Ruo-Shan Zheng

An improved Transformer for multivariate stock time-series forecasting that combines feature-gated embedding with a residual prediction head is proposed that performs nearly identically to Persistence on GOOG and is slightly weaker than Persistence and residual XGBoost on MSFT, while consistently outperforming the LSTM and Transformer-based deep-learning baselines.