Stock Market Prediction

Stock market prediction aims to forecast future price movements, a challenging task due to market complexity and inherent noise. Current research heavily utilizes deep learning models, including LSTMs, Transformers, and GANs, often incorporating technical indicators, macroeconomic factors, and sentiment analysis from diverse sources like social media and earnings reports to improve prediction accuracy. These advancements offer potential for more informed investment decisions and refined risk management strategies, though the inherent uncertainty of financial markets remains a significant hurdle. The field is actively exploring hybrid models combining machine learning with human expertise and focusing on probabilistic approaches to better quantify prediction uncertainty.