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Causality Relationship Between Dirty and Clean Tanker Index Volatilities and BRIC Stock Exchanges

Year 2024, , 915 - 936, 25.12.2024
https://doi.org/10.26745/ahbvuibfd.1470589

Abstract

In this study, the relationship between the Baltic Dirty Tanker Index (BDTI) and the Baltic Clean Tanker Index (BCTI) volatility and the returns of BRIC stock markets was investigated by a frequency domain causality test. In this study, which was investigated with daily data for the period 04.01.2013–29.12.2023, an artificial volatility series was first created for dirty tanker and clean tanker indices. The findings show that there is a bidirectional causality between the Brazilian stock market return and dirty tanker volatility in the long term. A one-way causality relationship was found between the Russian stock market and clean tanker volatility in the medium term, and a statistically significant causality relationship was found between the Indian stock market return and dirty tanker volatility in the long and short term. However, no causal relationship was found between Chinese stock market returns and dirty and clean tanker volatility. These results place Russia among the most important oil-exporting countries in the world. Therefore, it has been demonstrated that the information in the past period returns of this country's stock market, especially of dirty tanker ship owners, contains information on the current period values of dirty tanker freight shocks in the long, short, and medium term. The most important reason for the lack of a causal relationship between Chinese stock market returns and the volatility of crude oil and oil by-product freight rates can be shown as China's emphasis on renewable energy policies.

References

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Kirli ve Temiz Tanker Endeksi Volatiliteleri ile BRIC Borsaları Arasındaki Nedensellik İlişkisi

Year 2024, , 915 - 936, 25.12.2024
https://doi.org/10.26745/ahbvuibfd.1470589

Abstract

Bu çalışmada, Baltık Kirli Tanker Endeksi (BDTI) ile Baltık Temiz Tanker Endeksi (BCTI) volatilitesinin BRIC borsalarının getirileri arasındaki ilişki frekans alan nedensellik testi ile araştırılmıştır. 04.01.2013-29.12.2023 dönemine ait günlük veriler ile araştırılan bu çalışmada, öncelikle kirli tanker ve temiz tanker endeksleri için yapay volatilite serisi oluşturulmuştur. Ulaşılan bulgular ise uzun vadede Brezilya borsası getirisi ile kirli tanker volatilitesi arasında çift taraflı nedensellik elde edilmiştir. Rusya borsası ile temiz tanker volatilitesi arasında orta vadede tek yönlü, uzun ve kısa vadede Hindistan borsası getirisi ile kirli tanker volatilitesi arasında istatistiksel olarak anlamlı nedensellik ilişkisi bulunmuştur. Ancak Çin borsası getirisi ile kirli ve temiz tanker volatilitesi arasında herhangi bir nedensellik ilişkisi bulunamamıştır. Bu sonuçlar, Rusya, dünyadaki önemli petrol ihracatçısı ülkeler arasında yer almaktadır. Dolayısıyla, özellikle kirli tanker armatörlerinin bu ülke borsasının geçmiş dönem getirilerindeki bilgilerin kirli tanker navlun şoklarının cari dönem değerlerindeki bilgileri barındırdığını uzun, kısa ve orta vadede ortaya konmuştur. Çin borsa getirisi ile ham petrol ve petrol yan ürünü navlun oranları volatilitesi arasında nedensellik ilişkisinin bulunmamasının en önemli nedeni ise Çin’in yenilenebilir enerji politikalarına ağırlık vermesi olarak gösterilebilir.

References

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  • Alam, M. M., & Uddin, M. G. S. (2009). Relationship between Interest Rate and Stock Price: Empirical Evidence from Developed and Developing Countries. International Journal of Business and Management, 4(3), 43–51. https://doi.org/10.5539/ijbm.v4n3p43.
  • Alizadeh, A. H., & Muradoglu, G. (2014). Stock market efficiency and international shipping-market information. Journal of International Financial Markets, Institutions and Money, 33, 445–461. https://doi.org/10.1016/j.intfin.2014.10.002.
  • Bakshi, G. S., Panayotov, G., & Skoulakis, G. (2011). The Baltic Dry Index as a Predictor of Global Stock Returns, Commodity Returns, and Global Economic Activity. In SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1787757.
  • Bekaert, G., & Engstrom, E. (2010). Inflation and the stock market: Understanding the “Fed Model.” Journal of Monetary Economics, 57(3), 278–294. https://doi.org/10.1016/j.jmoneco.2010.02.004.
  • Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181–192. https://doi.org/10.1016/j.jeconom.2014.05.008.
  • Bhar, R., & Nikolova, B. (2009). Oil prices and equity returns in the BRIC countries. World Economy, 32(7), 1036–1054. https://doi.org/10.1111/j.1467-9701.2009.01194.x.
  • Bodart, V., & Candelon, B. (2009). Evidence of Interdependence and Contagion Using a Frequency Domain Framework. Emerging Markets Review, 10(2), 140–150. https://doi.org/10.1016/j.ememar.2008.11.003.
  • Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31, 307–327. https://doi.org/10.1109/TNN.2007.902962.
  • Bouri, E., Lien, D., Roubaud, D., & Hussain Shahzad, S. J. (2018). Fear Linkages Between the US and BRICS Stock Markets: A Frequency-Domain Causality. International Journal of the Economics of Business, 25(3), 441–454. https://doi.org/10.1080/13571516.2018.1505241.
  • Breitung, J., & Candelon, B. (2006). Testing for Short- and Long-run Causality: A Frequency-Domain Approach. Journal of Econometrics, 132(2), 363–378. https://doi.org/10.1016/j.jeconom.2005.02.004.
  • Chi, J. (2016). Exchange rate and transport cost sensitivities of bilateral freight flows between the US and China. Transportation Research Part A: Policy and Practice, 89, 1–13. https://doi.org/10.1016/j.tra.2016.05.004.
  • Ekanayake, E. M., & Dissanayake, A. (2022). Effects of Real Exchange Rate Volatility on Trade: Empirical Analysis of the United States Exports to BRICS. Journal of Risk and Financial Management, 15(2). https://doi.org/10.3390/jrfm15020073.
  • Erlandsen, U. A., & Gjertsen, F. (2023). Do Shipping Freight Rates Predict Stock Market Return? Norwegian School of Economics.
  • Gavriilidis, K., Kambouroudis, D. S., Tsakou, K., & Tsouknidis, D. A. (2018). Volatility forecasting across tanker freight rates: The role of oil price shocks. Transportation Research Part E: Logistics and Transportation Review, 118(September), 376–391. https://doi.org/10.1016/j.tre.2018.08.012.
  • Geman, H., & Smith, W. O. (2012). Shipping markets and freight rates: An Analysis of the Baltic Dry Index. Journal of Alternative Investments, 15(1), 98–109. https://doi.org/10.3905/jai.2012.15.1.098.
  • Geweke, J. (1982). Measurement of Linear Dependence and Feedback Between Multiple Time Series. Journal of the American Statistical Association, 77(378), 304–313. https://doi.org/10.2307/2287242.
  • Hammoudeh, S., Kang, S. H., Mensi, W., & Nguyen, D. K. (2016). Dynamic Global Linkages of the BRICS Stock Markets with the United States and Europe Under External Crisis Shocks: Implications for Portfolio Risk Forecasting. World Economy, 39(11), 1703–1727. https://doi.org/10.1111/twec.12433.
  • Helmi, M. H., Nazif Catik, A., Kosedagli, B. Y., Kisla, G. S. H., & Akdeniz, C. (2023). The Effects of Energy Prices on Oil-Gas Sectoral Stock Returns for BRIC Countries: Evidence from Space State Models. International Journal of Energy Economics and Policy, 13(6), 430–440. https://doi.org/10.32479/ijeep.14801.
  • Hosoya, Y. (1991). The Decomposition and Measurement of the Interdependency Between Second-Order Stationary Processes. Probability Theory and Related Fields, 88(4), 429–444. https://doi.org/10.1007/BF01192551.
  • Iskenderoglu, Ö., & Akdag, S. et. (2020). Comparison of the Effect of Vix Fear Index on Stock Exchange Indices of Developed and Developing Countries: The G20 Case. South East European Journal of Economics and Business, 15(1), 105–121. https://doi.org/10.2478/jeb-2020-0009.
  • Jing, L., Marlow, P., & Hui, W. (2008). An analysis of freight rate volatility in dry bulk shipping markets. Maritime Policy and Management, 35(3), 237–251. https://doi.org/10.1080/03088830802079987.
  • Khan, K., Su, C. W., Tao, R., & Umar, M. (2021). How Often Do Oil Prices and Tanker Freight Rates Depend on Global Uncertainty? Regional Studies in Marine Science, 48, 102043. https://doi.org/10.1016/j.rsma.2021.102043.
  • Kumar, A., Mallick, S., Mohanty, M. S., & Zampolli, F. (2022). Market Volatility, Monetary Policy and The Term Premium (No. 606).
  • Lakshmi, P., Visalakshmi, S., & Shanmugam, K. (2015). Intensity of shock transmission amid US-BRICS markets. International Journal of Emerging Markets, 10(3), 311–328. https://doi.org/10.1108/IJoEM-04-2013-0063.
  • Laopodis, N. T. (2006). Dynamic Interactions among the Stock Market and Economic Activity. The Financial Review, 41(April 2005), 513–545.
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There are 66 citations in total.

Details

Primary Language Turkish
Subjects Microeconomics (Other)
Journal Section Main Section
Authors

İsmail Koçak 0000-0002-8901-7401

Savaş Tarkun 0000-0002-2684-184X

Mehmet Çınar 0000-0001-8441-243X

Early Pub Date December 15, 2024
Publication Date December 25, 2024
Submission Date April 18, 2024
Acceptance Date August 9, 2024
Published in Issue Year 2024

Cite

APA Koçak, İ., Tarkun, S., & Çınar, M. (2024). Kirli ve Temiz Tanker Endeksi Volatiliteleri ile BRIC Borsaları Arasındaki Nedensellik İlişkisi. Ankara Hacı Bayram Veli Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 26(3), 915-936. https://doi.org/10.26745/ahbvuibfd.1470589