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Stock Price Prediction with GANs & Transformers by winwinstufff is a document available to read on EtoBox.

This paper proposes a novel approach to enhance stock price prediction by integrating generative adversarial networks (GANs) and transformer-based attention mechanisms, addressing limitations of traditional statistical methods. The model incorporates market sentiment and volatility data, aiming to improve prediction accuracy and robustness. Experimental evaluations will compare the proposed method

Author

winwinstufff

Language

EN