AI ALGORITHM IN STOCK MARKET PREDICTION
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Artificial intelligence (AI) has become a revolutionary force in stock market forecasting thanks to its advanced methods for analysing complex, dynamic, and non-linear financial data. In order to identify hidden patterns, correlations, and trends in economic indicators, trading volumes, and stock prices, artificial intelligence (AI) techniques such as neural networks, support vector machines, decision trees, and deep learning architectures outperform traditional statistical models. Time-series forecasting models, particularly recurrent neural networks such as Long Short-Term Memory (LSTM), often capture sequential dependencies in financial data. Machine learning techniques use both historical and real-time data, while natural language processing (NLP) integrates sentiment analysis from financial news and social media to improve forecast accuracy. Reinforcement learning is also useful for optimising trading strategies in real time. Despite challenges like market volatility, overfitting, and external shocks, AI-driven prediction systems provide insightful information, reduce human bias, and enhance risk management. This is a significant development in the field of intelligent financial forecasting.
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MARIA, T. R., THOWSIF, S., RIYAZUDDIN, S. & BHARADWAJ, K. (2026). AI Algorithm in Stock Market Prediction. International Journal of Science, Strategic Management and Technology, 02(04). https://doi.org/10.55041/ijsmt.v2i4.265
MARIA, T., et al.. "AI Algorithm in Stock Market Prediction." International Journal of Science, Strategic Management and Technology, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i4.265.
MARIA, T.,SHAIK THOWSIF,SHAIK RIYAZUDDIN, and KUMBAM BHARADWAJ. "AI Algorithm in Stock Market Prediction." International Journal of Science, Strategic Management and Technology 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i4.265.
References
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