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Estimation of World Maritime Trade Volatility with Day of the Week Anomaly: Baltic Dry Index Application

Yıl 2023, , 166 - 188, 29.12.2023
https://doi.org/10.18613/deudfd.1279863

Öz

The shipment of raw materials in the world by sea and the volatility in the Baltic Dry Index (BDI), which is the subject of this trade, and the day anomaly are two important issues. Although there are studies on BDI volatility in the literature, there are not many studies on the day anomaly related to BDI. The aim of this study is to reveal the volatility of the BDI variable used in determining the volume of world maritime trade and to determine the day of the week that causes this volatility. Data of the study includes the observation values for 262 working days for the period of 01 July 2021 – 01 July 2022. By taking the natural logarithmic differences of BDI data, the rate of return of the BDI index was obtained. Using these rates of return, experiments were conducted with various autoregressive conditional heteroscedasticity models and according to the findings obtained, it was concluded that there was an ARCH effect in the BDI variable, that Tuesday had an effect on increasing the volatility in the index and Friday had a decreasing effect.

Kaynakça

  • Açık, A., and Başer, S. Ö. (2017). The relationship between freight revenues and vessel disposal decisions. Ekonomi, Politika & Finans Araştırmaları Dergisi, 2(2), 96–112. https://doi.org/10.30784/epfad.363721
  • Açık, A., and Başer, S. Ö. (2018). Baltık Kuru Yük Endeksi etkin mi? [Is Baltic Dry Index efficient?]. Journal of Yaşar University, 13(50), 140–149. https://doi.org/10.19168/jyasar.368149
  • Ådland, A. O. S., and Koekebakker, S. (2004). Market efficiency in the second-hand market for bulk ships. Maritime Economics and Logistics, 6(1), 1–15. https://doi.org/10.1057/palgrave.mel.9100092
  • Adland, R., and Strandenes, S. (2006). Market efficiency in the bulk freight market revisited. Maritime Policy and Management, 33(2), 107–117. https://doi.org/10.1080/03088830600612773
  • Alizadeh, A. H., and Nomikos, N. K. (2007). Investment timing and trading strategies in the sale and purchase market for ships. Transportation Research Part B: Methodological, 41(1), 126–143. https://doi.org/10.1016/j.trb.2006.04.002
  • 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
  • Atakan, T. (2008). İstanbul Menkul Kıymetler Borsası’nda haftanın günü etkisi ve ocak ayı anomalilerinin ARCH-GARCH modelleri ile test edilmesi [Testing the day-of-the-week effect and january effect anomalies at Istanbul Stock Exchange with Arch-Garch models]. İstanbul Üniversitesi İşletme Fakültesi Dergisi Istanbul University Journal of the School of Business Administration Cilt, 37(2), 98–110. www.ifdergisi.org
  • Aygün, D. F. (2021). Sermaye piyasalarındaki takvim anomalilerinin Borsa İstanbul’da test edilmesi [Testing the calendar anomalies of capital market in Istanbul Stock Exchange], Yüksek Lisans Tezi, İstanbul Üniversitesi, Sosyal Bilimler Enstitüsü, İstanbul. http://nek.istanbul.edu.tr:4444/ekos/TEZ/ET002633.pdf
  • Bakshi, G. S., Panayotov, G., and Skoulakis, G. (2012). The Baltic Dry Index as a predictor of global stock returns, commodity returns, and global economic activity. AFA 2012 Chicago Meetings Paper. Available at SSRN: https://doi.org/10.2139/ssrn.1787757
  • Barone, E. (1989). The Italian stock market: Efficiency and calendar anomalies. SSRN. Available at SSRN: https://doi.org/10.2139/ssrn.512503
  • Basher, S. A., and Sadorsky, P. (2006). Day-of-the-week effects in emerging stock markets. Applied Economics Letters, 13(10), 621–628. https://doi.org/10.1080/13504850600825238
  • Brooks, C. (2008). Introductory Econometrics for Finance. Cambridge University Press.
  • Bruffaerts, C., Verardi, V., and Vermandele, C. (2014). A generalized boxplot for skewed and heavy-tailed distributions. Statistics and Probability Letters, 95, 110–117. https://doi.org/10.1016/j.spl.2014.08.016
  • Chia, R. C. J., Liew, V. K. Sen, and Wafa, S. A. W. S. K. (2008). Day-ofthe- week effects in selected East Asian stock markets. Economics Bulletin, 7(5).
  • Chiah, M., and Zhong, A. (2019). Day-of-the-week effect in anomaly returns: International evidence. Economics Letters, 182, 90–92. https://doi.org/10.1016/j.econlet.2019.05.042
  • Choudhry, T. (2000). Day of the week effect in emerging Asian stockmarkets: Evidence from the GARCH model. Applied Financial Economics, 10(3), 235–242. https://doi.org/10.1080/096031000331653
  • Cihangir, Ç. K. (2018). Küresel risk algısının küresel ticaret üzerindeki etkisi [ The effect of global risk perception on global trade]. İşletme ve İktisat Çalışmaları Dergisi, 6(1), 1–10.
  • Cross, F. (1973). The Behavior of stock prices on fridays and mondays. Financial Analysts Journal, 29(6), 67–69. https://doi.org/10.2469/faj.v29.n6.67
  • Davidson, S., and Faff, R. (1999). Some additional Australian evidence on the day-of-the-week effect. Applied Economics Letters, 6(4), 247–249. https://doi.org/10.1080/135048599353447
  • Doyle, J. R., and Chen, C. H. (2009). The wandering weekday effect in major stock markets. Journal of Banking and Finance, 33(8), 1388–1399. https://doi.org/10.1016/j.jbankfin.2009.02.002
  • Du Toit, E., Hall, J. H., and Pradhan, R. P. (2018). The day-of-the-week effect: South African stock market indices. African Journal of Economic and Management Studies, 9(2), 197–212. https://doi.org/10.1108/AJEMS- 07-2017-0163
  • Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. https://doi.org/10.2307/1912773
  • Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417.
  • Fan, Y. H., Xing, Y. W., and Yang, H. L. (2014). Prediction of Baltic Capesize Freight Index based on GARCH model. Applied Mechanics and Materials, 488, 1494–1497. https://doi.org/10.4028/www.scientific.net/AMM.488-489.1494
  • French, K. R. (1980). Stock returns and the weekend effect. Journal of Financial Economics, 8, 55–69.
  • Geman, H., and 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
  • Güç, E., Saçan, E., and Kaplan Yildirim, R. (2016). Borsa İstanbul’dahaftanın günü anomalisinin ARCH, GARCH ve OLS modelleri ile test edilmesi [Testing the Day of the week effect anomalies at Istanbul Stock Exchange with ARCH-GARCH-OLS models]. Uluslararası Sosyal Araştırmalar Dergisi, 1084–1094.
  • Höl, A. Ö., Akyıldırım, E., Kılıçaslan, Ş., and Çınar, K. (2022). Baltık Kuru Yük Endeksi, petrol, altın, dolar, MSCI Dünya Endeksi arasındaki volatilite yayılımı [ Volatility spillover between Baltic Dry Index, oil, gold, dollar, and MSCI World Index]. Ekonomi, Politika & Finans Araştırmaları Dergisi, 7(2), 386–406. https://doi.org/10.30784/epfad.1089836
  • Hsiao, Y. J., Chou, H. C., and Wu, C. C. (2014). Return lead–lag and volatility transmission in shipping freight markets. Maritime Policy and Management, 41(7), 697–714. https://doi.org/10.1080/03088839.2013.865849
  • Işığıçok, E. (1994). Zaman Serilerinde Nedensellik Çözümlemesi. Bursa: Uludağ Üniversitesi Basımevi.
  • Jacks, D. S., and Pendakur, K. (2010). Global trade and the maritime transport revolution. The Review of Economics and Statistics, 92(4), 745– 755.
  • Kasra, P. (2021). Monday effect in maritime financial variables: An anomaly in Baltic Exchange Dry Index. International Journal of Maritime Technology, 16(Summer), 87–92.
  • Katris, C., and Kavussanos, M. G. (2021). Time series forecasting methods for the Baltic dry index. Journal of Forecasting, 40(8), 1540–1565. https://doi.org/10.1002/for.2780
  • Kim, C. B. (2016). Impact of exchange rate movements, global economic activity, and the BDI volatility on loaded port cargo throughput in South Korea. Asian Journal of Shipping and Logistics, 32(4), 243–248. https://doi.org/10.1016/j.ajsl.2016.12.008
  • Kiymaz, H., and Berument, H. (2001). The day of the week effect on stock market volatility. Journal of Economics and Finance, 25(2), 363–380.
  • Lakonishok, J., and Levi, M. (1982). Weekend effects on stock returns: A note. American Finance Association, 37(3), 883–889.
  • Li, S., Wei, L., and Wu, H. (2017). Stock market and the Baltic Dry Index:Volatilities and correlations in China’s business cycle. European Financial Management Symposium 2017. https://www.efmaefm.org/0EFMSYMPOSIUM/2017/papers/paper for conference.pdf
  • Nargeleçekenler, M. (2004). Euro kuru satış değerindeki volatilitenin ARCH ve GARCH modelleri ile tahmini [Estimation of volatility in Euro exchange rate sales values with ARCH and GARCH Models]. İstanbul Üniversitesi İktisat Fakültesi Mecmuası, 54(2), 153–179.
  • Pascali, L. (2017). The wind of change: Maritime technology, trade, and economic development. American Economic Review, 107(9), 2821–2854. https://doi.org/10.1257/aer.20140832
  • Pepur, P., Peronja, I., and Laća, S. (2022). Global market factors that impact Baltic Dry Index. Pomorstvo, 36(2), 242–248. https://doi.org/10.31217/p.36.2.8
  • Radivojevic, N., Muhovic, A., Joksimovic, M., & Pimic, 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. https://doi.org/10.20448/journal.501.2021.82.67.72
  • Rossi, M., and Gunardi, A. (2018). Efficient market hypothesis and stock market anomalies: Empirical evidence in four European countries. Journal of Applied Business Research, 34(1), 183–192. https://doi.org/10.19030/jabr.v34i1.10111
  • Sariannidis, N., Galyfianakis, G., & Drimbetas, E. (2015). The effect of financial and macroeconomic factors on the oil market. International Journal of Energy Economics and Policy, 5(4), 1084–1091.
  • Stopford, M. (2008). Maritime Economics 3e. New York: Routledge. Thaler, R. H. (1987). Anomalies: The january effect. Journal of Economic Perspectives, 1(1), 197–201. https://doi.org/10.1257/jep.1.1.197
  • Zaremba, A. (2020). Performance persistence in anomaly returns: Evidence from frontier markets. Emerging Markets Finance and Trade, 56(12), 2852–2873. https://doi.org/10.1080/1540496X.2019.1605594
  • Zeng, Q., and Qu, C. (2014). An approach for Baltic Dry Index analysis based on empirical mode decomposition. Maritime Policy and Management, 41(3), 224–240. https://doi.org/10.1080/03088839.2013.839512
  • Zhang, B., and Li, X. (2006). Do calendar effects still exist in the Chinese stock markets? Journal of Chinese Economic and Business Studies, 4(2), 151–163. https://doi.org/10.1080/14765280600736999
  • Data Source: https://www.investing.com/indices/baltic-dry

Haftanın Günü Anomalisi ile Dünya Deniz Ticareti Oynaklığının Tahmini: Baltık Kuru Yük Endeksi Uygulaması

Yıl 2023, , 166 - 188, 29.12.2023
https://doi.org/10.18613/deudfd.1279863

Öz

Dünyadaki hammaddelerin deniz yoluyla taşınması ve bu ticarete konu olan Baltık Kuru İndeksindeki (BDI) oynaklık ve gün anomalisi iki önemli husustur. Literatürde BDI oynaklığı ile ilgili çalışmalar olmasına rağmen BDI ile ilgili gün anomalisi ile ilgili çok fazla çalışma bulunmamaktadır. Bu çalışmanın amacı, dünya deniz ticaret hacminin belirlenmesinde kullanılan BDI değişkeninin oynaklığını ortaya koymak ve bu oynaklığa neden olan haftanın gününü belirlemektir. Çalışmanın verileri 01 Temmuz 2021 – 01 Temmuz 2022 dönemine ait 262 iş günü gözlem değerlerini içermektedir. BDI verilerinin doğal logaritmik farkları alınarak BDI indeksinin getiri oranı elde edildi. Bu getiri oranları kullanılarak çeşitli otoregresif koşullu değişen varyans modelleri ile deneyler yapılmış ve elde edilen bulgulara göre BDI oynaklık değişkeninde ARCH etkisinin olduğu, Salı gününün oynaklığı arttığının ve Cuma gününün oynaklığı azaldığının sonucuna varılmıştır.

Kaynakça

  • Açık, A., and Başer, S. Ö. (2017). The relationship between freight revenues and vessel disposal decisions. Ekonomi, Politika & Finans Araştırmaları Dergisi, 2(2), 96–112. https://doi.org/10.30784/epfad.363721
  • Açık, A., and Başer, S. Ö. (2018). Baltık Kuru Yük Endeksi etkin mi? [Is Baltic Dry Index efficient?]. Journal of Yaşar University, 13(50), 140–149. https://doi.org/10.19168/jyasar.368149
  • Ådland, A. O. S., and Koekebakker, S. (2004). Market efficiency in the second-hand market for bulk ships. Maritime Economics and Logistics, 6(1), 1–15. https://doi.org/10.1057/palgrave.mel.9100092
  • Adland, R., and Strandenes, S. (2006). Market efficiency in the bulk freight market revisited. Maritime Policy and Management, 33(2), 107–117. https://doi.org/10.1080/03088830600612773
  • Alizadeh, A. H., and Nomikos, N. K. (2007). Investment timing and trading strategies in the sale and purchase market for ships. Transportation Research Part B: Methodological, 41(1), 126–143. https://doi.org/10.1016/j.trb.2006.04.002
  • 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
  • Atakan, T. (2008). İstanbul Menkul Kıymetler Borsası’nda haftanın günü etkisi ve ocak ayı anomalilerinin ARCH-GARCH modelleri ile test edilmesi [Testing the day-of-the-week effect and january effect anomalies at Istanbul Stock Exchange with Arch-Garch models]. İstanbul Üniversitesi İşletme Fakültesi Dergisi Istanbul University Journal of the School of Business Administration Cilt, 37(2), 98–110. www.ifdergisi.org
  • Aygün, D. F. (2021). Sermaye piyasalarındaki takvim anomalilerinin Borsa İstanbul’da test edilmesi [Testing the calendar anomalies of capital market in Istanbul Stock Exchange], Yüksek Lisans Tezi, İstanbul Üniversitesi, Sosyal Bilimler Enstitüsü, İstanbul. http://nek.istanbul.edu.tr:4444/ekos/TEZ/ET002633.pdf
  • Bakshi, G. S., Panayotov, G., and Skoulakis, G. (2012). The Baltic Dry Index as a predictor of global stock returns, commodity returns, and global economic activity. AFA 2012 Chicago Meetings Paper. Available at SSRN: https://doi.org/10.2139/ssrn.1787757
  • Barone, E. (1989). The Italian stock market: Efficiency and calendar anomalies. SSRN. Available at SSRN: https://doi.org/10.2139/ssrn.512503
  • Basher, S. A., and Sadorsky, P. (2006). Day-of-the-week effects in emerging stock markets. Applied Economics Letters, 13(10), 621–628. https://doi.org/10.1080/13504850600825238
  • Brooks, C. (2008). Introductory Econometrics for Finance. Cambridge University Press.
  • Bruffaerts, C., Verardi, V., and Vermandele, C. (2014). A generalized boxplot for skewed and heavy-tailed distributions. Statistics and Probability Letters, 95, 110–117. https://doi.org/10.1016/j.spl.2014.08.016
  • Chia, R. C. J., Liew, V. K. Sen, and Wafa, S. A. W. S. K. (2008). Day-ofthe- week effects in selected East Asian stock markets. Economics Bulletin, 7(5).
  • Chiah, M., and Zhong, A. (2019). Day-of-the-week effect in anomaly returns: International evidence. Economics Letters, 182, 90–92. https://doi.org/10.1016/j.econlet.2019.05.042
  • Choudhry, T. (2000). Day of the week effect in emerging Asian stockmarkets: Evidence from the GARCH model. Applied Financial Economics, 10(3), 235–242. https://doi.org/10.1080/096031000331653
  • Cihangir, Ç. K. (2018). Küresel risk algısının küresel ticaret üzerindeki etkisi [ The effect of global risk perception on global trade]. İşletme ve İktisat Çalışmaları Dergisi, 6(1), 1–10.
  • Cross, F. (1973). The Behavior of stock prices on fridays and mondays. Financial Analysts Journal, 29(6), 67–69. https://doi.org/10.2469/faj.v29.n6.67
  • Davidson, S., and Faff, R. (1999). Some additional Australian evidence on the day-of-the-week effect. Applied Economics Letters, 6(4), 247–249. https://doi.org/10.1080/135048599353447
  • Doyle, J. R., and Chen, C. H. (2009). The wandering weekday effect in major stock markets. Journal of Banking and Finance, 33(8), 1388–1399. https://doi.org/10.1016/j.jbankfin.2009.02.002
  • Du Toit, E., Hall, J. H., and Pradhan, R. P. (2018). The day-of-the-week effect: South African stock market indices. African Journal of Economic and Management Studies, 9(2), 197–212. https://doi.org/10.1108/AJEMS- 07-2017-0163
  • Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. https://doi.org/10.2307/1912773
  • Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417.
  • Fan, Y. H., Xing, Y. W., and Yang, H. L. (2014). Prediction of Baltic Capesize Freight Index based on GARCH model. Applied Mechanics and Materials, 488, 1494–1497. https://doi.org/10.4028/www.scientific.net/AMM.488-489.1494
  • French, K. R. (1980). Stock returns and the weekend effect. Journal of Financial Economics, 8, 55–69.
  • Geman, H., and 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
  • Güç, E., Saçan, E., and Kaplan Yildirim, R. (2016). Borsa İstanbul’dahaftanın günü anomalisinin ARCH, GARCH ve OLS modelleri ile test edilmesi [Testing the Day of the week effect anomalies at Istanbul Stock Exchange with ARCH-GARCH-OLS models]. Uluslararası Sosyal Araştırmalar Dergisi, 1084–1094.
  • Höl, A. Ö., Akyıldırım, E., Kılıçaslan, Ş., and Çınar, K. (2022). Baltık Kuru Yük Endeksi, petrol, altın, dolar, MSCI Dünya Endeksi arasındaki volatilite yayılımı [ Volatility spillover between Baltic Dry Index, oil, gold, dollar, and MSCI World Index]. Ekonomi, Politika & Finans Araştırmaları Dergisi, 7(2), 386–406. https://doi.org/10.30784/epfad.1089836
  • Hsiao, Y. J., Chou, H. C., and Wu, C. C. (2014). Return lead–lag and volatility transmission in shipping freight markets. Maritime Policy and Management, 41(7), 697–714. https://doi.org/10.1080/03088839.2013.865849
  • Işığıçok, E. (1994). Zaman Serilerinde Nedensellik Çözümlemesi. Bursa: Uludağ Üniversitesi Basımevi.
  • Jacks, D. S., and Pendakur, K. (2010). Global trade and the maritime transport revolution. The Review of Economics and Statistics, 92(4), 745– 755.
  • Kasra, P. (2021). Monday effect in maritime financial variables: An anomaly in Baltic Exchange Dry Index. International Journal of Maritime Technology, 16(Summer), 87–92.
  • Katris, C., and Kavussanos, M. G. (2021). Time series forecasting methods for the Baltic dry index. Journal of Forecasting, 40(8), 1540–1565. https://doi.org/10.1002/for.2780
  • Kim, C. B. (2016). Impact of exchange rate movements, global economic activity, and the BDI volatility on loaded port cargo throughput in South Korea. Asian Journal of Shipping and Logistics, 32(4), 243–248. https://doi.org/10.1016/j.ajsl.2016.12.008
  • Kiymaz, H., and Berument, H. (2001). The day of the week effect on stock market volatility. Journal of Economics and Finance, 25(2), 363–380.
  • Lakonishok, J., and Levi, M. (1982). Weekend effects on stock returns: A note. American Finance Association, 37(3), 883–889.
  • Li, S., Wei, L., and Wu, H. (2017). Stock market and the Baltic Dry Index:Volatilities and correlations in China’s business cycle. European Financial Management Symposium 2017. https://www.efmaefm.org/0EFMSYMPOSIUM/2017/papers/paper for conference.pdf
  • Nargeleçekenler, M. (2004). Euro kuru satış değerindeki volatilitenin ARCH ve GARCH modelleri ile tahmini [Estimation of volatility in Euro exchange rate sales values with ARCH and GARCH Models]. İstanbul Üniversitesi İktisat Fakültesi Mecmuası, 54(2), 153–179.
  • Pascali, L. (2017). The wind of change: Maritime technology, trade, and economic development. American Economic Review, 107(9), 2821–2854. https://doi.org/10.1257/aer.20140832
  • Pepur, P., Peronja, I., and Laća, S. (2022). Global market factors that impact Baltic Dry Index. Pomorstvo, 36(2), 242–248. https://doi.org/10.31217/p.36.2.8
  • Radivojevic, N., Muhovic, A., Joksimovic, M., & Pimic, 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. https://doi.org/10.20448/journal.501.2021.82.67.72
  • Rossi, M., and Gunardi, A. (2018). Efficient market hypothesis and stock market anomalies: Empirical evidence in four European countries. Journal of Applied Business Research, 34(1), 183–192. https://doi.org/10.19030/jabr.v34i1.10111
  • Sariannidis, N., Galyfianakis, G., & Drimbetas, E. (2015). The effect of financial and macroeconomic factors on the oil market. International Journal of Energy Economics and Policy, 5(4), 1084–1091.
  • Stopford, M. (2008). Maritime Economics 3e. New York: Routledge. Thaler, R. H. (1987). Anomalies: The january effect. Journal of Economic Perspectives, 1(1), 197–201. https://doi.org/10.1257/jep.1.1.197
  • Zaremba, A. (2020). Performance persistence in anomaly returns: Evidence from frontier markets. Emerging Markets Finance and Trade, 56(12), 2852–2873. https://doi.org/10.1080/1540496X.2019.1605594
  • Zeng, Q., and Qu, C. (2014). An approach for Baltic Dry Index analysis based on empirical mode decomposition. Maritime Policy and Management, 41(3), 224–240. https://doi.org/10.1080/03088839.2013.839512
  • Zhang, B., and Li, X. (2006). Do calendar effects still exist in the Chinese stock markets? Journal of Chinese Economic and Business Studies, 4(2), 151–163. https://doi.org/10.1080/14765280600736999
  • Data Source: https://www.investing.com/indices/baltic-dry
Toplam 48 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Makaleler
Yazarlar

Erkan Işığıçok 0000-0003-4037-0869

Savaş Tarkun 0000-0002-2684-184X

Yayımlanma Tarihi 29 Aralık 2023
Yayımlandığı Sayı Yıl 2023

Kaynak Göster

APA Işığıçok, E., & Tarkun, S. (2023). Estimation of World Maritime Trade Volatility with Day of the Week Anomaly: Baltic Dry Index Application. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 15(2), 166-188. https://doi.org/10.18613/deudfd.1279863
AMA Işığıçok E, Tarkun S. Estimation of World Maritime Trade Volatility with Day of the Week Anomaly: Baltic Dry Index Application. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi. Aralık 2023;15(2):166-188. doi:10.18613/deudfd.1279863
Chicago Işığıçok, Erkan, ve Savaş Tarkun. “Estimation of World Maritime Trade Volatility With Day of the Week Anomaly: Baltic Dry Index Application”. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 15, sy. 2 (Aralık 2023): 166-88. https://doi.org/10.18613/deudfd.1279863.
EndNote Işığıçok E, Tarkun S (01 Aralık 2023) Estimation of World Maritime Trade Volatility with Day of the Week Anomaly: Baltic Dry Index Application. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 15 2 166–188.
IEEE E. Işığıçok ve S. Tarkun, “Estimation of World Maritime Trade Volatility with Day of the Week Anomaly: Baltic Dry Index Application”, Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, c. 15, sy. 2, ss. 166–188, 2023, doi: 10.18613/deudfd.1279863.
ISNAD Işığıçok, Erkan - Tarkun, Savaş. “Estimation of World Maritime Trade Volatility With Day of the Week Anomaly: Baltic Dry Index Application”. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 15/2 (Aralık 2023), 166-188. https://doi.org/10.18613/deudfd.1279863.
JAMA Işığıçok E, Tarkun S. Estimation of World Maritime Trade Volatility with Day of the Week Anomaly: Baltic Dry Index Application. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi. 2023;15:166–188.
MLA Işığıçok, Erkan ve Savaş Tarkun. “Estimation of World Maritime Trade Volatility With Day of the Week Anomaly: Baltic Dry Index Application”. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, c. 15, sy. 2, 2023, ss. 166-88, doi:10.18613/deudfd.1279863.
Vancouver Işığıçok E, Tarkun S. Estimation of World Maritime Trade Volatility with Day of the Week Anomaly: Baltic Dry Index Application. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi. 2023;15(2):166-88.

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