Araştırma Makalesi
BibTex RIS Kaynak Göster

Yıl 2025, Sayı: 43, 72 - 90, 26.12.2025
https://doi.org/10.26650/ekoist.2025.43.1630251
https://izlik.org/JA44MT56GK

Öz

Kaynakça

  • AbduL Aziz, N. S., Vrontos, S. & Hasim, H. M. (2019). EvaLuation of muLtivariate GARCH modeLs in an optimaL asset aLLocation framework. North American Journal of Economics and Finance, 47, 568-596. google scholar
  • BoLLersLev, T. (1990). ModeLLing the coherence in short-run nominaL exchange rates: A MuLtivariate GeneraLized ARCH ModeL. Review of Economics and Statistics, 72, 498-505. google scholar
  • Buyukkara, G., Kucukozmen, C. C. & UysaL, E. T. (2022). OptimaL hedge ratios and hedging effectiveness: An anaLysis of the Turkish futures market. Borsa İstanbul Review, 22(1), 92-102 google scholar
  • CapieLLo, L., EngLe, R. F. Sheppard, K. (2006). Asymmetric dynamics in the correLations of gLobaL equity and bond returns. Journal of Econometrics, 4(4), 537-572. google scholar
  • Chen, Y., Zheng, B. & Qu, F. (2020). ModeLing the nexus of crude oiL, new energy, and rare earth in China: An asymmetric VAR-BEKK (DCC)-GARCH approach. Resources Policy, 65. google scholar
  • CeLik, S. (2012). The more contagion effect on emerging markets: The evidence of DCC-GARCH modeL. Economic Modelling, 29(5), 1946-1959. google scholar
  • Efimova, O. & SerLetis, A. (2014). Energy markets voLatiLity modeLing using GARCH. Energy Economics, 43, 264-273. google scholar
  • EngLe, R. F. (2002). Dynamic conditionaL correLation: A simpLe cLass of muLtivariate GARCH modeLs. Journal of Business and Economic Statistics, 20(3), 339-350. google scholar
  • EngLe, R., Ito, T. & Lin, W.L. (1990). Meteor showers or heat waves? Heteroskedastic intra-daiLy voLatiLity in the foreign exchange market. Econometrlca, 58(3), 525-542. google scholar
  • Gabauer, D. (2020). VoLatiLity impuLse response anaLysis for DCC-GARCH modeLs: The roLe of voLatiLity transmission mechanisms. Journal of Forecastlng, 39, 788-796. google scholar
  • Horpestad, J. B., Lyocsa, S., MoLnar, P. & OLsen, T. B. (2019). Asymmetric voLatiLity in equity markets around the worLd. The North Amerlcan Journal of Economlcs and Flnance, 48, 540-554. google scholar
  • Hou, Y. & Li, S. (2016). Information transmission between U.S. and China index futures markets: An asymmetric DCC GARCH approach. Economlc Modelllng, 52, 884-897. google scholar
  • Jain, P. & SehgaL, S. (2019). An examination of return and voLatiLity spiLLovers between mature equity markets. JournaL of Economics and Finance, 43(1), 180-210. google scholar
  • Kang, S. H., Uddin, G. S., Troster, V. & Yoon, S. (2019). DirectionaL spiLLover effects between ASEAN and worLd stock markets. Journal of Multlnatlonal Flnanclal Management, 52-53. google scholar
  • Kodres, L. E. & Pritsker, M. (2002). A rationaL expectations modeL of financiaL contagion. JournaL of Finance, 57(2), 769-799. google scholar
  • Kroner, K. F. & Ng, V. K. (1998). ModeLing asymmetric comovements of asset returns. The Revlew of Flnanclal Studles, 11(4), 817-844. google scholar
  • Kroner, K. F. & SuLtan, J. (1993). Time-varying distributions and dynamic hedging with foreign currency futures. The Journal of Flnanclal and Quantltatlve Analysls, 28(4), 535-551. google scholar
  • MaLik, F. (2021). VoLatiLity spiLLover between exchange rate and stock returns under voLatiLity shifts. The Quarterly Revlew of Economlcs and Flnance, 80, 605-613. google scholar
  • Mensi, W., NekhiLi, R., Vo, X. V. & Kang, S. H. (2021). OiL and precious metaLs: VoLatiLity transmission, hedging, and safe haven anaLysis from the Asian crisis to the COVID-19 crisis. Economlc Analysls and Pollcy, 71, 73-96. google scholar
  • Moon, G. H. & Yu, W. C. (2010). VoLatiLity spiLLovers between the US and China stock markets: StructuraL break test with symmetric and asymmetric GARCH approaches. Global Economlc Revlew, 39(2), 129-149. google scholar
  • Morales-Zumaquero, A. & Sosvilla-Rivero, S. (2018). Volatility spillovers between foreign exchange and stock markets in industrialized countries. The Quarterly Review of Economics and Finance, 70, 121-136. google scholar
  • Ross, S. A. (1989). Information and voLatiLity: The no-arbitrage martingaLe approach to timing and resoLution irreLevancy. The Journal of Finance, 44(1), 1-17. google scholar
  • Sadorsky, P. (2012). CorreLations and voLatiLity spiLLovers between oiL prices and the stock prices of cLean energy and technoLogy companies. Energy Economics, 34(1), 248-255. google scholar
  • Sikhosana, A. & Aye, G. C. (2018). Asymmetric voLatiLity transmission between the reaL exchange rate and stock returns in South Africa. Economic Analysis and Policy, 60, 1-8. google scholar
  • Su, F. (2021). ConditionaL voLatiLity persistence and voLatiLity spiLLovers in the foreign exchange market. Research in International Business and Finance, 55. google scholar
  • Tsukada, Y., Shimada, J. & Miyakoshi, T. (2017). Bond market integration in East Asia: MuLtivariate GARCH with dynamic conditionaL correLations approach. International Review of Economics and Finance, 51, 193-213. google scholar
  • Yadav, M. P., Sharma, S. & Bhardwaj, I. (2023). VoLatiLity spiLLover between Chinese stock market and seLected emerging economies: A dynamic conditionaL correLation and portfoLio optimization perspective. Asia-Pacific Financial Markets, 30, 427-444. google scholar
  • Yousaf, I. & ALi, S. (2020). The COVID-19 outbreak and high frequency information transmission between major cryptocurrencies: Evidence from the VAR-DCC-GARCH approach. Borsa İstanbul Review, 20(S1), S1-S10. google scholar
  • Wang, P. & Moore, T. (2012). The integration of the credit defauLt swap markets during the US subprime crisis: Dynamic correLation anaLysis. Journal of International Financial Markets, Institutions and Money, 22(1), 1-15. google scholar
  • Warshaw, E. (2020). Asymmetric voLatiLity spiLLover between European equity and foreign exchange markets: Evidence from the frequency domain. International Review of Economics and Finance, 68, 1-14. google scholar
  • Zhang, W., He, X. & Hamori, S. (2022). VoLatiLity spiLLover and investment strategies among sustainabiLity-reLated financiaL indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copuLa approach. International Review of Finan-cial Analysis, 83. google scholar
  • Zhao, H. (2010). Dynamic reLationship between exchange rate and stock price: evidence from China. Research in International Business and Finance, 24, 103-112. google scholar
  • Zhong, Y. & Liu, J. (2021). CorreLations and voLatiLity spiLLovers between China and Southeast Asian stock markets. The Quarterly of Review of Economics and Finance, 81, 57-69. google scholar

Financial Asset Returns and Volatility Spillovers Across Developed Markets: Evidence From The DCC-GARCH Approach

Yıl 2025, Sayı: 43, 72 - 90, 26.12.2025
https://doi.org/10.26650/ekoist.2025.43.1630251
https://izlik.org/JA44MT56GK

Öz

This paper investigates the volatility spillovers between exchange rates and stock returns across three major developed economies: the United States (US), the Euro area (EA), and the United Kingdom (UK). Using daily data from January 1, 2010, to December 31, 2019, this study employs the Dynamic Conditional Correlation Generalized Autore3 gressive Conditional Heteroscedasticity (DCC3GARCH) framework to capture time3varying conditional correlations and inter3market volatility spillovers across financial asset classes. The analysis further computes optimal hedge ratios and portfolio weights to support risk3minimising investment strategies across asset return pairs within each market. The results reveal that volatility spillovers are not significant between foreign exchange markets; however, they are evident across stock markets. Moreover, dynamic correlations among stock markets are consistently positive, whereas correlations in foreign exchange markets are negative over time. Dynamic hedge ratio estimates indicate that short positions are only feasible in the currency markets. Lastly, the portfolio optimisation analysis reveals that, for a $1 portfolio of exchange rate (stock) returns, the US (UK) asset should dominate the portfolio. These findings offer valuable insights for both academics and practitioners, particularly international investors seeking to understand cross3market volatility dynamics among key global financial centres.

Kaynakça

  • AbduL Aziz, N. S., Vrontos, S. & Hasim, H. M. (2019). EvaLuation of muLtivariate GARCH modeLs in an optimaL asset aLLocation framework. North American Journal of Economics and Finance, 47, 568-596. google scholar
  • BoLLersLev, T. (1990). ModeLLing the coherence in short-run nominaL exchange rates: A MuLtivariate GeneraLized ARCH ModeL. Review of Economics and Statistics, 72, 498-505. google scholar
  • Buyukkara, G., Kucukozmen, C. C. & UysaL, E. T. (2022). OptimaL hedge ratios and hedging effectiveness: An anaLysis of the Turkish futures market. Borsa İstanbul Review, 22(1), 92-102 google scholar
  • CapieLLo, L., EngLe, R. F. Sheppard, K. (2006). Asymmetric dynamics in the correLations of gLobaL equity and bond returns. Journal of Econometrics, 4(4), 537-572. google scholar
  • Chen, Y., Zheng, B. & Qu, F. (2020). ModeLing the nexus of crude oiL, new energy, and rare earth in China: An asymmetric VAR-BEKK (DCC)-GARCH approach. Resources Policy, 65. google scholar
  • CeLik, S. (2012). The more contagion effect on emerging markets: The evidence of DCC-GARCH modeL. Economic Modelling, 29(5), 1946-1959. google scholar
  • Efimova, O. & SerLetis, A. (2014). Energy markets voLatiLity modeLing using GARCH. Energy Economics, 43, 264-273. google scholar
  • EngLe, R. F. (2002). Dynamic conditionaL correLation: A simpLe cLass of muLtivariate GARCH modeLs. Journal of Business and Economic Statistics, 20(3), 339-350. google scholar
  • EngLe, R., Ito, T. & Lin, W.L. (1990). Meteor showers or heat waves? Heteroskedastic intra-daiLy voLatiLity in the foreign exchange market. Econometrlca, 58(3), 525-542. google scholar
  • Gabauer, D. (2020). VoLatiLity impuLse response anaLysis for DCC-GARCH modeLs: The roLe of voLatiLity transmission mechanisms. Journal of Forecastlng, 39, 788-796. google scholar
  • Horpestad, J. B., Lyocsa, S., MoLnar, P. & OLsen, T. B. (2019). Asymmetric voLatiLity in equity markets around the worLd. The North Amerlcan Journal of Economlcs and Flnance, 48, 540-554. google scholar
  • Hou, Y. & Li, S. (2016). Information transmission between U.S. and China index futures markets: An asymmetric DCC GARCH approach. Economlc Modelllng, 52, 884-897. google scholar
  • Jain, P. & SehgaL, S. (2019). An examination of return and voLatiLity spiLLovers between mature equity markets. JournaL of Economics and Finance, 43(1), 180-210. google scholar
  • Kang, S. H., Uddin, G. S., Troster, V. & Yoon, S. (2019). DirectionaL spiLLover effects between ASEAN and worLd stock markets. Journal of Multlnatlonal Flnanclal Management, 52-53. google scholar
  • Kodres, L. E. & Pritsker, M. (2002). A rationaL expectations modeL of financiaL contagion. JournaL of Finance, 57(2), 769-799. google scholar
  • Kroner, K. F. & Ng, V. K. (1998). ModeLing asymmetric comovements of asset returns. The Revlew of Flnanclal Studles, 11(4), 817-844. google scholar
  • Kroner, K. F. & SuLtan, J. (1993). Time-varying distributions and dynamic hedging with foreign currency futures. The Journal of Flnanclal and Quantltatlve Analysls, 28(4), 535-551. google scholar
  • MaLik, F. (2021). VoLatiLity spiLLover between exchange rate and stock returns under voLatiLity shifts. The Quarterly Revlew of Economlcs and Flnance, 80, 605-613. google scholar
  • Mensi, W., NekhiLi, R., Vo, X. V. & Kang, S. H. (2021). OiL and precious metaLs: VoLatiLity transmission, hedging, and safe haven anaLysis from the Asian crisis to the COVID-19 crisis. Economlc Analysls and Pollcy, 71, 73-96. google scholar
  • Moon, G. H. & Yu, W. C. (2010). VoLatiLity spiLLovers between the US and China stock markets: StructuraL break test with symmetric and asymmetric GARCH approaches. Global Economlc Revlew, 39(2), 129-149. google scholar
  • Morales-Zumaquero, A. & Sosvilla-Rivero, S. (2018). Volatility spillovers between foreign exchange and stock markets in industrialized countries. The Quarterly Review of Economics and Finance, 70, 121-136. google scholar
  • Ross, S. A. (1989). Information and voLatiLity: The no-arbitrage martingaLe approach to timing and resoLution irreLevancy. The Journal of Finance, 44(1), 1-17. google scholar
  • Sadorsky, P. (2012). CorreLations and voLatiLity spiLLovers between oiL prices and the stock prices of cLean energy and technoLogy companies. Energy Economics, 34(1), 248-255. google scholar
  • Sikhosana, A. & Aye, G. C. (2018). Asymmetric voLatiLity transmission between the reaL exchange rate and stock returns in South Africa. Economic Analysis and Policy, 60, 1-8. google scholar
  • Su, F. (2021). ConditionaL voLatiLity persistence and voLatiLity spiLLovers in the foreign exchange market. Research in International Business and Finance, 55. google scholar
  • Tsukada, Y., Shimada, J. & Miyakoshi, T. (2017). Bond market integration in East Asia: MuLtivariate GARCH with dynamic conditionaL correLations approach. International Review of Economics and Finance, 51, 193-213. google scholar
  • Yadav, M. P., Sharma, S. & Bhardwaj, I. (2023). VoLatiLity spiLLover between Chinese stock market and seLected emerging economies: A dynamic conditionaL correLation and portfoLio optimization perspective. Asia-Pacific Financial Markets, 30, 427-444. google scholar
  • Yousaf, I. & ALi, S. (2020). The COVID-19 outbreak and high frequency information transmission between major cryptocurrencies: Evidence from the VAR-DCC-GARCH approach. Borsa İstanbul Review, 20(S1), S1-S10. google scholar
  • Wang, P. & Moore, T. (2012). The integration of the credit defauLt swap markets during the US subprime crisis: Dynamic correLation anaLysis. Journal of International Financial Markets, Institutions and Money, 22(1), 1-15. google scholar
  • Warshaw, E. (2020). Asymmetric voLatiLity spiLLover between European equity and foreign exchange markets: Evidence from the frequency domain. International Review of Economics and Finance, 68, 1-14. google scholar
  • Zhang, W., He, X. & Hamori, S. (2022). VoLatiLity spiLLover and investment strategies among sustainabiLity-reLated financiaL indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copuLa approach. International Review of Finan-cial Analysis, 83. google scholar
  • Zhao, H. (2010). Dynamic reLationship between exchange rate and stock price: evidence from China. Research in International Business and Finance, 24, 103-112. google scholar
  • Zhong, Y. & Liu, J. (2021). CorreLations and voLatiLity spiLLovers between China and Southeast Asian stock markets. The Quarterly of Review of Economics and Finance, 81, 57-69. google scholar
Toplam 33 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Uygulamalı Makro Ekonometri, Zaman Serileri Analizi
Bölüm Araştırma Makalesi
Yazarlar

Ahmet Usta 0000-0001-9899-8072

Gönderilme Tarihi 30 Ocak 2025
Kabul Tarihi 17 Haziran 2025
Yayımlanma Tarihi 26 Aralık 2025
DOI https://doi.org/10.26650/ekoist.2025.43.1630251
IZ https://izlik.org/JA44MT56GK
Yayımlandığı Sayı Yıl 2025 Sayı: 43

Kaynak Göster

APA Usta, A. (2025). Financial Asset Returns and Volatility Spillovers Across Developed Markets: Evidence From The DCC-GARCH Approach. EKOIST Journal of Econometrics and Statistics, 43, 72-90. https://doi.org/10.26650/ekoist.2025.43.1630251