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BRICS-T HİSSE SENEDİ PİYASALARI VE KÜRESEL FİNANSAL GÖSTERGELER ARASINDAKİ VOLATİLİTE ETKİLEŞİMİ

Yıl 2025, , 109 - 134, 30.06.2025

Meltem Kılıç

https://doi.org/10.53443/anadoluibfd.1569090

Öz

Çalışmada, 10.03.2011-29.02.2024 tarihleri arasındaki BRICS-T ülkelerinin borsa endeksleriyle küresel finansal göstergeler arasındaki volatilite etkileşimi Dinamik Koşullu Korelasyon DCC-GARCH modeli ile analiz edilmiştir. BRICS-T ülkeleri borsa endekslerini temsilen Brezilya’nın BOVESPA (IBOV), Rusya’nın RTSI (IRTS), Hindistan’ın S&P BSE-100 (BSE100), Çin’in Shanghai Composite (SHCI), Güney Afrika’nın Top 40 (JTOPI) ve Türkiye’nin Borsa İstanbul 100 (BIST100) fiyat endeksleri kullanılmıştır. Küresel finansal gösterge olarak Batı Teksas ham petrol (WTI), Amerika Birleşik Devletleri (ABD) 10 yıllık hazine tahvili (10YT) ve altının ons fiyatı (ALTIN) kullanılmış ve tüm serilerin getirileri hesaplanmıştır. Çalışma sonucunda, tüm göstergelerin çok yüksek kalıcı volatilite sahip olduğu belirlenmiştir. Ayrıca, BRICS-T ülkeleri endeksleri ile 10YT arasında çok kuvvetli dinamik korelasyon ilişkisine, IRTS, BSE100 ve BIST100 endeksleri ile WTI arasında çok kuvvetli dinamik korelasyon ilişkisine ve IBOV, JTOPI endeksleri ile altın getirileri arasında çok kuvvetli dinamik korelasyon ilişkisine rastlanılmıştır. Sonuç olarak, elde edilen bu bulgular politika yapıcıları ve yatırımcılara portföy stratejileri hakkında bilgiler sağlamaktadır.

Anahtar Kelimeler

BRICS-T Hisse Senedi Piyasaları Küresel Finansal Göstergeler Volatilite Etkileşimi. DCC-GARCH Modeli

Kaynakça

  • Ahmad, W., Mishra, A.V., & Daly, K.J. (2018). Financial connectedness of brıcs and global sovereign bond markets. Emerging Markets Review, 37, 1-16. doi: 10.1016/j.ememar.2018.02.006
  • Akçalı, B.Y. Mollaahmetoğlu, E., & Altay, E. (2019). Borsa İstanbul ve küresel piyasa göstergeleri arasındaki volatilite etkileşiminin DCC-GARCH yöntemi ile analizi. Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 4(3), 597-614. doi: 10.17153/oguiibf.472731
  • Aslan, M. (2024). BRICS-T ülkelerinin önde gelen borsa endekslerinin oynaklık davranışlarının asimetrik stokastik oynaklık modelleri ile analizi. Uluslararası Ekonomi, İşletme ve Politika Dergisi, 8(1), 230-243. doi: 10.29216/ueip.1441634
  • Başarır, Ç. (2019). Altın ve hisse senedi getirileri arasındaki nedensellik ilişkisi: Türkiye örneği. Trakya Üniversitesi Sosyal Bilimler Dergisi, 2(2), 475-490. doi: 10.26468/trakyasobed.472190
  • Baydaş, Y., & Kılıç, E. (2022). Bitcoin ve ons arasındaki çok değişkenli stokastik volatilite aktarımı. Akademik Araştırmalar ve Çalışmalar Dergisi, 14(26), 149-157. doi: 10.20990/kilisiibfakademik.1082840
  • Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24. doi: 10.1016/j.econmod.2014.10.044
  • Behera, C., & Rath, B.N. (2024). The interconnectedness between crude oil prices and stock returns in G20 countries. Resources Policy, 91, 1-9. doi: 10.1016/j.resourpol.2024.104950
  • Bollerslev, T. (1990). Modellin the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. The Review of Economics and Statistics, 72(3), 498-505.
  • Bollerslev, T., Engle, R. F., & Wooldridge, J.M. (1988). A capital asset pricing model with time-varing covariances. Journal of Political Economy, 96(1), 116-131.
  • Büberkökü, Ö., Kızıldere, C., & Yiğenoğlu, K. (2021). BRICS ülkeleri ile Türkiye hisse senedi piyasaları arasındaki volatilite yayılımın incelenmesi. Van Yüzüncü Yıl Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 6(11), 101-117.
  • Caporale, G.M., Çatık, A.N. Kısla, G.S.K., Helmi, M.H. & Akdeniz, C. (2022). Oil prices and sectoral stock returns in the BRICS-T countries: A time-varying approach. Resources Policy, 79, 1-16. doi: 10.1016/j.resourpol.2022.103044
  • Chang, K-L. (2012). Volatility regimes, asymmetric basis effects and forecasting performance: An empirical investigation of the WTI crude oil futures market. Energy Economics, 34, 294-306. doi: 10.1016/j.eneco.2011.11.009
  • Chang, H-W. Chang, T. & Lee, C-C. (2023). Return and volatility connectedness among the BRICS stock and oil markets. Resources Policy. 86, 1-17. doi: 10.1016/j.resourpol.2023.104241
  • Chen, W., Huang, Z., & Yi, Y. (2015). Is there a structural change in the persistence of WTI-Brent oil price spreads in the post-2010 period? Economic Modelling, 50, 64-71. doi: 10.1016/j.econmod.2015.06.007
  • Çelik, İ., Özdemir, A., Gürsoy, S. & Ünlü, Uzunoğlu, H. (2018). Gelişmekte olan hisse senedi piyasaları ile kıymetli madenler arasındaki getiri ve volatilite yayılımı. Ege Akademik Bakış, 18(2), 217-230. doi: 10.21121/eab.2018237351
  • Diebold, F.X. & Yılmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119, 158-171.
  • Diebold, F.X. & Yılmaz, K. (2012). Better to given than to receive: predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28, 57-66. doi: 10.1016/j.ijforecast.2011.02.006
  • Diebold, F.X. & Yılmaz, K. (2023). Reprint of: On the network topology of variance decomposition: Measuring the connectedness of financial firms. Journal of Econometrics. 234, 70-90. doi: 10.1016/j.jeconom.2023.03.003
  • Ding, L., & Vo, M. (2012). Exchange rates and oil prices: A Multivariate Stochastic Volatility Analysis. The Quarterly Review of Economics and Finance, 52, 15-37.
  • Engle, R. (2002). Dynamic Conditional Correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models, Journal of Business & Economic Statistics, 20(3). doi: 10.1198/073500102288618487
  • Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4) 987-1007.
  • Eyüboğlu, S., & Eyüboğlu, K. (2018). Amerikan 10 yıllık tahvil faizleri ile gelişmekte olan ülke borsaları arasındaki ilişkinin test edilmesi. Yönetim Bilimleri Dergisi, 16(31), 443-459.
  • Gamba-Santamaria, S., Gomez-Gonzalez, J.E., Hurtado-Guarin, J.L., & Melo-Velandia, L.F. (2017). Stock market volatility spillovers: Evidence for Latin America. Finance Research Letters, 20, 207-216. doi: 10.1016/j.frl.2016.10.001
  • Ghani, U. Zhu, B. Ghani, M., Khan, N., & Khan, R.D.A. (2023). Role of oil shocks in US stock market volatility: A new insight from GARCH-MIDAS perspective. Resources Policy, 85, 1-8. doi: 10.1016/j.resourpol.2023.103933
  • Göktaş, Ö. (2017). Volatility transmission among G-7 stock markets and gold market. Eurasian Academy of Sciences-Eurasian Econometrics, Statistics & Emprical Economics Journal, 8, 100-114.
  • Guru, B.K., Pradhan, A.K., & Bandaru, R. (2023). Volatility contagion between oil and the stock markets of G7 countries plus India and China. Resources Policy, 81, 1-10. doi: 10.1016/j.resourpol.2023.103377
  • Hepsağ, A., & Akçalı, B.Y. (2016) Analysis of volatility spillovers between the bank stocks traded in Istanbul Stock Exchange and New York Stock Exchange. Eurasian Academy of Sciences Eurasian Econometrics, Statistics & Emprical Economics Journal. 1, 57-72.
  • Hossenidoust, E., Janor, H., Yusefi, M., & Majid, H.A. (2013). Volatility spillovers across commodity and stock market among ASEAN countries. Prosiding Perkem 8(3), 1401-1412.
  • Joo, B.A., Ghulam, Y.A., & Mir, S.I. (2023). Symmetric and asymmetric volatility spillover among BRICS countries’ stock markets. Decision, 50(4), 473-488. doi: 10.1007/s40622-023-00368-7
  • Kılıç, E. (2022). Petrol riski, petrol spot ve petrol vadeli işlemler arasındaki dinamik stokastik volatilite yayılımı. Equinoks Ekonomi İşletme ve Siyasal Çalışmalar Dergisi, 9(2), 158-171. doi: 10.48064/equinox.1116434.
  • Kılıç, E., & Gürsoy, E. (2021). Küresel belirsizlik endeksi ile Brics Borsaları arasındaki volatilite yayılımı: BEKK Garch ile analizi. 24. Finans Sempozyumu (20-23 Ekim 2021-Sakarya), Sempozyum Bildiri Kitabı (s. 162-173).
  • Korkusuz, B., McMillan, D.G., & Kambouroudis, D. (2023). Complex network analysis of volatility spillovers between global financial ındicators and G20 stock markets. Empirical Economics, 64, 1517-1537. doi: 10.1007/s00181-022-02290-w
  • Lee, Y-H., Huang, Y-L., & Wu, C-Y. (2014). Dynamic correlations and volatility spillovers between crude oil and stock ındex returns: The implications for optimal portfolio construction. International Journal of Energy Economics and Policy. 4(3), 327-336.
  • Ljung, G. M., & Box, G.E.P. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297-303.
  • Im, K.S., Lee, J., & Tieslau, M.A. (2014). More powerfull unit root tests with non-normal errors. Sickle, R.C., & Horrace, W.C. (Editörler), Festschrift in honor of Peter Schmidt-Econometric methods and applications (s. 315-342) içinde. Springer.
  • Massadikov, K. (2021). Volatility spillovers between oil prices and stock returns in developing countries. In: International Journal of Energy Economics and Policy, 11(4), 121-126. doi: 10.32479/ijeep.11117
  • Mensi, W., Hammoudeh, S. Reboredo, J.C., & Nguyen, D.K. (2014). Do global factors impact BRICS stock markets? A quantile regression approach. Emerging Markets Review, 19, 1-17. doi: 10.1016/j.ememar.2014.04.002
  • Mensi, W., Rehman, M.U. Al-Yahyaee, K.H., & Vo, X.V. (2023). Frequency dependence between oil futures and international stock markets and the role of gold, bonds, and uncertainty ındices: Evidence from partial and multivariate wavelet approaches. Resources Policy, 80, 1-27. doi: 10.1016/j.resourpol.2022.103161
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VOLATILITY SPILLOVERS BETWEEN GLOBAL FINANCIAL INDICATORS AND BRICS-T STOCK MARKETS

Yıl 2025, , 109 - 134, 30.06.2025

Meltem Kılıç

https://doi.org/10.53443/anadoluibfd.1569090

Öz

In the study, the volatility interaction between the stock indices of BRICS-T countries and global financial indicators from 03.10.2011 to 02.29.2024 was analyzed using the Dynamic Conditional Correlation DCC-GARCH model. The stock indices representing the BRICS-T countries are represented by the stock indices: Brazil’s BOVESPA (IBOV), Russia’s RTSI (IRTS), India’s S&P BSE-100 (BSE100), China’s Shanghai Composite (SHCI), South Africa’s Top 40 (JTOPI) and Turkey’s Borsa Istanbul 100 (BIST100). As global asset indicators, The West Texas Intermediarte (WTI) crude oil, The United States (US) 10-year Treasury bond yield (10YT), and the price of gold per ounce (GOLD) were used as global financial indicators and the returns of all series were calculated. As a result of the study, it has been determined that all indicators exhibit a high level of persistent volatility. Furthermore, a strong dynamic correlation has been observed between the BRICS-T country indices and the 10-year Treasury yield, between the IRTS, BSE100 and BIST100 indices and WTI and between the IBOV and JTOPI indices and gold returns. In conclusion, these findings provide information to policymakers and investors regarding portfolio strategies.

Anahtar Kelimeler

The BRICS-T Stock Markets Global Financial Indicators Volatility Spillover DCC-GARCH Model

Kaynakça

  • Ahmad, W., Mishra, A.V., & Daly, K.J. (2018). Financial connectedness of brıcs and global sovereign bond markets. Emerging Markets Review, 37, 1-16. doi: 10.1016/j.ememar.2018.02.006
  • Akçalı, B.Y. Mollaahmetoğlu, E., & Altay, E. (2019). Borsa İstanbul ve küresel piyasa göstergeleri arasındaki volatilite etkileşiminin DCC-GARCH yöntemi ile analizi. Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 4(3), 597-614. doi: 10.17153/oguiibf.472731
  • Aslan, M. (2024). BRICS-T ülkelerinin önde gelen borsa endekslerinin oynaklık davranışlarının asimetrik stokastik oynaklık modelleri ile analizi. Uluslararası Ekonomi, İşletme ve Politika Dergisi, 8(1), 230-243. doi: 10.29216/ueip.1441634
  • Başarır, Ç. (2019). Altın ve hisse senedi getirileri arasındaki nedensellik ilişkisi: Türkiye örneği. Trakya Üniversitesi Sosyal Bilimler Dergisi, 2(2), 475-490. doi: 10.26468/trakyasobed.472190
  • Baydaş, Y., & Kılıç, E. (2022). Bitcoin ve ons arasındaki çok değişkenli stokastik volatilite aktarımı. Akademik Araştırmalar ve Çalışmalar Dergisi, 14(26), 149-157. doi: 10.20990/kilisiibfakademik.1082840
  • Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24. doi: 10.1016/j.econmod.2014.10.044
  • Behera, C., & Rath, B.N. (2024). The interconnectedness between crude oil prices and stock returns in G20 countries. Resources Policy, 91, 1-9. doi: 10.1016/j.resourpol.2024.104950
  • Bollerslev, T. (1990). Modellin the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. The Review of Economics and Statistics, 72(3), 498-505.
  • Bollerslev, T., Engle, R. F., & Wooldridge, J.M. (1988). A capital asset pricing model with time-varing covariances. Journal of Political Economy, 96(1), 116-131.
  • Büberkökü, Ö., Kızıldere, C., & Yiğenoğlu, K. (2021). BRICS ülkeleri ile Türkiye hisse senedi piyasaları arasındaki volatilite yayılımın incelenmesi. Van Yüzüncü Yıl Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 6(11), 101-117.
  • Caporale, G.M., Çatık, A.N. Kısla, G.S.K., Helmi, M.H. & Akdeniz, C. (2022). Oil prices and sectoral stock returns in the BRICS-T countries: A time-varying approach. Resources Policy, 79, 1-16. doi: 10.1016/j.resourpol.2022.103044
  • Chang, K-L. (2012). Volatility regimes, asymmetric basis effects and forecasting performance: An empirical investigation of the WTI crude oil futures market. Energy Economics, 34, 294-306. doi: 10.1016/j.eneco.2011.11.009
  • Chang, H-W. Chang, T. & Lee, C-C. (2023). Return and volatility connectedness among the BRICS stock and oil markets. Resources Policy. 86, 1-17. doi: 10.1016/j.resourpol.2023.104241
  • Chen, W., Huang, Z., & Yi, Y. (2015). Is there a structural change in the persistence of WTI-Brent oil price spreads in the post-2010 period? Economic Modelling, 50, 64-71. doi: 10.1016/j.econmod.2015.06.007
  • Çelik, İ., Özdemir, A., Gürsoy, S. & Ünlü, Uzunoğlu, H. (2018). Gelişmekte olan hisse senedi piyasaları ile kıymetli madenler arasındaki getiri ve volatilite yayılımı. Ege Akademik Bakış, 18(2), 217-230. doi: 10.21121/eab.2018237351
  • Diebold, F.X. & Yılmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119, 158-171.
  • Diebold, F.X. & Yılmaz, K. (2012). Better to given than to receive: predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28, 57-66. doi: 10.1016/j.ijforecast.2011.02.006
  • Diebold, F.X. & Yılmaz, K. (2023). Reprint of: On the network topology of variance decomposition: Measuring the connectedness of financial firms. Journal of Econometrics. 234, 70-90. doi: 10.1016/j.jeconom.2023.03.003
  • Ding, L., & Vo, M. (2012). Exchange rates and oil prices: A Multivariate Stochastic Volatility Analysis. The Quarterly Review of Economics and Finance, 52, 15-37.
  • Engle, R. (2002). Dynamic Conditional Correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models, Journal of Business & Economic Statistics, 20(3). doi: 10.1198/073500102288618487
  • Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4) 987-1007.
  • Eyüboğlu, S., & Eyüboğlu, K. (2018). Amerikan 10 yıllık tahvil faizleri ile gelişmekte olan ülke borsaları arasındaki ilişkinin test edilmesi. Yönetim Bilimleri Dergisi, 16(31), 443-459.
  • Gamba-Santamaria, S., Gomez-Gonzalez, J.E., Hurtado-Guarin, J.L., & Melo-Velandia, L.F. (2017). Stock market volatility spillovers: Evidence for Latin America. Finance Research Letters, 20, 207-216. doi: 10.1016/j.frl.2016.10.001
  • Ghani, U. Zhu, B. Ghani, M., Khan, N., & Khan, R.D.A. (2023). Role of oil shocks in US stock market volatility: A new insight from GARCH-MIDAS perspective. Resources Policy, 85, 1-8. doi: 10.1016/j.resourpol.2023.103933
  • Göktaş, Ö. (2017). Volatility transmission among G-7 stock markets and gold market. Eurasian Academy of Sciences-Eurasian Econometrics, Statistics & Emprical Economics Journal, 8, 100-114.
  • Guru, B.K., Pradhan, A.K., & Bandaru, R. (2023). Volatility contagion between oil and the stock markets of G7 countries plus India and China. Resources Policy, 81, 1-10. doi: 10.1016/j.resourpol.2023.103377
  • Hepsağ, A., & Akçalı, B.Y. (2016) Analysis of volatility spillovers between the bank stocks traded in Istanbul Stock Exchange and New York Stock Exchange. Eurasian Academy of Sciences Eurasian Econometrics, Statistics & Emprical Economics Journal. 1, 57-72.
  • Hossenidoust, E., Janor, H., Yusefi, M., & Majid, H.A. (2013). Volatility spillovers across commodity and stock market among ASEAN countries. Prosiding Perkem 8(3), 1401-1412.
  • Joo, B.A., Ghulam, Y.A., & Mir, S.I. (2023). Symmetric and asymmetric volatility spillover among BRICS countries’ stock markets. Decision, 50(4), 473-488. doi: 10.1007/s40622-023-00368-7
  • Kılıç, E. (2022). Petrol riski, petrol spot ve petrol vadeli işlemler arasındaki dinamik stokastik volatilite yayılımı. Equinoks Ekonomi İşletme ve Siyasal Çalışmalar Dergisi, 9(2), 158-171. doi: 10.48064/equinox.1116434.
  • Kılıç, E., & Gürsoy, E. (2021). Küresel belirsizlik endeksi ile Brics Borsaları arasındaki volatilite yayılımı: BEKK Garch ile analizi. 24. Finans Sempozyumu (20-23 Ekim 2021-Sakarya), Sempozyum Bildiri Kitabı (s. 162-173).
  • Korkusuz, B., McMillan, D.G., & Kambouroudis, D. (2023). Complex network analysis of volatility spillovers between global financial ındicators and G20 stock markets. Empirical Economics, 64, 1517-1537. doi: 10.1007/s00181-022-02290-w
  • Lee, Y-H., Huang, Y-L., & Wu, C-Y. (2014). Dynamic correlations and volatility spillovers between crude oil and stock ındex returns: The implications for optimal portfolio construction. International Journal of Energy Economics and Policy. 4(3), 327-336.
  • Ljung, G. M., & Box, G.E.P. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297-303.
  • Im, K.S., Lee, J., & Tieslau, M.A. (2014). More powerfull unit root tests with non-normal errors. Sickle, R.C., & Horrace, W.C. (Editörler), Festschrift in honor of Peter Schmidt-Econometric methods and applications (s. 315-342) içinde. Springer.
  • Massadikov, K. (2021). Volatility spillovers between oil prices and stock returns in developing countries. In: International Journal of Energy Economics and Policy, 11(4), 121-126. doi: 10.32479/ijeep.11117
  • Mensi, W., Hammoudeh, S. Reboredo, J.C., & Nguyen, D.K. (2014). Do global factors impact BRICS stock markets? A quantile regression approach. Emerging Markets Review, 19, 1-17. doi: 10.1016/j.ememar.2014.04.002
  • Mensi, W., Rehman, M.U. Al-Yahyaee, K.H., & Vo, X.V. (2023). Frequency dependence between oil futures and international stock markets and the role of gold, bonds, and uncertainty ındices: Evidence from partial and multivariate wavelet approaches. Resources Policy, 80, 1-27. doi: 10.1016/j.resourpol.2022.103161
  • Öner, S., & İçellioğlu Şarkaya, C. (2018). ABD’nin geleneksel olmayan para politikası uygulamalarının gelişmekte olan ülke tahvil piyasaları üzerindeki etkisi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 32(4), 1171-1188.
  • Polat, M., & Kılıç, E. (2022). BRICS ve MIST ülkelerinin borsalar arası getiri ve volatilite etkileşimi. Manisa Celal Bayar Üniversitesi, İ.İ.B.F. Yönetim ve Ekonomi Dergisi, 29(4), 723-739. doi: 10.18657/yonveek.1020756
  • Sarwar, S. Tiwari, A.K., & Tingqiu, C. (2020). Analyzing volatility spillovers between oil market and Asian stock markets. Resources Policy. 66, 1-12. doi: 10.1016/j.resourpol.2020.101608
  • Shabbir, A., Kousar, S., & Batool, S.A. (2020). Impact of gold and oil prices on the stock market in Pakistan, Journal of Economics, Finance and Administrative Sciences, 25(50), 279-294. doi: 10.1108/JEFAS-04-2019-0053
  • Taşkan, B., & İşcanoğlu Çekiç, A. (2019). Sermaye piyasası endeksleri ile altın piyasası arasındaki etkileşim: Gelişmekte olan ülkeler örneği. Uluslararası İktisadi ve İdari İncelemeler Dergisi, 23, 131-150. doi: 10.18092/ulikidince.476844
  • Tse, Y.K., & Tsui, A.K.C. (2002). A multivariate generalized autoregressive conditional heteroscedasticity model with time-varing correlations. Journal of Business & Economic Statistics, 20(3), 351-362. doi: 10.1198/073500102288618496
  • Wang, N., & You, W. (2023). New insights into the role of global factors in BRICS stock markets: A quantile cointegration approach. Economic Systems, 47, 1-18. doi: 10.1016/j.ecosys.2022.101015
  • Wang, Y., Liu, L. Diao, X., & Wu, C. (2015). Forecasting the real prices of crude oil under economic and statistical constraints. Energy Economics, 51, 599-608. doi: 10.1016/j.eneco.2015.09.003
  • Wang, Y. S., & Chueh, Y. L. (2013). Dynamic transmission effects between the interest rate, the US dollar, and gold and crude oil prices. Economic Modelling, 30, 792-798. doi: 10.1016/j.econmod.2012.09.052
  • Whaley, R. E. (2000), The investor fear gauge. The Journal of Portfolio Management, 26(3): 12-17. doi: 10.3905/jpm.2000.319728
  • Yang, Y., Shao, Y., Shao, H., & Song, X (2020). The time-dependent lead-lag relationship between WTI and Brent crude oil spot markets. Frontiers in Physics, 8(132), 1-6. doi: 10.3389/fphy.2020.00132
  • Yıldırım, D. Ç., Yıldırım, S., & Demirtaş, I. (2019). Investigating energy consumption and economic growth for BRICS-T countries. World Journal of Science, Technology and Sustainable Development, 16(4), 184-195. doi: 10.1108/WJSTSD-12-2018-0063
  • Yoon, S.M., Mamun, M.A., Uddin, G.S., & Kang, S.H. (2019). Network connectedness and net spillover between financial commodity markets. North American Journal of Economics and Finance, 48, 801-818. doi: 10.1016/j.najef.2018.08.012
  • Yu, L., Li, J., & Tang, L. (2015). Dynamic volatility spillover effect analysis between carbon market and crude oil market: A DCC-ICSS approach. International Journal Global Energy Issues, 38(4/5/6), 242-256.
  • Zhang, P., Sha, Y., & Xu, Y. (2021). Stock market volatility spillovers in G7 and BRIC. Emerging Markets Finance and Trade, 57(7), 2107-2119. doi: 10.1080/1540496X.2021.1908256
Toplam 53 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Finansal Piyasalar ve Kurumlar
Bölüm Araştırma Makalesi
Yazarlar

Meltem Kılıç 0000-0001-8978-9076

Yayımlanma Tarihi 30 Haziran 2025
Gönderilme Tarihi 17 Ekim 2024
Kabul Tarihi 17 Şubat 2025
Yayımlandığı Sayı Yıl 2025

Kaynak Göster

APA Kılıç, M. (2025). BRICS-T HİSSE SENEDİ PİYASALARI VE KÜRESEL FİNANSAL GÖSTERGELER ARASINDAKİ VOLATİLİTE ETKİLEŞİMİ. Anadolu Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 26(2), 109-134. https://doi.org/10.53443/anadoluibfd.1569090


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