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This market requirements document explores the potential of artificial intelligence (AI) in stock price prediction, an area integral to the financial market's profit-maximization aspirations. Historically, the prediction of stock prices, with its intricate patterns and influences, has posed significant challenges. Traditional techniques like PCA and LSTM have limitations in adapting to the dynamic nature of stock markets. AI, on the other hand, offers transformative possibilities, with its capabilities to process vast data sets, identify patterns, and continuously learn. Drawing parallels from AI's success in other sectors, like healthcare, the essay suggests that AI can revolutionize stock price prediction by offering higher accuracy and adaptability. It underscores the need to combine various AI methodologies for optimized results while also emphasizing the importance of regulating AI applications. In essence, this paper envisions a future where AI becomes the fulcrum of stock price prediction, potentially overhauling the entire financial sector's operations and delivering unparalleled benefits to all stakeholders.
He et al. (Wed,) studied this question.