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Egyptian Stock Exchange Prediction Models by Abdelhak Belmekki is a document available to read on EtoBox.

What is Egyptian Stock Exchange Prediction Models about?

- The document presents a study that assesses deep learning models using nonlinear artificial neural networks to predict stock prices on the Egyptian Stock Exchange. - It trains NARX networks using three algorithms - Bayesian regularization, Levenberg-Marquardt, and scaled conjugate gradient - and compares their performance on six Egyptian indices for time horizons from 1 to 30 days ahead. - The results show that Bayesian regularization achieves the best short-term predictions within 3 days, while Levenber

Author

Abdelhak Belmekki

Language

EN