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BRICS-T Ülkelerinde Makroekonomik Faktörlerin ve Belirsizliklerin Hisse Senedi Volatilitesi Üzerindeki Etkisi: Panel NARDL Yaklaşımı

Yıl 2025, Cilt: 9 Sayı: 4, 1440 - 1460, 23.12.2025
https://doi.org/10.30586/pek.1663653

Öz

Hisse senedi piyasalarında volatilite ülkelerin ekonomik ve finansal göstergeleriyle açıklanamayacak kadar çok boyutlu bir yapıya sahiptir. Politik ve ekonomik belirsizlikler, yatırımcı kararları üzerinden varlık fiyatlamalarında önemli dalgalanmalara yol açabilmektedir. Finansal piyasalar, özellikle gelişmekte olan ekonomilerde, küresel risk algısındaki dalgalanmalara ve belirsizliklere karşı duyarlıdır. Bu çerçevede, birçok belirsizlik faktörünü içeren dünya belirsizlik endeksindeki artışlar, finansal varlıkların fiyatlarını doğrudan etkileyebilmektedir. Bu araştırmanın amacı, BRICS-T ülkelerinin hisse senedi piyasalarındaki oynaklığın, makroekonomik faktörler dahilinde belirsizlikler karşısındaki tepkisini incelemektir. Araştırmada Panel NARDL yöntemi kullanılarak kısa ve uzun dönem ilişkileri incelenmiştir. Araştırmanın ampirik bulguları, uzun vadede enflasyon ve faiz oranlarındaki yükselişlerin hisse senedi piyasasındaki volatil davranışları artırdığını, döviz kuru azalışlarının ise volatiliteyi azalttığını ortaya koymaktadır. Dünya belirsizlik endeksinin ise kısa ve uzun dönemde ülkelerin hisse senedi oynaklıklarının üzerinde anlamlı bir etkiye sahip olduğu tespit edilmiştir. Ayrıca araştırmada, uzun vadede belirsizlikteki artışların piyasalarda durgunluğa yol açarak volatiliteyi azalttığı, kısa vadede ise belirsizliklere gelen pozitif şokların volatiliteyi artırdığı bulgusuna ulaşılmıştır. Sonuçlar, BRICS-T ülkelerindeki hisse senedi piyasalarının yalnızca iç ekonomik dinamiklere değil, farklı kanallardan gelen belirsizliklere de duyarlı olduğunu göstermektedir. Bu araştırma, BRICS-T hisse senedi piyasasının değerlendirilmesinde dış şokların dikkate alınmasının önemini vurgulamakta ve küresel belirsizliklere bağlı risklerin yönetimi hususunda öneriler sunmaktadır.

Kaynakça

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  • Acuña, C. A., Bolancé, C. B., & Torra, S. (2021). Dynamic distances between stock markets: Use of uncertainty indices measures. Anales del Instituto de Actuarios Españoles, (27), 55-73. https://doi.org/10.26360/2021_3
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The Impact of Macroeconomic Factors and Uncertainty on Stock Market Volatility in the BRICS-T Countries: A Panel NARDL Approach

Yıl 2025, Cilt: 9 Sayı: 4, 1440 - 1460, 23.12.2025
https://doi.org/10.30586/pek.1663653

Öz

: Volatility in stock markets has a multidimensional structure that cannot be explained solely by the economic and financial indicators of countries. Political and economic uncertainties can lead to significant fluctuations in asset pricing through their influence on investor decisions. Financial markets, particularly in emerging economies, are sensitive to fluctuations and uncertainties in global risk perception. In this context, increases in the World Uncertainty Index, which encompasses various uncertainty factors, can directly affect the prices of financial assets. The aim of this study is to examine the response of stock market volatility in the BRICS-T countries to uncertainties within the framework of macroeconomic factors. We analyzed both short- and long-term relationships using the Panel NARDL method. The empirical findings of the study reveal that, in the long term, increases in inflation and interest rates amplify volatile behavior in the stock markets, while decreases in exchange rates tend to reduce volatility. The World Uncertainty Index significantly influences stock market volatility, both in the short and long term. Moreover, the study finds that, in the long run, rising uncertainty leads to stagnation in markets, thereby reducing volatility, whereas in the short run, positive shocks to uncertainty increase volatility. The results demonstrate that stock markets in the BRICS-T countries are sensitive not only to domestic economic dynamics but also to uncertainties transmitted through various external channels. This study underscores the importance of considering external shocks in the evaluation of the BRICS-T stock markets and offers recommendations for managing risks associated with global uncertainties.

Kaynakça

  • Abdalla, I. S. A., ve Murinde, V. (1997). Exchange rate and stock price interactions in emerging financial markets: Evidence on India, Korea, Pakistan, and Philippines. Applied Financial Economics, 7(1), 25–35. https://doi.org/10.1080/096031097333826
  • Acuña, C. A., Bolancé, C. B., & Torra, S. (2021). Dynamic distances between stock markets: Use of uncertainty indices measures. Anales del Instituto de Actuarios Españoles, (27), 55-73. https://doi.org/10.26360/2021_3
  • Ahir, H., Bloom, N., & Furceri, D. (2022). The World Uncertainty Index. Economics Letters, (196), Article 109645. http://www.nber.org/papers/w29763
  • Al-Thaqeb, S. A., & Algharabali, B. G. (2019). Economic policy uncertainty: A literature review. The Journal of Economic Asymmetries, (20), Article e00133. https://doi.org/10.1016/j.jeca.2019.e00133
  • Amo-Bediako, E., Takawira, O., Choga, I., Otchere, I., & Siaw-Asamoah, D. (2024). Asymmetric impact of climate change on banking system stability in selected sub-Saharan economies. The Economics and Finance Letters, 11(4), 304-321. https://doi.org/10.18488/29.v11i4.3956
  • Antonakakis, N., Chatziantoniou, I., & Filis, G. (2013). Dynamic co-movements of stock market returns, implied volatility and policy uncertainty. Economics Letters, 120(1), 87-92. https://doi.org/10.1016/j.econlet.2013.04.004
  • Ariff, M., Chung, T. F., & Shamsher, M. (2012). Money supply, interest rate, liquidity and share prices: A test of their linkage. Global Finance Journal, (23), 202–220. https://doi.org/10.1016/j.gfj.2012.10.005
  • Ashraf, B. N. (2020). Stock markets’ reaction to COVID-19: Cases or fatalities?. Research in International Business and Finance, (54), Article 101249. https://doi.org/10.1016/j.ribaf.2020.101249
  • Bahmani-Oskooee, M., & Sohrabian, A. (1992). Stock prices and the effective exchange rate of the dollar. Applied Economics, 24(4), 459-464. https://doi.org/10.1080/00036849200000020
  • Baker, S. R., Bloom, N., & Davis, S. J. (2013). Economic Policy Uncertainty Index. 26 Ocak 2025 tarihinde www.policyuncertainty.com adresinden erişildi.
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  • Iqbal, J., Jabeen, S., Nosheen, M., & Wohar, M. (2024). The asymmetric effects of exchange rate volatility on Pakistan–Japan commodity trade: Evidence from non-linear ARDL approach. Asia-Pacific Financial Markets, 31(3), 657-732. https://doi.org/10.1007/s10690-023-09427-6
  • Isah, K. O., Badmus, S. K., Ogunjemilua, O. D., Adelakun, J. O., & Yakubu, Y. (2024). Revisiting the predictive prowess of economic policy uncertainty (EPU) in stock market volatility: GEPU or NEPU? Scientific African, (23), Article e02068. https://doi.org/10.1016/j.sciaf.2024.e02068
  • Jiao, W., & Zheng, X. (2025). Uncertainty and volatility asymmetry. Applied Economics Letters, 1-9. https://doi.org/10.1080/13504851.2025.2470305
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  • Kassouri, Y., & Altıntaş, H. (2020). Threshold cointegration, nonlinearity, and frequency domain causality relationship between stock price and Turkish Lira. Research in International Business and Finance, (52), 1–18. https://doi.org/10.1016/j.ribaf.2019.101097
  • Kazak, H., Saiti, B., Kılıç, C., Akcan, A. T., & Karataş, A. R. (2024). Impact of global risk factors on the Islamic stock market: New evidence from wavelet analysis. Computational Economics, 1-32. https://doi.org/10.1007/s10614-024-10665-7
  • Kurt, P. (2024) Küreselleşmenin hisse senedi piyasası oynaklığı üzerindeki etkisi: BRICS-T ülkeleri örneği. (Tez No. 897567). Doktora tezi, Bandırma Onyedi Eylül Üniversitesi, Yök Ulusal Tez Merkezi.
  • Latif, S., Aslam, F., Ferreira, P., & Iqbal, S. (2024). Integrating macroeconomic and technical indicators into forecasting the stock market: A data-driven approach. Economies, 13(1), 6. https://doi.org/10.3390/economies13010006
  • Li, T., Ma, F., Zhang, X., & Zhang, Y. (2020). Economic policy uncertainty and the Chinese stock market volatility: Novel evidence. Economic Modelling, (87), 24-33. https://doi.org/10.1016/j.econmod.2019.07.002
  • Liu, L., & Zhang, T. (2015). Economic policy uncertainty and stock market volatility. Finance Research Letters, (15), 99-105. https://doi.org/10.1016/j.frl.2015.08.009
  • Luan, D., Mahmood, H., Khalid, S., & Fida, B. A. (2024). Asymmetric impact of green innovation and taxation on environmental sustainability in developing countries. Journal of the Knowledge Economy, 1-22. https://doi.org/10.1007/s13132-024-01959-0
  • Mei, D., Zeng, Q., Zhang, Y., & Hou, W. (2018). Does US economic policy uncertainty matter for European stock markets volatility? Physica A: Statistical Mechanics and Its Applications, (512), 215-221. https://doi.org/10.1016/j.physa.2018.08.019
  • Moussa, F., & Delhoumi, E. (2022). The asymmetric impact of interest and exchange rate on the stock market index: Evidence from MENA region. International Journal of Emerging Markets, 17(10), 2510-2528. https://doi.org/10.1108/IJOEM-01-2020-0089
  • Mwamba, J. W., Mba, J. C., & Kitenge, A. K. (2025). Navigating uncertainty in an emerging market: Data-centric portfolio strategies and systemic risk assessment in the Johannesburg Stock Exchange. International Journal of Financial Studies, 13(1), 32. https://doi.org/10.3390/ijfs13010032
  • Obben, J., Pech, A., & Shakur, S. (2006). Analysis of the relationship between the share market performance and exchange rates in New Zealand: A cointegrating VAR approach. New Zealand Economic Papers, 40(2), 147-180. https://doi.org/10.1080/00779954.2006.9558559
  • O’Connell, P. G. (1998). The overvaluation of purchasing power parity. Journal of International Economics, 44(1), 1-19. https://doi.org/10.1016/S0022-1996(97)00017-2
  • Paule-Vianez, J., Gómez-Martínez, R., & Prado-Román, C. (2020a). Effect of economic and monetary policy uncertainty on stock markets: Evidence on return, volatility and liquidity. Economics Bulletin, 40(2), 1261–1271.
  • Paule-Vianez, J., Prado-Román, C., & Gómez-Martínez, R. (2020b). Monetary policy uncertainty and stock market returns: Influence of limits to arbitrage and the economic cycle. Studies in Economics and Finance, 37(4), 777–798. https://doi.org/10.1108/SEF-04-2020-0102
  • Pesaran, M. H. (2004). General diagnostic tests for cross-section dependence in panels. Cambridge Working Papers in Economics, 1240(1), 1-39.
  • Pedroni, P. (2004). Panel cointegration: Asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory, 20(3), 597-625. https://doi.org/10.1017/S0266466604203073
  • Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence. Journal of Applied Econometrics, 22(2), 265-312. https://doi.org/10.1002/jae.951
  • Pesaran, M. H., Shin, Y., & Smith, R. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621-634. https://doi.org/10.1080/01621459.1999.10474156
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326. https://doi.org/10.1002/jae.616
  • Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A bias‐adjusted LM test of error cross‐section independence. The Econometrics Journal, 11(1), 105-127. https://doi.org/10.1111/j.1368-423X.2007.00227.x
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  • Sultan, H., Rahman, S. U., Munir, F., Ali, A., Younas, S., & Khan, H. (2025). Institutional dynamics, innovation, and environmental outcomes: A panel NARDL analysis of BRICS nations. Environment, Development and Sustainability, 1-43. https://doi.org/10.1007/s10668-024-05879-6
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  • Ülkü, N., & Demirci, E. (2012). Joint dynamics of foreign exchange and stock markets in emerging Europe. Journal of International Financial Markets, Institutions & Money, (22), 55–86. https://doi.org/10.1016/j.intfin.2011.07.005
  • Wen, F., Shui, A., Cheng, Y., & Gong, X. (2022). Monetary policy uncertainty and stock returns in G7 and BRICS countries: A quantile-on-quantile approach. International Review of Economics and Finance, (78), 457–482. https://doi.org/10.1016/j.iref.2021.12.015
  • Wiedmann, M. (2011). Money, stock prices and central banks: A cointegrated VAR analysis. Springer Science & Business Media. DOI: 10.1007/978-3-7908-7647-0
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  • Yu, M. (2023). Forecasting sector-level stock market volatility: The role of world uncertainty index. Finance Research Letters, (58), Article 104568. https://doi.org/10.1016/j.frl.2023.104568
Toplam 86 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Uluslararası Finans
Bölüm Araştırma Makalesi
Yazarlar

Pınar Kurt 0000-0001-6870-4248

Gönderilme Tarihi 23 Mart 2025
Kabul Tarihi 6 Ağustos 2025
Yayımlanma Tarihi 23 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 9 Sayı: 4

Kaynak Göster

APA Kurt, P. (2025). BRICS-T Ülkelerinde Makroekonomik Faktörlerin ve Belirsizliklerin Hisse Senedi Volatilitesi Üzerindeki Etkisi: Panel NARDL Yaklaşımı. Politik Ekonomik Kuram, 9(4), 1440-1460. https://doi.org/10.30586/pek.1663653

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