The Role of Artificial Intelligence in Financial Prediction Models for Forecasting Market Trends with Traditional Methods

Abstract

The financial sector, especially in predicting market trends was greatly molded by Artificial Intelligence (AI). In these volatile and data-heavy markets driven by information, AI becomes a competitive edge to analyze large datasets, identify patterns, and predict (in real-time) future market states serving businesses, investors and policy makers alike. In this paper, we investigate some aspects of AI used for forecasting market trends, especially in the machine learning context: time series prediction and sentiment analysis. In this analysis, we pit traditional methods of time-series forecasting (such as autoregressive models) against more advanced AI methods that leverage neural networks and natural language processing (NLP). The findings show that the accuracy and generalisation of AI models are better than conventional approaches, but issues surrounding data quality and model interpretability remain. This research provides a clear demonstration of the important role artificial intelligence plays in contemporary market forecasting and offers valuable clues for further advances in financial prediction models.