The Impact of Artificial Intelligence in Enhancing Predictive Analytics for Stock Trading

Constantinos Challoumis

MPRA Paper from University Library of Munich, Germany

Abstract: Predictive analytics, possessing the potential to forecast future outcomes utilizing analysis of past data, is an emerging popular tool in financial trading. Stock trading often involves high uncertainty due to unpredictability arising from various unpredictable market conditions. Therefore, developing models to predict stock trends has been an important research concern. As a part of the data-driven approach, this predominantly focuses on predictive analytics, the analysis of multimedia financial data in quantitative terms. Market data metrics like opening price, highest price, lowest stock price, and closing price represent the daily activities of a particular stock traded in a particular stock trading, request data with the self-explanation of these terminologies. It is known that history tends to repeat itself. Similarly, the stock market works in a means of cycle, where it creates some repetitive patterns over time. Professional traders in the stock trading industry believe that when these patterns are observed, the stock trend is predicted.

Keywords: stock trading; economics; AI; analytics (search for similar items in EconPapers)
JEL-codes: E0 E1 E2 (search for similar items in EconPapers)
Date: 2025-02-28
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