Company-Specific Deep Learning Models for Next-Day Stock Price Prediction: A Comparative Study

The main contributions of this study are:

• We demonstrate that Encoder-only Transformer outper
forms GRU, CNN-LSTM and CNN-GRU, establishing a
performance baseline for the Bangladeshi capital market.

• We show that company-specific model selection yields
better results than applying a single architecture across
all stocks.

• We provide the first SHAP-based interpretability analysis
of deep learning stock prediction models on DSE data.