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Volatility Spillover between Baltic Dry Index, Oil, Gold, Dollar, and MSCI World Index

Year 2022, Volume: 7 Issue: 2, 386 - 406, 30.06.2022
https://doi.org/10.30784/epfad.1089836

Abstract

Being informed about the direction of price movements that may occur in financial markets is very important for investors, portfolio managers and those who want to hedge risk. In this study, the volatility spillover relationship between the global indicators such as Baltic Dry Index, oil prices, gold prices, Dollar Index, MSCI World Index was investigated using the TVP-VAR method developed by Antonakakis and Gabauer (2017) using the data for the 02.01.2015-23.12.2021 period. As a result of the research, it is observed that the Baltic Dry Index, Brent oil price and MSCI World Index are the variables that transmit the volatility, while the Gold Ounce price and the Dollar Index are the variables that receive the volatility. While the variable that transmits volatility the most is Brent oil price, the variable that received the most volatility is the Dollar Index. By following the price movements that may occur in Brent oil prices, it will be possible to have information about the price changes of the financial indicators examined. It can be said that the changes in oil prices affect the world trade volume and capital movements. In addition, it has been observed that events such as the Covid-19 pandemic can change the direction of volatility.

References

  • Açık, A. ve Başer, S.Ö. (2018). Baltık Kuru Yük Endeksi etkin mi? Journal of Yaşar University, 13(50), 140-149. https://doi.org/10.19168/jyasar.368149
  • Açık, A., Okutucu, Ö., Efes, K.Ö. and Başer, S.Ö. (2021). Analyzing the impact of interest rate on dry bulk freight market with time-varying causality method. Ekonomi, Politika & Finans Araştırmaları Dergisi, 6(2), 403-417. doi: 10.30784/epfad.798092
  • Antonakakis, N. and Gabauer, D. (2017). Refined measures of dynamic connectedness based on TVP-VAR (MPRA Working Paper No. 78282). Retrieved from https://mpra.ub.uni-muenchen.de/78282/
  • Antonakakis, N., Chatziantoniou, I. and Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84. https://doi.org/10.3390/jrfm13040084
  • Antonakakis, N., Cuñado, J., Filis, G., Gabauer, D. and de Gracia, F.P. (2019a). Oil and asset classes implied volatilities: Dynamic connectedness and investment strategies (SSRN Working Paper No. 3399996). http://dx.doi.org/10.2139/ssrn.3399996
  • Antonakakis, N., Gabauer, D. and Gupta, R. (2019b). International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression. International Review of Financial Analysis, 65, 101382. https://doi.org/10.1016/j.irfa.2019.101382
  • Apergis, N. and Payne, J.E. (2013). New evidence on the information and predictive content of the Baltic Dry Index. International Journal of Financial Studies, 1(3), 62-80. https://doi.org/10.3390/ijfs1030062
  • Bakshi, G., Panayotov, G. and Skoulakis, G. (2010). The Baltic Dry Index as a predictor of global stock returns, commodity returns, and global economic activity (SSRN Working Paper No. 1787757). http://dx.doi.org/10.2139/ssrn.1747345
  • Baltyn, P. (2016). Baltic Dry Index as economic leading indicator in the United States. Paper presented at the Management Knowledge and Learning, Joint International Conference 2016, Technology, Innovation and Industrial Management. Timisoara, Romania. Retrieved from http://www.toknowpress.net/ISBN/978-961-6914-16-1/papers/ML16-037.pdf
  • Bandyopadhyay, A. and Rajib, P. (2021). The asymmetric relationship between Baltic Dry Index and commodity spot prices: Evidence from nonparametric causality-in-quantiles test. Mineral Economics, 1, 1-21. https://doi.org/10.1007/s13563-021-00287-y
  • Barut, A., Görgün, M.R. ve Erdoğdu, A. (2020). Baltık Kuru Yük Endeksi ve Dow Jones Demir-Çelik Endeksi arasındaki ilişki. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 9(3), 3019-3033. doi:10.15869/itobiad.700223
  • Bildirici, M.E., Kayıkçı, F. and Onat, I.Ş. (2015). Baltic Dry Index as a major economic policy indicator: The relationship with economic growth. Procedia-Social and Behavioral Sciences, 210, 416-424. https://doi.org/10.1016/j.sbspro.2015.11.389
  • Bildirici, M., Kayıkçı, F. and Onat, I.Ş. (2016). BDI, gold price and economic growth. Procedia Economics and Finance, 38, 280-286. https://doi.org/10.1016/S2212-5671(16)30200-3
  • Choi, K.H. and Kim, D.Y. (2018). Relationship between Baltic Dry Index and crude oil market. Journal of Korea Port Economic Association, 34(4), 125-140. doi:10.38121/kpea.2018.12.34.4.125
  • Choi, K.H. and Kim, D.Y. (2019). The effect of Baltic Dry Index on the Korean stock price volatility. Journal of Korea Port Economic Association, 35(2), 61-76. Retrieved from https://www.koreascience.or.kr/
  • Cihangir, Ç.K. (2018). Küresel risk algısının küresel ticaret üzerindeki etkisi. İşletme ve İktisat Çalışmaları Dergisi, 6(1), 1-10. Erişim adresi: http://www.isletmeiktisat.com
  • Çağlayan, E. ve Saçaklı, İ. (2006). Satın alma gücü paritesinin geçerliliğinin sıfır frekansta spektrum tahmincisine dayanan birim kök testleri ile incelenmesi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 20(1), 121-137. doi:10.16951/IIBD.95882
  • Diebold, F.X. and Mariano R.S. (1995). Comparing predictive accuracy. Journal of Business Economic Statistics, 13, 253–263. https://doi.org/10.1198/073500102753410444
  • Diebold, F.X. and Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. Economic Journal, 119(534), 158-171. https://doi.org/10.1111/j.1468-0297.2008.02208.x
  • Diebold, F.X. and Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. doi:10.1016/j.ijforecast.2011.02.006
  • Diebold, F.X. and Yilmaz, 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
  • Giannarakis, G., Lemonakis, C., Sormas, A. and Georganakis, C. (2017). The effect of Baltic Dry Index, gold, oil and USA trade balance on Dow Jones Sustainability Index World. International Journal of Economics and Financial Issues, 7(5), 155. Retrieved from https://www.econjournals.com/
  • Han, L., Wan, L. and Xu, Y. (2020). Can the Baltic Dry Index predict foreign exchange rates? Finance Research Letters, 32, 101157. doi:10.1016/j.frl.2019.04.014
  • Kiracı, K. ve Akan, E. (2020). Baltık Kuru Yük Endeksi (BDI) ile seçilmiş makroekonomik değişkenler arasındaki nedensellik ilişkisi. C. Kartal ve M. Kamışlı (Ed.), İşletme ve Finans Yazıları-IV (s. 260-276). İstanbul: Beta Basım Yayım Dağıtım.
  • Koop, G., Pesaran, M.H. and 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
  • Lin, A.J., Chang, H.Y. and Hsiao, J.L. (2019). Does the Baltic Dry Index drive volatility spillovers in the commodities, currency, or stock markets? Transportation Research Part E: Logistics and Transportation Review, 127, 265-283. https://doi.org/10.1016/j.tre.2019.05.013
  • Lin, F. and Sim, N.C. (2013). Trade, income and the Baltic Dry Index. European Economic Review, 59, 1-18. https://doi.org/10.1016/j.euroecorev.2012.12.004
  • Manoharan, M. and Visalakshmi, S. (2019). The interrelation between Baltic Dry Index a practical economic indicator and emerging stock market indices. Afro-Asian Journal of Finance and Accounting, 9(2), 213-224. doi:10.1504/AAJFA.2019.099483
  • Papailias, F., Thomakos, D.D. and Liu, J. (2017). The Baltic Dry Index: Cyclicalities, forecasting and hedging strategies. Empirical Economics, 52(1), 255-282. doi:10.1007/s00181-016-1081-9
  • Pesaran, H.H. and 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
  • Radivojević, N., Muhović, A., Joksimović, M. and Pimić, M. (2021). Examining the impact of movements of the commodity price on the value of the Baltic Dry Index during Covid19 pandemic. Asian Journal of Economics and Empirical Research, 8(2), 67-72. doi:10.20448/journal.501.2021.82.67.72
  • Ruan, Q., Wang, Y., Lu, X. and Qin, J. (2016). Cross-correlations between Baltic Dry Index and crude oil prices. Physica A: Statistical Mechanics and Its Applications, 453, 278-289. doi:10.1016/j.physa.2016.02.018
  • Saraç, M. ve Başar, R. (2015). Amerikan ekonomisindeki borçluluğun altın fiyatlarına etkisi. Düzce Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 5(2), 1-21. Erişim adresi: https://dergipark.org.tr/en/pub/dusbed/
  • Saraç, M., Zeren, F. ve Başar, R. (2015). Küresel altın fiyatlarıyla ABD ek beslenme yardımı harcamaları ve Baltık Kuru Yük Endeksi arasındaki etkileşim. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 44(1), 12-20. Erişim adresi: http://dergipark.ulakbim.gov.tr/iuisletme
  • Sartorius, K., Sartorius, B. and Zuccollo, D. (2018). Does the Baltic Dry Index predict economic activity in South Africa? A review from 1985 to 2016. South African Journal of Economic and Management Sciences, 21(1), 1-9. https://doi.org/ 10.4102/sajems.v21i1.1457
  • Şahan, D., Memişoğlu, R. and Başer, S.Ö. (2018). Predicting Baltic Dry Index with leading indicators. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 10(2), 233-248. https://doi.org/10.18613/deudfd.495820
  • Uğurlu, E. (2009). Durağanlık ve birim kök sınamaları. Ders Notları, 1, 1-17. doi:10.13140/rg.2.1.3262.2561
  • Yılmaz, T. ve Emir, S. (2021). Petrol fiyatları ve Baltık Kuru Yük Endeksinin hisse senedi piyasaları üzerindeki etkilerinin incelenmesi: Ekonometrik bir araştırma. Uluslararası İşletme, Ekonomi ve Yönetim Perspektifleri Dergisi, 5(2), 861-876. doi:10.29228/ijbemp.54935
  • Yildiz, B. and Bucak, U. (2017). Determinants of freight rates: A study on the Baltic Dry Index. İstanbul Gelişim Üniversitesi Sosyal Bilimler Dergisi, 4(ICEFM Special Issue), 17-32. https://doi.org/10.17336/igusbd.317006
  • Zeren, F. ve Kahramaner, H. (2019). Baltık Kuru Yük Endeksi ile İstanbul Navlun Endeksi arasındaki etkileşimin incelenmesi: Ekonometrik bir uygulama. Journal of International Management Educational and Economics Perspectives, 7(1), 68-79. Erişim adresi: https://dergipark.org.tr/en/pub/jimeep/

Baltık Kuru Yük Endeksi, Petrol, Altın, Dolar, MSCI Dünya Endeksi Arasındaki Volatilite Yayılımı

Year 2022, Volume: 7 Issue: 2, 386 - 406, 30.06.2022
https://doi.org/10.30784/epfad.1089836

Abstract

Finansal piyasalarda oluşabilecek fiyat hareketlerinin yönü hakkında bilgi sahibi olmak yatırımcılar, portföy yöneticileri ve riskten korunmak isteyenler için oldukça önemlidir. Finansal piyasalar hakkında tahminlerde bulunabilmek için çeşitli öncü göstergelerden faydalanılmaktadır. Bu çalışmada küresel göstergelerden olan Baltık Kuru Yük Endeksi, petrol fiyatları, altın fiyatları, Dolar Endeksi, MSCI Dünya Endeksi arasındaki volatilite yayılımı ilişkisi 02.01.2015-23.12.2021 dönemi verileri kullanılarak Antonakakis ve Gabauer (2017) tarafından geliştirilen TVP-VAR yöntemiyle araştırılmıştır. Araştırma sonucunda Baltık Kuru Yük Endeksi, Brent petrol fiyatı ve MSCI Dünya Endeksinin volatiliteyi yayan değişkenler olduğu, altın ons fiyatı ile Dolar Endeksinin volatiliteyi alan değişkenler olduğu görülmüştür. Volatiliteyi en çok yayan değişken Brent petrol fiyatı iken volatiliteyi en çok alan değişken de Dolar endeksi olmuştur. Brent petrol fiyatlarında meydana gelebilecek fiyat hareketleri takip edilerek incelenen finansal göstergelerin fiyat değişimleri hakkında bilgi sahibi olunabilecektir. Petrol fiyatlarında meydana gelen değişmelerin dünya ticaret hacmini ve sermaye hareketlerini etkilediği söylenebilmektedir. Ayrıca Covid-19 pandemisi gibi yaşanan olayların volatilitenin yönünü değiştirebileceği gözlemlenmiştir.

References

  • Açık, A. ve Başer, S.Ö. (2018). Baltık Kuru Yük Endeksi etkin mi? Journal of Yaşar University, 13(50), 140-149. https://doi.org/10.19168/jyasar.368149
  • Açık, A., Okutucu, Ö., Efes, K.Ö. and Başer, S.Ö. (2021). Analyzing the impact of interest rate on dry bulk freight market with time-varying causality method. Ekonomi, Politika & Finans Araştırmaları Dergisi, 6(2), 403-417. doi: 10.30784/epfad.798092
  • Antonakakis, N. and Gabauer, D. (2017). Refined measures of dynamic connectedness based on TVP-VAR (MPRA Working Paper No. 78282). Retrieved from https://mpra.ub.uni-muenchen.de/78282/
  • Antonakakis, N., Chatziantoniou, I. and Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84. https://doi.org/10.3390/jrfm13040084
  • Antonakakis, N., Cuñado, J., Filis, G., Gabauer, D. and de Gracia, F.P. (2019a). Oil and asset classes implied volatilities: Dynamic connectedness and investment strategies (SSRN Working Paper No. 3399996). http://dx.doi.org/10.2139/ssrn.3399996
  • Antonakakis, N., Gabauer, D. and Gupta, R. (2019b). International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression. International Review of Financial Analysis, 65, 101382. https://doi.org/10.1016/j.irfa.2019.101382
  • Apergis, N. and Payne, J.E. (2013). New evidence on the information and predictive content of the Baltic Dry Index. International Journal of Financial Studies, 1(3), 62-80. https://doi.org/10.3390/ijfs1030062
  • Bakshi, G., Panayotov, G. and Skoulakis, G. (2010). The Baltic Dry Index as a predictor of global stock returns, commodity returns, and global economic activity (SSRN Working Paper No. 1787757). http://dx.doi.org/10.2139/ssrn.1747345
  • Baltyn, P. (2016). Baltic Dry Index as economic leading indicator in the United States. Paper presented at the Management Knowledge and Learning, Joint International Conference 2016, Technology, Innovation and Industrial Management. Timisoara, Romania. Retrieved from http://www.toknowpress.net/ISBN/978-961-6914-16-1/papers/ML16-037.pdf
  • Bandyopadhyay, A. and Rajib, P. (2021). The asymmetric relationship between Baltic Dry Index and commodity spot prices: Evidence from nonparametric causality-in-quantiles test. Mineral Economics, 1, 1-21. https://doi.org/10.1007/s13563-021-00287-y
  • Barut, A., Görgün, M.R. ve Erdoğdu, A. (2020). Baltık Kuru Yük Endeksi ve Dow Jones Demir-Çelik Endeksi arasındaki ilişki. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 9(3), 3019-3033. doi:10.15869/itobiad.700223
  • Bildirici, M.E., Kayıkçı, F. and Onat, I.Ş. (2015). Baltic Dry Index as a major economic policy indicator: The relationship with economic growth. Procedia-Social and Behavioral Sciences, 210, 416-424. https://doi.org/10.1016/j.sbspro.2015.11.389
  • Bildirici, M., Kayıkçı, F. and Onat, I.Ş. (2016). BDI, gold price and economic growth. Procedia Economics and Finance, 38, 280-286. https://doi.org/10.1016/S2212-5671(16)30200-3
  • Choi, K.H. and Kim, D.Y. (2018). Relationship between Baltic Dry Index and crude oil market. Journal of Korea Port Economic Association, 34(4), 125-140. doi:10.38121/kpea.2018.12.34.4.125
  • Choi, K.H. and Kim, D.Y. (2019). The effect of Baltic Dry Index on the Korean stock price volatility. Journal of Korea Port Economic Association, 35(2), 61-76. Retrieved from https://www.koreascience.or.kr/
  • Cihangir, Ç.K. (2018). Küresel risk algısının küresel ticaret üzerindeki etkisi. İşletme ve İktisat Çalışmaları Dergisi, 6(1), 1-10. Erişim adresi: http://www.isletmeiktisat.com
  • Çağlayan, E. ve Saçaklı, İ. (2006). Satın alma gücü paritesinin geçerliliğinin sıfır frekansta spektrum tahmincisine dayanan birim kök testleri ile incelenmesi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 20(1), 121-137. doi:10.16951/IIBD.95882
  • Diebold, F.X. and Mariano R.S. (1995). Comparing predictive accuracy. Journal of Business Economic Statistics, 13, 253–263. https://doi.org/10.1198/073500102753410444
  • Diebold, F.X. and Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. Economic Journal, 119(534), 158-171. https://doi.org/10.1111/j.1468-0297.2008.02208.x
  • Diebold, F.X. and Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. doi:10.1016/j.ijforecast.2011.02.006
  • Diebold, F.X. and Yilmaz, 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
  • Giannarakis, G., Lemonakis, C., Sormas, A. and Georganakis, C. (2017). The effect of Baltic Dry Index, gold, oil and USA trade balance on Dow Jones Sustainability Index World. International Journal of Economics and Financial Issues, 7(5), 155. Retrieved from https://www.econjournals.com/
  • Han, L., Wan, L. and Xu, Y. (2020). Can the Baltic Dry Index predict foreign exchange rates? Finance Research Letters, 32, 101157. doi:10.1016/j.frl.2019.04.014
  • Kiracı, K. ve Akan, E. (2020). Baltık Kuru Yük Endeksi (BDI) ile seçilmiş makroekonomik değişkenler arasındaki nedensellik ilişkisi. C. Kartal ve M. Kamışlı (Ed.), İşletme ve Finans Yazıları-IV (s. 260-276). İstanbul: Beta Basım Yayım Dağıtım.
  • Koop, G., Pesaran, M.H. and 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
  • Lin, A.J., Chang, H.Y. and Hsiao, J.L. (2019). Does the Baltic Dry Index drive volatility spillovers in the commodities, currency, or stock markets? Transportation Research Part E: Logistics and Transportation Review, 127, 265-283. https://doi.org/10.1016/j.tre.2019.05.013
  • Lin, F. and Sim, N.C. (2013). Trade, income and the Baltic Dry Index. European Economic Review, 59, 1-18. https://doi.org/10.1016/j.euroecorev.2012.12.004
  • Manoharan, M. and Visalakshmi, S. (2019). The interrelation between Baltic Dry Index a practical economic indicator and emerging stock market indices. Afro-Asian Journal of Finance and Accounting, 9(2), 213-224. doi:10.1504/AAJFA.2019.099483
  • Papailias, F., Thomakos, D.D. and Liu, J. (2017). The Baltic Dry Index: Cyclicalities, forecasting and hedging strategies. Empirical Economics, 52(1), 255-282. doi:10.1007/s00181-016-1081-9
  • Pesaran, H.H. and 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
  • Radivojević, N., Muhović, A., Joksimović, M. and Pimić, M. (2021). Examining the impact of movements of the commodity price on the value of the Baltic Dry Index during Covid19 pandemic. Asian Journal of Economics and Empirical Research, 8(2), 67-72. doi:10.20448/journal.501.2021.82.67.72
  • Ruan, Q., Wang, Y., Lu, X. and Qin, J. (2016). Cross-correlations between Baltic Dry Index and crude oil prices. Physica A: Statistical Mechanics and Its Applications, 453, 278-289. doi:10.1016/j.physa.2016.02.018
  • Saraç, M. ve Başar, R. (2015). Amerikan ekonomisindeki borçluluğun altın fiyatlarına etkisi. Düzce Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 5(2), 1-21. Erişim adresi: https://dergipark.org.tr/en/pub/dusbed/
  • Saraç, M., Zeren, F. ve Başar, R. (2015). Küresel altın fiyatlarıyla ABD ek beslenme yardımı harcamaları ve Baltık Kuru Yük Endeksi arasındaki etkileşim. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 44(1), 12-20. Erişim adresi: http://dergipark.ulakbim.gov.tr/iuisletme
  • Sartorius, K., Sartorius, B. and Zuccollo, D. (2018). Does the Baltic Dry Index predict economic activity in South Africa? A review from 1985 to 2016. South African Journal of Economic and Management Sciences, 21(1), 1-9. https://doi.org/ 10.4102/sajems.v21i1.1457
  • Şahan, D., Memişoğlu, R. and Başer, S.Ö. (2018). Predicting Baltic Dry Index with leading indicators. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 10(2), 233-248. https://doi.org/10.18613/deudfd.495820
  • Uğurlu, E. (2009). Durağanlık ve birim kök sınamaları. Ders Notları, 1, 1-17. doi:10.13140/rg.2.1.3262.2561
  • Yılmaz, T. ve Emir, S. (2021). Petrol fiyatları ve Baltık Kuru Yük Endeksinin hisse senedi piyasaları üzerindeki etkilerinin incelenmesi: Ekonometrik bir araştırma. Uluslararası İşletme, Ekonomi ve Yönetim Perspektifleri Dergisi, 5(2), 861-876. doi:10.29228/ijbemp.54935
  • Yildiz, B. and Bucak, U. (2017). Determinants of freight rates: A study on the Baltic Dry Index. İstanbul Gelişim Üniversitesi Sosyal Bilimler Dergisi, 4(ICEFM Special Issue), 17-32. https://doi.org/10.17336/igusbd.317006
  • Zeren, F. ve Kahramaner, H. (2019). Baltık Kuru Yük Endeksi ile İstanbul Navlun Endeksi arasındaki etkileşimin incelenmesi: Ekonometrik bir uygulama. Journal of International Management Educational and Economics Perspectives, 7(1), 68-79. Erişim adresi: https://dergipark.org.tr/en/pub/jimeep/
There are 40 citations in total.

Details

Primary Language Turkish
Subjects Finance
Journal Section Makaleler
Authors

Arife Özdemir Höl 0000-0002-9902-9174

Erdinç Akyıldırım 0000-0003-0102-4111

Şerife Kılıcaslan 0000-0002-8692-8939

Kader Çınar 0000-0003-0619-374X

Publication Date June 30, 2022
Acceptance Date June 27, 2022
Published in Issue Year 2022 Volume: 7 Issue: 2

Cite

APA Özdemir Höl, A., Akyıldırım, E., Kılıcaslan, Ş., Çınar, K. (2022). Baltık Kuru Yük Endeksi, Petrol, Altın, Dolar, MSCI Dünya Endeksi Arasındaki Volatilite Yayılımı. Ekonomi Politika Ve Finans Araştırmaları Dergisi, 7(2), 386-406. https://doi.org/10.30784/epfad.1089836