Stock Market
Stock market prediction aims to forecast price movements, primarily to inform investment decisions and risk management. Current research heavily utilizes machine learning, employing diverse architectures like Long Short-Term Memory (LSTM) networks, transformers, graph neural networks, and quantum-inspired algorithms to analyze vast datasets encompassing historical prices, macroeconomic indicators, social media sentiment, and news articles. These efforts seek to improve prediction accuracy and portfolio optimization, with implications for both academic understanding of market dynamics and practical applications in wealth management and algorithmic trading.
Papers
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