Bubble Assets in Baltic Exchange Indices

Yıl 2024, Sayı: 19, 14 - 24, 31.05.2024

Savaş Tarkun

https://doi.org/10.29157/etusbed.1441108

Öz

In this study, potential bubble assets in the Baltic stock market indices are investigated. Bubble entities were examined with the Generalized Supremum Augmented Dickey-Fuller (GSADF) test. Considering the study period, bubble assets emerged in late 2021. A bubble has been detected once in the Baltic Capesize Index, once in the Baltic Panamax Index, six times in the Baltic Surpramax Index, and five times in the Baltic Handysize Index on the Baltic Stock Exchange. Bubble assets were obtained in the Baltic Dirty Tanker Index five times and in the Baltic Clean Tanker Index three times. The longest bubble existence among the indices in the study was in the Baltic Handysize Index, which lasted 110 days. Negative effects on the international maritime market and economy and the impact of the maritime sector, which has an impact on world trade, on the general economy are inevitable. Since it tracks the transportation costs of key inputs for infrastructure and energy-intensive industries, it can be said to be a leading indicator of the global economy. It can also have a contagion effect on the commodity market, the energy market, and the overall economy, albeit with a lag. The disruption of the supply chain caused by the pandemic and the subsequent recovery efforts of economies and fluctuations such as the Suez Canal problem are important for the analysis of the international transportation market.

Anahtar Kelimeler

Baltic Exchange, Bubble Assets, GSADF Test

Baltık Borsası Endekslerindeki Balon Varlıkları

Öz

Bu çalışmada, Baltık borsası endekslerindeki potansiyel balon varlıkları araştırılmaktadır. Balon varlıkları Genelleştirilmiş Supremum Artırılmış Dickey-Fuller (GSADF) testi ile incelenmiştir. Çalışma dönemi dikkate alındığında balon varlıkları 2021 yılının sonlarında ortaya çıkmıştır. Baltık borsasında bulunan Baltic Capesize Endeksi’nde 1 kez, Baltic Panamax Endeksi’nde 1 kez, Baltic Surpramax Endeksi’nde 6 kez ve Baltic Handysize Endeksi’nde 5 kez gerçekleşen balon tespit edilmiştir. Baltic Kirli Tanker Endeksi’nde 5 kez ve Baltic Temiz Tanker Endeksi’nde 3 kez gerçekleşen balon varlıkları elde edilmiştir. Çalışmadaki endekslerden en uzun balon varlığı ise Baltic Handysize Endeksi’nde gerçekleşmiş ve 110 gün sürmüştür. Uluslararası denizcilik piyasasının ve ekonomisinin üzerindeki olumsuz etkiler, dünya ticaretinde etkisi bulunan denizcilik sektörünün genel ekonomilere etkisi kaçınılmazdır. Altyapı ve enerji yoğun sanayiler için önemli girdilerin nakliye maliyetlerini takip ettiğinden küresel ekonomi hakkında öncü gösterge niteliğinde olduğu söylenebilir. Ayrıca emtia piyasası, enerji piyasası ve genel ekonomi üzerinde gecikmeli de olsa bulaşıcı etki yaratabilmektedir. Pandemiden dolayı meydana gelen tedarik zincirinin bozulması ve akabinde ekonomilerin toparlanma çabası ile Süveyş Kanalı problemi gibi dalgalanmalar, uluslararası nakliye pazarının incelenmesi açısından önem arz etmektedir.

Anahtar Kelimeler

Baltık Borsası, Balon Varlıkları, GSADF Testi

Kaynakça

• Açık, A., & Başer, S. Ö. (2018). An analytical study on the likely causes of the minor bubbles in the Baltic dry index. International Journal of Logistics Economics and Globalisation, 7(4), 353. https://doi.org/10.1504/ijleg.2018.10018600
• Açık, A., & Başer, S. Ö. (2020). The Effect of Freight Rates on Asset Price Bubbles in Dirty Tanker Market. Transport & Logistics: The International Journal, 20(49), 13–28.
• Açık, A., Başer, S. Ö., & Ertürk, E. (2018). What Triggers the ISTFIX Bubbles? Uluslararası Ekonomi ve Yenilik Dergisi, 4(2), 119–135. https://doi.org/10.20979/ueyd.434031
• Adland, R., Adland, R., Jia, H., & Strandenes, S. (2006). Asset bubbles in shipping? An analysis of recent history in the drybulk market. Maritime Economics and Logistics, 8(3), 223–233. https://doi.org/10.1057/palgrave.mel.9100162
• Ahmed, H., Aslam, F., & Ferreira, P. (2023). Navigating Choppy Waters : Interplay between Financial Stress and Commodity Market Indices. Preprints. https://doi.org/10.20944/preprints202311.1439.v1
• Alizadeh, A. H., & Muradoglu, G. (2011). Stock Market Returns and Shipping Freight Market Information: Yet Another Puzzle! SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1905590
• 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
• Bandyopadhyay, A., & Rajib, P. (2023). The asymmetric relationship between Baltic Dry Index and commodity spot prices: evidence from nonparametric causality-in-quantiles test. Mineral Economics, 36(2), 217–237. https://doi.org/10.1007/s13563-021-00287-y
• Bildirici, M. E., Kayıkçı, F., & 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
• Chen, S., Meersman, H., & Van De Voorde, E. (2010). Dynamic interrelationships in returns and volatilities between Capesize and Panamax markets. Maritime Economics and Logistics, 12(1), 65–90. https://doi.org/10.1057/mel.2009.19
• Chen, S., Zheng, S., & Meersman, H. (2018). Testing for the burst of bubbles in dry bulk shipping market using log periodic power law model. Maritime Business Review, 3(2), 128–144. https://doi.org/10.1108/MABR-12-2017-0033
• Chu, H. ng. (2023). Crude oil prices, container freight rates and dry bulk freight rates: are there short-term and long-term effects on seaborne exports from Taiwan. International Journal of Shipping and Transport Logistics, 17(4), 451–468. https://doi.org/10.1504/IJSTL.2023.136046
• Cocconcelli, L., & Medda, F. (2016). Testing a speculative bubble in the dry bulk shipping market: a multi-factor approach. International Journal of Decision Sciences, Risk and Management, 6(3), 281. https://doi.org/10.1504/ijdsrm.2016.079795
• Dasgupta, S. (2018). Indian shipping industry – an ocean of opportunities. 55th National Maritime Day Celebration Conference, April, 17.
• Erdogan, O., Tata, K., Karahasan, B. C., & Sengoz, M. H. (2013). Dynamics of the co-movement between stock and maritime markets. International Review of Economics and Finance, 25(2), 282–290. https://doi.org/10.1016/j.iref.2012.07.007
• Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383–417.
• Fan, Y., & Xu, J. H. (2011). What has driven oil prices since 2000? A structural change perspective. Energy Economics, 33(6), 1082–1094. https://doi.org/10.1016/j.eneco.2011.05.017
• Hong, H., Torous, W., & Valkanov, R. (2007). Do industries lead stock markets? Journal of Financial Economics, 83(2), 367–396. https://doi.org/10.1016/j.jfineco.2005.09.010
• 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., Khurshid, A., & Köseoğlu, S. D. (2023). Are there bubbles in shipping freight during COVID-19? Research in Transportation Economics, 100(April). https://doi.org/10.1016/j.retrec.2023.101319
• Kuo, P. L., Chiu, C. L., Chen, C. S., & Wang, M. C. (2020). The dynamic relationships between the Baltic dry index and the BRICS stock markets: A wavelet analysis. Asian Economic and Financial Review, 10(3), 340–351. https://doi.org/10.18488/journal.aefr.2020.103.340.351
• Lee, T. T. H., & Yip, T. L. (2018). A cause of oversupply and failure in the shipping market: measuring herding behavior effects. Maritime Policy and Management, 45(8), 995–1006. https://doi.org/10.1080/03088839.2018.1454990
• Lin, F., & Sim, N. C. S. (2013). Trade, income and the Baltic Dry Index. European Economic Review, 59, 1–18. https://doi.org/10.1016/j.euroecorev.2012.12.004
• Luo, B. (2015). Do the sub-indices of the BDI have better predictability for stock market returns than the BDI ? Tilburg University.
• Makridakis, S., Merikas, A., Merika, A., Tsionas, M. G., & Izzeldin, M. (2020). A novel forecasting model for the Baltic dry index utilizing optimal squeezing. Journal of Forecasting, 39(1), 56–68. https://doi.org/10.1002/for.2613
• McPhail, L. L., Du, X., & Muhammad, A. (2012). Disentangling Corn Price Volatility: The Role of Global Demand, Speculation, and Energy. Journal of Agricultural and Applied Economics, 44(3), 401–410. https://doi.org/10.1017/s107407080000050x
• Mileski, J., Clott, C., Galvao, C. B., & Laverne, T. (2020). Technical analysis: the psychology of the market of dry bulk freight rates. Journal of Shipping and Trade, 5(1). https://doi.org/10.1186/s41072-020-00079-7
• Oomen, J. G. M. (2012). The Baltic Dry Index: A predictor of stock market returns? [Tilnurg University]. http://arno.uvt.nl/show.cgi?fid=126903
• Phillips, P. C. B., Shi, S., & Yu, J. (2015). Testing for multiple bubbles: Historical episodes of exuberance and collapse in the S&P 500. International Economic Review, 56(4), 1043–1078. https://doi.org/10.1111/iere.12132
• Phillips, P. C. B., Wu, Y., & Yu, J. (2011). Explosive Behavior in the 1990s Nasdaq: When Did Exuberance Escalate Asset Values? International Economic Review, 52(1), 201–226.
• Ruan, Q., Wang, Y., Lu, X., & Qin, J. (2016). Cross-correlations between Baltic Dry Index and crude oil prices. Physica A: Statistical Mechanics and Its Applications, 453(xxxx), 278–289. https://doi.org/10.1016/j.physa.2016.02.018
• Su, C. W., Wang, K. H., Shao, Q., & Tao, R. (2019). Are there bubbles in the shipping freight market? Maritime Policy and Management, 46(7), 818–830. https://doi.org/10.1080/03088839.2019.1619946
• Yang, J., Ge, Y. E., & Li, K. X. (2022). Measuring volatility spillover effects in dry bulk shipping market. Transport Policy, 125(December 2020), 37–47. https://doi.org/10.1016/j.tranpol.2022.01.018
• Zhang, S., & Pei, L. (2018). Correlation Research of Shanghai Index and the BDI. Advances in Economics, Business and Management Research, 53(Icem 2017), 653–656. https://doi.org/10.2991/icem-17.2018.132