüm ahlaki ve hukuki sonuçlara razı olduğumu bildiririm.

References

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  • Khan, S., Rehman, M. Z., Shahzad, M. R., Khan, N. U., & Abdul Razak, L. (2025). How prone are emerging markets' sectoral indices to global uncertainties? Evidence from the quantile connectedness approach with portfolio implications. International Journal of Emerging Markets, 20(4), 1569-1592. https://doi.org/10.3390/su142315908
  • Laborda, R., & Olmo, J. (2021). Volatility spillover between economic sectors in financial crisis prediction: Evidence spanning the great financial crisis and Covid-19 pandemic. Research in International Business and Finance, 57, 101402. https://doi.org/10.1016/j.ribaf.2021.101402
  • Leone, M., Manelli, A., & Pace, R. (2025). The Russia–Ukraine conflict and stock markets: Risk and spillovers. Risks, 13(7), 130. https://doi.org/10.3390/risks13070130
  • Liu, Y., Wei, Y., Wang, Q., & Liu, Y. (2022). International stock market risk contagion during the COVID-19 pandemic. Finance Research Letters, 45, 102145. https://doi.org/10.1016/j.frl.2021.102145
  • Mahran, H. A. (2023). The impact of the Russia–Ukraine conflict (2022) on volatility connectedness between the Egyptian stock market sectors: evidence from the DCC-GARCH-CONNECTEDNESS approach. The Journal of Risk Finance, 24(1), 105-121. https://doi.org/10.1108/JRF-06-2022-0163
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  • Obi, P., Waweru, F., & Nyangu, M. (2023). An event study on the reaction of equity and commodity markets to the onset of the Russia–Ukraine conflict. Journal of Risk and Financial Management, 16(5), 256. https://doi.org/10.3390/jrfm16050256
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Dynamic Connectedness and Risk Transmission Among Global Sectoral Indices: Findings from COVID-19 and the Russia-Ukraine War

Year 2025, Volume: 7 Issue: 2, 154 - 172, 31.12.2025

Abstract

This study explores the dynamic relationships and volatility spillovers among global sectoral indices during the Covid-19 pandemic and the Russia–Ukraine war. It evaluates changes in the connectedness of sectoral indices throughout both crisis periods. The finance, materials, industrials, health care, energy, and consumer staples sectors—represented by the MSCI ACWI indices—are analysed using the TVP-VAR-SV model. The findings reveal significant increases in cross-sectoral connectedness during both crises. During the pandemic, the health care sector was at the core of the connectedness network, exhibiting strong linkages with other sectors. Conversely, during the war, the energy sector assumed a central role, with intensified interactions particularly between the energy sector and the health care, financial, and industrials sectors. Marked increases in volatility were observed in the health care and financial sectors during the pandemic, and in the energy and materials sectors during the war. In the financial sector, short-term shocks predominated during the war, whereas in the energy and health care sectors, short-term shocks in the early phase gave way to long-term, persistent shocks later on. Over time, a changing impulse–response dynamic emerged: short-term effects dominated the health care and industrials sectors during the pandemic, while long-term impacts were more prevalent in the financial and consumer staples sectors. Furthermore, the results underscore the financial sector’s leading role in transmitting risk across sectors during both crisis periods.

Ethical Statement

I declare that this study is an original work; that I have adhered to scientific ethical principles and rules throughout all stages of the study, including preparation, data collection, analysis, and presentation of information; that I have cited all data and information not obtained within the scope of this study and included these sources in the bibliography; that I have not made any changes to the data used; and that I have accepted all terms and conditions of the Committee on Publication Ethics (COPE) and have complied with my ethical duties and responsibilities. I hereby declare that I consent to all ethical and legal consequences that may arise if, at any time, any violation of this declaration regarding the study is detected.

References

  • Aizenman, J., Lindahl, R., Stenvall, D., & Uddin, G. S. (2024). Geopolitical shocks and commodity market dynamics: New evidence from the Russia-Ukraine conflict. European Journal of Political Economy, 85, 102574. https://doi.org/10.1016/j.ejpoleco.2024.102574
  • Akhtaruzzaman, M., Boubaker, S., & Sensoy, A. (2021). Financial contagion during COVID–19 crisis. Finance research letters, 38, 101604. https://doi.org/10.1016/j.frl.2020.101604
  • Alam, M. K., Tabash, M. I., Billah, M., Kumar, S., & Anagreh, S. (2022). The impacts of the Russia–Ukraine invasion on global markets and commodities: A dynamic connectedness among G7 and BRIC markets. Journal of Risk and Financial Management, 15(8), 352. https://doi.org/10.3390/jrfm15080352
  • Almansour, B. Y., Elkrghli, S., Gaytan, J. C. T., & Mohnot, R. (2023). Interconnectedness dynamic spillover among US, Russian, and Ukrainian equity indices during the COVID-19 pandemic and the Russian–Ukrainian war. Heliyon, 9(12).
  • Anyikwa, I., & Phiri, A. (2023). Quantile connectedness amongst BRICS equity markets during the COVID-19 pandemic and Russia–Ukraine war. Cogent Economics & Finance, 11(2), 2251300. https://doi.org/10.1080/23322039.2023.2251300
  • Baqaee, D., & Farhi, E. (2022). Supply and demand in disaggregated Keynesian economies with an application to the Covid-19 crisis. American Economic Review, 112(5), 1397-1436.
  • Cavaglia, S., Brightman, C., & Aked, M. (2000). The increasing importance of industry factors. Financial Analysts Journal, 56(5), 41-54. https://doi.org/10.2469/faj.v56.n5.2389
  • Cheng, T., Liu, J., Yao, W., & Zhao, A. B. (2022). The impact of COVID-19 pandemic on the volatility connectedness network of global stock market. Pacific-Basin Finance Journal, 71, 101678. https://doi.org/10.1016/j.pacfin.2021.101678
  • Chirilă, V. (2022). Connectedness between sectors: the case of the polish stock market before and during COVID-19. Journal of Risk and Financial Management, 15(8), 322. https://doi.org/10.3390/jrfm15080322
  • Choi, S. Y. (2023). The dynamic network of industries in US stock market: Evidence of GFC, COVID-19 pandemic and Russia-Ukraine war. Heliyon, 9(9). https://doi.org/10.1016/j.heliyon.2023.e19726
  • Costa, A., Matos, P., & da Silva, C. (2022). Sectoral connectedness: New evidence from US stock market during COVID-19 pandemics. Finance Research Letters, 45, 102124. https://doi.org/10.1016/j.frl.2021.102124
  • Countryman, A. M., Litvinov, V., Kolodiazhnyi, I., Bogonos, M., & Nivievskyi, O. (2025). Global economic effects of war‐induced agricultural export declines from Ukraine. Applied Economic Perspectives and Policy, 47(2), 624-665. https://doi.org/10.1002/aepp.13468
  • del Rio-Chanona, R. M., Mealy, P., Pichler, A., Lafond, F., & Farmer, J. D. (2020). Supply and demand shocks in the COVID-19 pandemic: An industry and occupation perspective. Oxford Review of Economic Policy, 36(Supplement_1), 94-137.
  • Duncan, A. S., & Kabundi, A. (2013). Domestic and foreign sources of volatility spillover to South African asset classes. Economic Modelling, 31, 566-573. https://doi.org/10.1016/j.econmod.2012.11.016
  • Ekinci, R., & Gençyürek, A. G. (2021). Dynamic connectedness between sector indices: Evidence from Borsa Istanbul. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 16(2), 512-534.
  • Fernandez-Perez, A., Gilbert, A., Indriawan, I., & Nguyen, N. H. (2021). COVID-19 pandemic and stock market response: A culture effect. Journal of behavioral and experimental finance, 29, 100454.
  • Fitriyah, F., & Mukminatin, Z. N. (2025). Return connectedness of sectoral stock indices on the Indonesian stock exchange during Russian-Ukraine conflict. Journal of Accounting and Investment, 26(1), 155-172. DOI: https://doi.org/10.18196/jai.v26i1.22406
  • Frikha, W., Brahim, M., Jeribi, A., & Lahiani, A. (2023). COVID-19, Russia-Ukraine war and interconnectedness between stock and crypto markets: a wavelet-based analysis. Journal of Business Analytics, 6(4), 255-275. https://doi.org/10.1080/2573234X.2023.2193224
  • Ghorbel, A., Loukil, S., & Bahloul, W. (2024). Connectedness between cryptocurrencies, gold and stock markets in the presence of the COVID-19 pandemic. European Journal of Management and Business Economics, 33(4), 466-487. https://doi.org/10.1108/EJMBE-10-2021-0281
  • Gupta, R., & Basu, P. K. (2011). Does sector diversification benefit all markets?-analysis of Australian and Indian markets. The Asia Pacific Journal of Economics & Business, 15(1), 15.).
  • Ha, LT (2023). TVP-VAR genişletilmiş ortak bağlantılı yaklaşımını uygulayarak COVID-19 pandemisi sırasında kripto para ve borsa piyasalarının birbirine bağlanması. Ekonomi Çalışmaları Dergisi, 50 (3), 407-428. https://doi.org/10.1108/JES-01-2022-0055
  • İmre, S. (2021). Covid-19 pandemisinin seçili BİST sektör endeksleri üzerindeki etkisi. Journal of Management and Economics Research, 19(4), 335-348. http://dx.doi.org/10.11611/yead.984604
  • Jebabli, I., Arouri, M., & Teulon, F. (2014). On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVP-VAR models with stochastic volatility. Energy Economics, 45, 66-98. https://doi.org/10.1016/j.eneco.2014.06.008
  • Jiang, W., & Chen, Y. (2024). Impact of Russia-Ukraine conflict on the time-frequency and quantile connectedness between energy, metal and agricultural markets. Resources Policy, 88, 104376. https://doi.org/10.1016/j.resourpol.2023.104376
  • Khan, S., Rehman, M. Z., Shahzad, M. R., Khan, N. U., & Abdul Razak, L. (2025). How prone are emerging markets' sectoral indices to global uncertainties? Evidence from the quantile connectedness approach with portfolio implications. International Journal of Emerging Markets, 20(4), 1569-1592. https://doi.org/10.3390/su142315908
  • Laborda, R., & Olmo, J. (2021). Volatility spillover between economic sectors in financial crisis prediction: Evidence spanning the great financial crisis and Covid-19 pandemic. Research in International Business and Finance, 57, 101402. https://doi.org/10.1016/j.ribaf.2021.101402
  • Leone, M., Manelli, A., & Pace, R. (2025). The Russia–Ukraine conflict and stock markets: Risk and spillovers. Risks, 13(7), 130. https://doi.org/10.3390/risks13070130
  • Liu, Y., Wei, Y., Wang, Q., & Liu, Y. (2022). International stock market risk contagion during the COVID-19 pandemic. Finance Research Letters, 45, 102145. https://doi.org/10.1016/j.frl.2021.102145
  • Mahran, H. A. (2023). The impact of the Russia–Ukraine conflict (2022) on volatility connectedness between the Egyptian stock market sectors: evidence from the DCC-GARCH-CONNECTEDNESS approach. The Journal of Risk Finance, 24(1), 105-121. https://doi.org/10.1108/JRF-06-2022-0163
  • Maurya, P. K., Bansal, R., & Mishra, A. K. (2024). Dynamic connectedness among market volatilities: a perspective of COVID-19 and Russia-Ukraine conflict. Studies in Economics and Finance, 41(5), 1119-1140. https://doi.org/10.1108/SEF-01-2024-0029
  • Mezghani, T., Ben Hamadou, F., & Boujelbène Abbes, M. (2021). The dynamic network connectedness and hedging strategies across stock markets and commodities: COVID-19 pandemic effect. Asia-Pacific Journal of Business Administration, 13(4), 520-552. https://doi.org/10.1108/APJBA-01-2021-0036
  • Nakajima, J. (2011). Time-varying parameter VAR model with stochastic volatility: An overview of methodology and empirical applications.
  • Noorani, G. M., Khan, M. T. A., & Khan, H. U. (2024). The Global Economic Consequences of the Russia-Ukraine War: Implications for Energy, Food Security, Post-COVID Recovery, and Regional Economic Stability. Policy Res. J, 2, 380-390.
  • Obi, P., Waweru, F., & Nyangu, M. (2023). An event study on the reaction of equity and commodity markets to the onset of the Russia–Ukraine conflict. Journal of Risk and Financial Management, 16(5), 256. https://doi.org/10.3390/jrfm16050256
  • Pichler, A., Pangallo, M., del Rio-Chanona, R. M., Lafond, F., & Farmer, J. D. (2021). In and out of lockdown: Propagation of supply and demand shocks in a dynamic input-output model. arXiv preprint arXiv:2102.09608.
  • Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. The Review of economic studies, 72(3), 821-852. https://doi.org/10.1111/j.1467-937X.2005.00353.x
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There are 50 citations in total.

Details

Primary Language English
Subjects Finance
Journal Section Research Article
Authors

Emrah Şahin 0000-0002-1001-6511

Submission Date November 16, 2025
Acceptance Date December 15, 2025
Publication Date December 31, 2025
Published in Issue Year 2025 Volume: 7 Issue: 2

Cite

APA Şahin, E. (2025). Dynamic Connectedness and Risk Transmission Among Global Sectoral Indices: Findings from COVID-19 and the Russia-Ukraine War. Quantrade Journal of Complex Systems in Social Sciences, 7(2), 154-172.

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