Cargando…
Hybrid fuzzy inference rules of descent method and wavelet function for volatility forecasting
This research employs the gradient descent learning (FIR.DM) approach as a learning process in a nonlinear spectral model of maximum overlapping discrete wavelet transform (MODWT) to improve volatility prediction of daily stock market prices using Saudi Arabia’s stock exchange (Tadawul) data. The MO...
Autores principales: | Alenezy, Abdullah H., Ismail, Mohd Tahir, Jaber, Jamil J., Wadi, S. AL, Alkhawaldeh, Rami S. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733893/ https://www.ncbi.nlm.nih.gov/pubmed/36490280 http://dx.doi.org/10.1371/journal.pone.0278835 |
Ejemplares similares
-
Improving forecasting accuracy for stock market data using EMD-HW bagging
por: Awajan, Ahmad M., et al.
Publicado: (2018) -
Efficient algorithms for discrete wavelet transform: with applications to denoising and fuzzy inference systems
por: Shukla, K K, et al.
Publicado: (2013) -
A novel investigation of the influence of corporate governance on firms’ credit ratings
por: Alkhawaldeh, Abdullah A. K., et al.
Publicado: (2021) -
Forecasting tourist arrivals by using the adaptive network-based fuzzy inference system
por: Chen, Miao-Sheng, et al.
Publicado: (2010) -
A COVID-19 forecasting system using adaptive neuro-fuzzy inference
por: Ly, Kim Tien
Publicado: (2021)