Adaptive Variational Mode Decomposition via RIME Optimization and Fuzzy Entropy for PatchTST-Based Financial Time-Series Forecasting

The inherent non-linear, non-stationary, multi-scale nature of financial time-series data makes the task of financial forecasting exceptionally difficult. While deep learning models incorporating decomposition techniques have achieved significant progress in forecasting, their performance heavily re...

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Autores principales:	Jawaria Nasir, Moiz Qureshi, Yasir Hussain, Muhammad Junaid, Javier Linkolk López‐Gonzales, Ronny Ivan Gonzales Medina
Formato:	Artículo
Lenguaje:	inglés
Publicado:	2026
Materias:	variational mode decomposition fuzzy entropy sample entropy permutation entropy PatchTST financial time series forecasting S&P 500 multi-scale decomposition ensemble forecasting multi-horizon forecasting Diebold-Mariano test Stock Market Forecasting Methods Time Series Analysis and Forecasting Forecasting Techniques and Applications
Acceso en línea:	Enlace permanente (DOI o Handle) Registro tomado de OpenAlex, que lo atribuye a la UPeU. Aún no está en el CRIS de la universidad.
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