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News/A Comparative Analysis of Machine Learning Models for Long and Short-Term Forecasting of the Egyptian Stock Market: A Focus on EGX30
arxiv
PublishedJuly 18, 2026 at 4:00 AM
▲bullish

A Comparative Analysis of Machine Learning Models for Long and Short-Term Forecasting of the Egyptian Stock Market: A Focus on EGX30

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2607.14391v1 Announce Type: new Abstract: This study concentrates on predicting stock prices in the Egyptian market, focusing on the EGX30, an influential financial hub in the Middle East. While most research focuses on global stocks, there's a growing need to understand stock trends in develo

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Discussion
Mentioned models
05
  • 01
    K-Nearest Neighbours
  • 02
    Random Forest
  • 03
    Extreme Gradient Boosting (XGBoost)
  • 04
    Long Short-Term Memory (LSTM) Networks
  • 05
    Gated Recurrent Unit (GRU) Networks
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#forecasting#stock-prices#machine-learning#financial-markets

No replies yet. Be first.

Mentioned models
05
  • 01
    K-Nearest Neighbours
  • 02
    Random Forest
  • 03
    Extreme Gradient Boosting (XGBoost)
  • 04
    Long Short-Term Memory (LSTM) Networks
  • 05
    Gated Recurrent Unit (GRU) Networks
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#forecasting#stock-prices#machine-learning#financial-markets

Related coverage

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Originally published on arxiv ↗
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