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Empirical mode decomposition–based least squares support vector regression for foreign exchange rate forecasting

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Cited by:

  1. Zhu, Bangzhu & Ye, Shunxin & Han, Dong & Wang, Ping & He, Kaijian & Wei, Yi-Ming & Xie, Rui, 2019. "A multiscale analysis for carbon price drivers," Energy Economics, Elsevier, vol. 78(C), pages 202-216.
  2. Ozgur Kisi & Levent Latifoğlu & Fatma Latifoğlu, 2014. "Investigation of Empirical Mode Decomposition in Forecasting of Hydrological Time Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4045-4057, September.
  3. Yi-Chen Chung & Hsien-Ming Chou & Chih-Neng Hung & Chihli Hung, 2021. "Using Textual and Economic Features to Predict the RMB Exchange Rate," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(6), pages 1-8.
  4. Kaijian He & Rui Zha & Jun Wu & Kin Keung Lai, 2016. "Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price," Sustainability, MDPI, vol. 8(4), pages 1-11, April.
  5. Nava, Noemi & Di Matteo, Tiziana & Aste, Tomaso, 2018. "Financial time series forecasting using empirical mode decomposition and support vector regression," LSE Research Online Documents on Economics 91028, London School of Economics and Political Science, LSE Library.
  6. He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2018. "Forecasting exchange rate using Variational Mode Decomposition and entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 15-25.
  7. Sun, Shaolong & Wang, Shouyang & Wei, Yunjie, 2019. "A new multiscale decomposition ensemble approach for forecasting exchange rates," Economic Modelling, Elsevier, vol. 81(C), pages 49-58.
  8. Li, Hui & Hong, Lu-Yao & He, Jia-Xun & Xu, Xuan-Guo & Sun, Jie, 2013. "Small sample-oriented case-based kernel predictive modeling and its economic forecasting applications under n-splits-k-times hold-out assessment," Economic Modelling, Elsevier, vol. 33(C), pages 747-761.
  9. Jying-Nan Wang & Jiangze Du & Chonghui Jiang & Kin-Keung Lai, 2019. "Chinese Currency Exchange Rates Forecasting with EMD-Based Neural Network," Complexity, Hindawi, vol. 2019, pages 1-15, October.
  10. Xiaowen Wang & Ying Ma & Wen Li, 2021. "The Prediction of Gold Futures Prices at the Shanghai Futures Exchange Based on the MEEMD-CS-Elman Model," SAGE Open, , vol. 11(1), pages 21582440211, March.
  11. Bai, Yun & Yan, Chuanmiao & Jiang, Fuxin & Wei, Yunjie & Wang, Shouyang, 2026. "Exchange rate forecasting with macroeconomic data: Evidence from a novel comprehensive ensemble approach," Journal of International Money and Finance, Elsevier, vol. 160(C).
  12. Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022. "“An application of deep learning for exchange rate forecasting”," AQR Working Papers 202201, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2022.
  13. Viviane Naimy & Tatiana Abou Chedid & Omar Abou Saleh & Nicolas Bitar, 2025. "Redefining volatility forecasting in the aerospace and defense sector: application of CEEMDAN-GARCH models," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-16, December.
  14. Latha Sreeram & Samie Ahmed Sayed, 2024. "Short-term Forecasting Ability of Hybrid Models for BRIC Currencies," Global Business Review, International Management Institute, vol. 25(3), pages 585-605, June.
  15. Li Xiangfei & Zhang Zaisheng & Huang Chao, 2014. "An EPC Forecasting Method for Stock Index Based on Integrating Empirical Mode Decomposition, SVM and Cuckoo Search Algorithm," Journal of Systems Science and Information, De Gruyter, vol. 2(6), pages 481-504, December.
  16. Noemi Nava & Tiziana Di Matteo & Tomaso Aste, 2018. "Financial Time Series Forecasting Using Empirical Mode Decomposition and Support Vector Regression," Risks, MDPI, vol. 6(1), pages 1-21, February.
  17. Pattnaik, Debidutta & Kumar, Satish & Burton, Bruce & Lim, Weng Marc, 2022. "Economic Modelling at thirty-five: A retrospective bibliometric survey," Economic Modelling, Elsevier, vol. 107(C).
  18. Shahzad, Syed Jawad Hussain & Hoang, Thi Hong Van & Caporin, Massimiliano & Naifar, Nader, 2026. "Volatility spillovers in forex markets and the role of quantitative easing," The North American Journal of Economics and Finance, Elsevier, vol. 81(C).
  19. Tasadduq Imam, 2021. "Model selection for one‐day‐ahead AUD/USD, AUD/EUR forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1808-1824, April.
  20. Linya Huang & Xite Yang & Yongzeng Lai & Ankang Zou & Jilin Zhang, 2024. "Crude Oil Futures Price Forecasting Based on Variational and Empirical Mode Decompositions and Transformer Model," Mathematics, MDPI, vol. 12(24), pages 1-16, December.
  21. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 341-357, August.
  22. Jin, Xuejun & Zhu, Keer & Yang, Xiaolan & Wang, Shouyang, 2021. "Estimating the reaction of Bitcoin prices to the uncertainty of fiat currency," Research in International Business and Finance, Elsevier, vol. 58(C).
  23. Gourav Kumar & Uday Pratap Singh & Sanjeev Jain, 2022. "Swarm Intelligence Based Hybrid Neural Network Approach for Stock Price Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 991-1039, October.
  24. Ke Gong & Yi Peng & Yong Wang & Maozeng Xu, 2018. "Time series analysis for C2C conversion rate," Electronic Commerce Research, Springer, vol. 18(4), pages 763-789, December.
  25. Yu-Sheng Kao & Kazumitsu Nawata & Chi-Yo Huang, 2020. "Predicting Primary Energy Consumption Using Hybrid ARIMA and GA-SVR Based on EEMD Decomposition," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
  26. Zhu, Bangzhu & Han, Dong & Wang, Ping & Wu, Zhanchi & Zhang, Tao & Wei, Yi-Ming, 2017. "Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression," Applied Energy, Elsevier, vol. 191(C), pages 521-530.
  27. Ana Paula Santos Gularte & Danusio Gadelha Guimarães Filho & Gabriel Oliveira Torres & Thiago Carvalho Nunes Silva & Vitor Venceslau Curtis, 2024. "Machine Learning-Based Time Series Prediction at Brazilian Stocks Exchange," Computational Economics, Springer;Society for Computational Economics, vol. 64(4), pages 2477-2508, October.
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