Stock Market Index Prediction Using CEEMDAN-LSTM-BPNN-Decomposition Ensemble Model
This study investigates the forecasting of the Deutscher Aktienindex (DAX) market index by addressing the nonlinear and nonstationary nature of financial time series data using the CEEMDAN decomposition method. The CEEMDAN technique is used to decompose the time series into intrinsic mode functions...
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| Main Authors: | John Kamwele Mutinda, Abebe Geletu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/jama/7706431 |
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