Stock Index

Stock index prediction aims to forecast the future value of a market index, a crucial task with significant financial implications. Current research heavily utilizes deep learning architectures, such as recurrent neural networks (including LSTM and GRU variants) and other advanced models like Deep AR, often incorporating diverse datasets encompassing fundamental, technical, and macroeconomic factors to improve prediction accuracy. These studies highlight the importance of careful data selection, particularly during market crises, and the ongoing search for optimal model architectures and hyperparameter tuning techniques to enhance forecasting performance. The findings contribute to a better understanding of market dynamics and inform more effective investment strategies.