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Artificial neural networks and the cross-section of equity returns: identifying nonlinear opportunities on the Johannesburg Stock Exchange
This study investigates the potential of Artificial Neural Networks (ANNs) to forecast stock returns on the Johannesburg Stock Exchange (JSE) using fundamental and technical factors. The optimal neural network architecture is explored, considering varying model depths and node counts. The activation...
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| Format: | Thesis |
| Language: | English English |
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Department of Finance and Tax
2026
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