The Structural Transformation of Financial Volatility Spillovers in G20 Economies amid Geopolitical Bloc Formation: Türkiye’s Role

Öz

This study examines volatility spillovers among G20 financial markets during the 2016–2025 period within the context of intensifying geopolitical competition and financial restructuring in the global economy. The 16 G20 countries analyzed are classified into three groups: the Western Bloc (G7+), representing the core of the global financial architecture; the Emerging Markets Bloc (BRICS+), consisting of rising economic powers; and Türkiye, positioned strategically between these two structures. The study investigates how financial connectedness is shaped not only by economic fundamentals but also by geopolitical alignments, trade networks, and shifts in global power balances. Country-specific conditional volatility series derived from GJR-GARCH models are analyzed within a VAR-X framework incorporating trade-weighted external variables, while financial connectedness is dynamically measured using the Diebold-Yılmaz approach. The findings indicate that, following global shock periods such as the COVID-19 pandemic and the Russia-Ukraine war, financial transmission mechanisms between blocs weakened, whereas financial interactions within BRICS+ strengthened. While the Western Bloc remained a net volatility transmitter, volatility spillover asymmetry between the G7+ and BRICS+ declined. Structural break analyses reveal that regime shifts in financial connectedness coincided with these global shocks. Although Türkiye’s overall position in volatility transmission remained stable, the relative impact of BRICS+-originated volatility shocks increased. The findings suggest that Türkiye functions as a connecting node between geopolitical-economic blocs and that financial integration has been reshaped by changing power configurations in the 21st-century global political economy.

Anahtar Kelimeler

• Volatility spillover
• Geopolitical bloc formation
• Financial fragmentation
• G20

Jeopolitik Bloklaşma Sürecinde G20 Ekonomilerinde Finansal Volatilite Yayılımının Yapısal Dönüşümü: Türkiye’nin Rolü

Öz

Bu çalışma, 2016–2025 döneminde G20 finansal piyasaları arasındaki volatilite yayılımını, küresel ekonomide derinleşen jeopolitik rekabet ve finansal yeniden yapılanma süreci bağlamında incelemektedir. Çalışmada G20’de yer alan 16 ülke; küresel finansal mimarinin merkezini temsil eden Batı Bloğu (G7+), yükselen ekonomik güçlerin oluşturduğu Yükselen Piyasalar Bloğu (BRICS+) ve iki yapı arasındaki ilişkilerde stratejik konuma sahip Türkiye olarak sınıflandırılmıştır. Çalışma, finansal bağlantılılığın yalnızca ekonomik temellerle değil, jeopolitik konumlanmalar, ticaret ağları ve küresel güç dengelerindeki değişimlerle nasıl şekillendiğini analiz etmektedir. Ülke bazında GJR-GARCH modellerinden elde edilen koşullu volatilite serileri, ticaret ağırlıklı dış değişkenleri içeren VAR-X sistemi kapsamında değerlendirilmiş, finansal bağlantılılık yapısı Diebold-Yılmaz yaklaşımıyla dinamik olarak ölçülmüştür. Bulgular, COVID-19 salgını ve Rusya-Ukrayna savaşı gibi küresel şok dönemlerinin ardından bloklar arası finansal aktarım mekanizmalarının zayıfladığını, buna karşılık BRICS+ içindeki finansal etkileşimlerin güçlendiğini göstermektedir. Batı Bloğu net volatilite yayıcısı konumunu korurken, G7+ ve BRICS+ arasındaki aktarım asimetrisinin azaldığı belirlenmiştir. Yapısal kırılım analizleri, finansal bağlantılılıktaki rejim değişimlerinin küresel şok dönemleriyle örtüştüğünü göstermektedir. Türkiye’nin volatilite yayılımındaki konumu büyük ölçüde istikrarlı kalırken, BRICS+ kaynaklı volatilite şoklarının göreli etkisinin arttığı görülmektedir. Bulgular, Türkiye’nin küresel finansal sistemde farklı jeopolitik-ekonomik bloklar arasındaki bağlantı noktalarından biri olduğunu ve 21. yüzyılın değişen küresel ekonomi politiğinde finansal entegrasyonun yeni güç dengeleri doğrultusunda yeniden şekillendiğini ortaya koymaktadır.

Anahtar Kelimeler

• Volatilite yayılımı
• jeopolitik bloklaşma
• Finansal parçalanma
• G20

Kaynakça

1. Ahmed, S., Akinci, O., & Queralto, A. (2024). U.S. monetary policy spillovers to emerging markets: Both shocks and vulnerabilities matter (Staff Report No. 972). Federal Reserve Bank of New York Staff Report. https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr972.pdf
2. Aiyar, S., Chen, J., Ebeke, C., Garcia-Saltos, R., Gudmundsson, T., Ilyina, A., Kangur, A., Kunaratskul, T., Rodriguez, S. L., Ruta, M., Schulze, T., Soderberg, G., & Trevino, J. P. (2023). Geo-economic fragmentation and the future of multilateralism (IMF Staff Discussion Note SDN/2023/001). International Monetary Fund. https://doi.org/10.5089/9798400229046.006
3. Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk & Financial Management, 13(4), 84. https://doi.org/10.3390/jrfm13040084
4. Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. https://doi.org/10.2307/2998540
5. Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 1–22. https://doi.org/10.1002/jae.659
6. Baru, S. (2012). Geo-economics and strategy. Survival, 54(3), 47–58. https://doi.org/10.1080/00396338.2012.690978 Baruník, J., Kočenda, E., & Vácha, L. (2016). Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers. Journal of Financial Markets, 27, 55–78. https://doi.org/10.1016/j.finmar.2015.09.003
7. Billio, M., Getmansky, M., Lo, A. W., & Pelizzon, L. (2012). Econometric measures of connectedness and systemic risk in the finance and insurance sectors. Journal of Financial Economics, 104(3), 535–559. https://doi.org/10.1016/j.jfineco.2011.12.010
8. Blackwill, R. D., & Harris, J. M. (2016). War by other means: Geoeconomics and statecraft. Harvard University Press. https://doi.org/10.2307/j.ctt1c84cr7

9. Caldara, D., & Iacoviello, M. (2022). Measuring geopolitical risk. American Economic Review, 112(4), 1194–1225. https://doi.org/10.1257/aer.20191823
10. Calvo, G. A. (1998). Capital flows and capital-market crises: The simple economics of sudden stops. Journal of Applied Economics, 1(1), 35–54. https://doi.org/10.1080/15140326.1998.12040516
11. Ceyhan, İ. F. (2025). Küresel ve Türkiye’ye özgü jeopolitik risklerin BİST endeksleri üzerindeki etkisinin araştırılması. Business a& Management Studies: An International Journal, 13(3), 1376–1390. https://doi.org/10.15295/bmij.v13i3.2569
12. Dees, S., di Mauro, F., Pesaran, M. H., & Smith, L. V. (2007). Exploring the international linkages of the euro area: A global VAR analysis. Journal of Applied Econometrics, 22(1), 1–38. https://doi.org/10.1002/jae.932
13. Demirer, M., Diebold, F. X., Liu, L., & Yilmaz, K. (2018). Estimating global bank network connectedness. Journal of Applied Econometrics, 33(1), 1–15. https://doi.org/10.1002/jae.2585
14. Diebold, F. X., & Yılmaz, 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
15. Diebold, F. X., & Yılmaz, 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
16. Diebold, F. X., & Yılmaz, 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
17. Eichengreen, B., & Hausmann, R. (1999). Exchange rates and financial fragility (NBER Working Paper No. 7418). National Bureau of Economic Research. https://www.nber.org/papers/w7418
18. Erzurumlu, E. A., & Akçakanat, Ö. (2025). Jeopolitik risk endeksinin Türkiye’de BIST banka endeksi üzerine etkisi. Fiscaoeconomia, 9(4), 2155–2168. https://doi.org/10.25295/fsecon.1687064
19. Farrell, H., & Newman, A. L. (2019). Weaponized interdependence: How global economic networks shape state coercion. International Security, 44(1), 42–79. https://doi.org/10.1162/isec_a_00351
20. Fleming, J. M. (1962). Domestic financial policies under fixed and under floating exchange rates. IMF Staff Papers, 1962(3), 369–380. https://www.elibrary.imf.org/view/journals/024/1962/003/article-A004-en.xml
21. Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: Measuring stock market comovements. The Journal of Finance, 57(5), 2223–2261. https://doi.org/10.1111/0022-1082.00494
22. Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. The Journal of Finance, 48(5), 1779–1801. https://doi.org/10.1111/j.1540-6261.1993.tb05128.x
23. Gopinath, G., Gourinchas, P.-O., Presbitero, A. F., & Topalova, P. (2025). Changing global linkages: A new Cold War? Journal of International Economics, 153, 104042. https://doi.org/10.1016/j.jinteco.2024.104042
24. Hatemi-J, A. (2024). On the asymmetric volatility connectedness (arXiv:2404.12997). arXiv. https://doi.org/10.48550/arXiv.2404.12997
25. 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
26. Kose, M. A., Otrok, C., & Prasad, E. S. (2012). Global business cycles: Convergence or decoupling? International Economic Review, 53(2), 511–538. https://doi.org/10.1111/j.1468-2354.2012.00690.x
27. Miranda-Agrippino, S., & Rey, H. (2020). U.S. monetary policy and the global financial cycle. The Review of Economic Studies, 87(6), 2754–2776. https://doi.org/10.1093/restud/rdaa019
28. Mundell, R. A. (1963). Capital mobility and stabilization policy under fixed and flexible exchange rates. The Canadian Journal of Economics & Political Science, 29(4), 475–485. https://doi.org/10.2307/139336
29. Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. https://doi.org/10.2307/2938260
30. OECD. (n.d.). OECD and G20. Organisation for Economic Co-operation and Development. Retrieved October 16, 2026, from https://www.oecd.org/en/about/oecd-and-g20.html
31. Özer, A. (2026). Jeopolitik risklerin hisse senedi piyasalarına etkisi. Business & Management Studies: An International Journal, 14(1), 452–468. https://doi.org/10.15295/bmij.v14i1.2722
32. Pesaran, H. H. & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29. https://doi.org/10.1016/S0165-1765(97)00214-0
33. Pesaran, M. H., Schuermann, T., & Weiner, S. M. (2004). Modeling regional interdependencies using a global error-correcting macroeconometric model. Journal of Business & Economic Statistics, 22(2), 129–162. https://doi.org/10.1198/073500104000000019
34. Pesce, A. (2017). The decoupling of emerging economies: Theoretical and empirical puzzle. Journal of Economic Surveys, 31(2), 602–631. https://doi.org/10.1111/joes.12165
35. R Core Team. (2025). R: A language and environment for statistical computing*[Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/
36. Rey, H. (2015). Dilemma not trilemma: The global financial cycle and monetary policy independence (NBER Working Paper No. 21162). National Bureau of Economic Research. https://www.nber.org/papers/w21162
37. Salisu, A. A., Ogbonna, A. E., Lasisi, L., & Olaniran, A. (2022). Geopolitical risk and stock market volatility in emerging markets: A GARCH–MIDAS approach. The North American Journal of Economics and Finance, 62, 101755. https://doi.org/10.1016/j.najef.2022.101755
38. Syriopoulos, T., Makram, B., & Boubaker, A. (2015). Stock market volatility spillovers and portfolio hedging: BRICS and the financial crisis. International Review of Financial Analysis, 39, 7–18. https://doi.org/10.1016/j.irfa.2015.01.015
39. Üçler, G., & Özşahin, Ş. (2020). Jeopolitik risk ve borsa endeksinin nedensellik analizi: Gelişmekte olan ülkeler üzerine bootstrap panel nedensellik testi. Muhasebe ve Finansman Dergisi, (87), 167–180. https://doi.org/10.25095/mufad.756266
40. Webb, P. (2024). Legal options for confiscation of Russian state assets to support the reconstruction of Ukraine (Study PE 759.602). European Parliamentary Research Service (EPRS), European Parliament. https://www.europarl.europa.eu/thinktank/en/document/EPRS_STU(2024)759602