Stock price et forecast data from Bloomberg shows the stock

Data from Bloomberg shows the stock price ET forecast for renewable energy stocks trending upward by 3% in Q This morning, the U.S. Air Force awarded the company a $499 million, 10-year research contract. Taking into account the limitations that have been observed in LSTM methods, we propose a structure that addresses the shortcomings of LSTM models. To mitigate the forgetting phenomenon, a transformer-based (Vaswani et al. 2017 ) model is used. Transformer utilizes a matrix that incorporate all previous data in a sequence, determining correlated values of the data. Therefore, it does not suffer from forgetting, however, all data segments should be provided as input, confining the model to a specific attention window (this study, the historical days of the stock). The cornerstone and the key advantage of the transformer despite its memory size (n 2 ) compared to LSTM (n.log(n)), is its ability for parallel computation. This capability has been a driving force behind the recent advancements in AI, with Chat GPT (Open-AI 2022 ) as an example. While transformers have demonstrated exceptional accuracy in large language models (LLMs), their potential can extend to other domains involving time series. To further enhance these model efficiency, feature-extractor models such as CNN-based models can be integrated. The new stock price ET forecast shows industrial stocks may see 1.5% growth in the next month, bolstered by infrastructure spending and manufacturing rebound data from PMI reports.