2025

Conférence

Second Edition IEEE Afro-Mediterranean Conference on Artificial Intelligence 2025 IEEE AMCAI IEEE AMCAI 2025

this paper presents a novel ensemble
methodology that integrates deep learning models to enhance
the accuracy and robustness of financial volatility forecasts. By
combining Convolutional Neural Networks (CNNs) and GRU
networks, the proposed approach captures both spatial and
temporal patterns in financial time series data. Empirical results
demonstrate the superiority of this ensemble model over
traditional forecasting methods in various financial markets.
Keywords: Volatility Forecasting, Deep Learning, Ensemble
Modeling, CNN, GRU, Financial Time Series

Paper IEEE AMCAI 2025