참고문헌
- Scarsi, Roberta. 2007. "The Bulk Shipping Business: Market Cycles and Shipowners' Biases." Maritime Policy & Management 34(6):577-590. https://doi.org/10.1080/03088830701695305
- Chiste, Claudio, and Gary Van Vuuren. 2014. "Investigating the Cyclical Behavior of the Dry Bulk Shipping Market." Maritime Policy & Management 41(1):1-19. https://doi.org/10.1080/03088839.2013.780216
- Courbariaux, Matthieu, et al. 2016. "Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1." arXiv, preprint arXiv:1602.02830:1-11.
- Cullinane, K. P. B., K. J. Mason, and M. Cape. 1999. "A Comparison of Models for Forecasting the Baltic Freight Index: Box-Jenkins Revisited." International Journal of Maritime Economics 1(2):15-39. https://doi.org/10.1057/ijme.1999.10
- Elman, Jeffrey L. 1990. "Finding Structure in Time." Cognitive Science 14(2):179-211. https://doi.org/10.1207/s15516709cog1402_1
- Fan, Yong Hui, Yu Wei Xing, and Hua Long Yang. 2014. "Prediction of Baltic Capesize Freight Index Based on GARCH Model." In Applied Mechanics and Materials 488:1494-1497. https://doi.org/10.4028/www.scientific.net/AMM.488-489.1494
- Geman, Hélyette, and William O. Smith. 2012. "Shipping Markets and Freight Rates: An Analysis of the Baltic Dry Index." Journal of Alternative Investments 15(1):98-109.
- HAN, Minsoo. 2019. "Prediction of Baltic Dry Index by Applications of Long Short-Term Memory Recurrent Neural Network Architectures." M.S. thesis., Korea Maritime and Ocean University.
- Hochreiter, Sepp, and Jurgen Schmidhuber. 1997. "Long short-term memory." Neural Computation, 9(8):1735-1780. https://doi.org/10.1162/neco.1997.9.8.1735
- Hochreiter, Sepp, et al. 2001. "Gradient Flow in Recurrent Nets: the Difficulty of Learning Long-term Dependencies." 1-15.
- Jordan, Michael I. 1997. "Serial Order: A Parallel Distributed Processing Approach." In Advances in Psychology 121:471-495. https://doi.org/10.1016/S0166-4115(97)80111-2
- Kavussanos, Manolis G., and Amir H. Alizadeh-M. 2001. "Seasonality Patterns in Dry Bulk Shipping Spot and Time Charter Freight Rates." Transportation Research Part E: Logistics and Transportation Review 37(6):443-467. https://doi.org/10.1016/S1366-5545(01)00004-7
- Kavussanos, Manolis G., and Amir H. Alizadeh-M. 2002. "Seasonality Patterns in Tanker Spot Freight Rate Markets." Economic Modelling 19(5):747-782. https://doi.org/10.1016/S0264-9993(01)00078-5
- Leonov, Yordan, and Ventsislav Nikolov. 2012. "A Wavelet and Neural Network Model for the Prediction of Dry Bulk Shipping Indices." Maritime Economics & Logistics 14(3):319-333. https://doi.org/10.1057/mel.2012.10
- Li, Jun, and Michael G. Parsons. 1997. "Forecasting Tanker Freight Rate using Neural Networks." Maritime Policy & Management 24(1):9-30. https://doi.org/10.1080/03088839700000053
- Lin, Faqin, and Nicholas CS Sim. 2013. "Trade, Income and the Baltic Dry Index." European Economic Review, 59:1-18. https://doi.org/10.1016/j.euroecorev.2012.12.004
- Lyridis, D. V., et al. 2004. "Forecasting Tanker Market using Artificial Neural Networks." Maritime Economics & Logistics 6(2):93-108. https://doi.org/10.1057/palgrave.mel.9100097
- Papailias, Fotis, Dimitrios D. Thomakos, and Jiadong Liu. 2017. "The Baltic Dry Index: cyclicalities, forecasting and hedging strategies." Empirical Economics 52(1):255-282. https://doi.org/10.1007/s00181-016-1081-9
- Signal Trading Group. 2011(revised in 2012). Bakshi, Gurdip, George Panayotov, and Georgios Skoulakis. "The Baltic Dry Index as a Predictor of Global Stock Rreturns, Commodity Returns, and Global Economic Activity." Accessed December 18. www.signaltradinggroup.com/wp-content/WhitePapers/Baltic Bakshi, Gurdip S. and Panayotov, George and Skoulakis, Georgios, The Baltic Dry Index as a Predictor of Global Stock Returns, Commodity Returns, and Global Economic Activity (January 26, 2011). AFA 2012 Chicago Meetings Paper.
- Thorsen, Ivar Sandvig. 2010. "Dry Bulk Shipping and Business Cycles." M. S. thesis., Norwegian School of Economics and Business Administration.
- Tsioumas, Vangelis, et al. 2017. "A Novel Approach to Forecasting the Bulk Freight Market." The Asian Journal of Shipping and Logistics 33(1):33-41. https://doi.org/10.1016/j.ajsl.2017.03.005
- Uyar, Kaan, and Ahmet Ilhan. 2016. "Long Term Dry Cargo Freight Rates Forecasting by using Recurrent Fuzzy Neural Networks." In: Aliev, R.A. et al., Procedia Computer Science, 12th International Conference on Application of Fuzzy Systems and Soft Computing (ICAFS 2016), Vienna, Austria, August 29-30, 2016, Elsevier: Oxford, United Kingdom, 102:642-647.
- Williams, Ronald J., and Jing Peng. 1990. "An Efficient Gradient-based Algorithm for On-line Training of Recurrent Network Trajectories." Neural Computation 2(4):490-501. https://doi.org/10.1162/neco.1990.2.4.490
- Zeng, Qingcheng, and Chenrui Qu. 2014. "An Approach for Baltic Dry Index Analysis Based on Empirical Mode Decomposition." Maritime Policy & Management 41(3):224-240. https://doi.org/10.1080/03088839.2013.839512
- Zeng, Qingcheng, et al. 2016. "A New Approach for Baltic Dry Index Forecasting Based on Empirical Mode Decomposition and Neural Networks." Maritime Economics & Logistics 18(2):192-210. https://doi.org/10.1057/mel.2015.2
- 2010. "Forecasting Freight Rates: Evidence from the Baltic Exchange Indices and the IMAREX Freight Futures." M.S. Thesis, University of Piraeus.