A Deep Learning Framework for Stock Prediction: Sentiment Analysis and Risk Management

We made a practical tool for the prediction of stock prices, as well as for making trades. It uses refined computer programs - particularly inspired by how the brain works - linked with information found from public opinion. This setup combines multiple forecasting models with carefully chosen indicators; it adapts to the changing market conditions and handles potential downsides. Testing on over thirty large American companies between 2015 and 2025. It showed strong results and steady reliability when faced with new data; the predictions were correct around half the time. Trading tests using lifelike scenarios, such as covering fees alongside shifts in price, showed a 65.91% gain with Microsoft stock (Case Stock), coupled with a 0.611 Sharpe ratio. Examining gave such results, and assessing potential dangers revealed that this system is straightforward as well as adjusts well with market changes simultaneously. Ultimately, we are blending advanced technology, unique information sources, along strong safety measures. This proves worthwhile for automated trades.