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Bayesian Deep Learning and Probabilistic Forecasting of Stock Prices

This study investigates the effectiveness of Bayesian probabilistic methods for stock price forecasting on the Johannesburg Stock Exchange by implementing and comparing Gaussian process regression (GPR), Bayesian long short-term memory (Bayesian LSTM), and Bayesian neural networks (BNNs). Using dail...

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Autores principales: Ndivhuwo Nelufhangani, Daniel Maposa
Formato: Artigo
Lenguaje:Inglês
Publicado: MDPI AG 2026-05-01
Colección:Algorithms
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Acceso en línea:https://www.mdpi.com/1999-4893/19/5/391
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