Forecasting the EUR/USD exchange rate using EEMD in combination with LSTM Algorithm
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DOI: https://doi.org/10.57110/vnu-jeb.v4i3.294Keywords:
EUR/USD exchange rate, ensemble empirical mode decomposition (EEMD), long short-term memory (LSTM)References
Bukowski, S. I., & Bukowska, J. E. (2017). Financial and fiscal crises, prices and EUR/USD rate of exchange. International Journal of Business and Economic Sciences Applied Research (IJBESAR), 10(3).
Bussiere, M. (2013). Exchange rate pass‐through to trade prices: The role of nonlinearities and asymmetries. Oxford Bulletin of Economics and Statistics, 75(5), 731-758.
Chen, Z., Yuan, C., Wu, H., Zhang, L., Li, K., Xue, X., & Wu, L. (2022). An improved method based on EEMD-LSTM to predict missing measured data of structural sensors. Applied Sciences, 12(18), 9027.
Dobrovolny, M., Soukal, I., Lim, K. C., Selamat, A., & Krejcar, O. (2020). Forecasting of FOREX price trend using recurrent neural network-long short-term memory. Conference: Hradec Economic Days 2020.
Galeshchuk, S., & Mukherjee, S. (2017). Deep networks for predicting direction of change in foreign exchange rates. Intelligent Systems in Accounting, Finance and Management, 24(4), 100-110.
Huang, N. E. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: mathematical, physical and engineering sciences.
Huang, W., Nakamori, Y., & Wang, S. Y. (2005). Forecasting stock market movement direction with support vector machine. Computers & operations research, 32(10), 2513-2522.
Janetzko, D. (2014). Using Twitter to model the EUR/USD exchange rate. arXiv preprint arXiv:1402.1624.
Özorhan, M. O., Toroslu, İ. H., & Şehitoğlu, O. T. (2017). A strength-biased prediction model for forecasting exchange rates using support vector machines and genetic algorithms. Soft Computing, 21, 6653-6671.
Pérez-Rodríguez, J. V. (2006). The euro and other major currencies floating against the US dollar. Atlantic Economic Journal, 34, 367-384.
Qu, Y., & Zhao, X. (2019). Application of LSTM neural network in forecasting foreign exchange price. Paper presented at the Journal of Physics: Conference Series.
Ribeiro, G. A. M. (2016). Macroeconomic determinants of international currencies. Master’s thesis.
Shen, F., Chao, J., & Zhao, J. (2015). Forecasting exchange rate using deep belief networks and conjugate gradient method. Neurocomputing, 167, 243-253.
Ulina, M., Purba, R., & Halim, A. (2020). Foreign exchange prediction using CEEMDAN and improved FA-LSTM. The 2020 Fifth International Conference on Informatics and Computing (ICIC).
Van Houdt, G., Mosquera, C., & Nápoles, G. (2020). A review on the long short-term memory model. Artificial Intelligence Review, 53, 5929-5955.
Vukovic, D., & VYKLYUK, V. (2013). Forex predicton with neural network: usd/eur currency pair. Actual Problems of Economics, 10, 251-261.
Wu, Y. X., Wu, Q. B., & Zhu, J. Q. (2019). Improved EEMD-based crude oil price forecasting using LSTM networks. Physica A: Statistical Mechanics and its Applications, 516, 114-124.
Yan, B., & Aasma, M. (2020). A novel deep learning framework: Prediction and analysis of financial time series using CEEMD and LSTM. Expert systems with Applications, 159, 113609.8, 71206-71218.
Yao, J., & Tan, C. L. (2000). A case study on using neural networks to perform technical forecasting of forex. Neurocomputing, 34(1-4), 79-98.
Zhang, B. (2018, July). Foreign exchange rates forecasting with an EMD-LSTM neural networks model. Journal of Physics: Conference Series, 1053(1), p. 012005.
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