The Prospects of Artificial Intelligence and Machine Learning in the Stock Market

Abstract

The stock markets are more volatile than they have ever been right now. Information that is publicly available is growing exponentially more often. However, human traders find it difficult to fully utilize such enormous volumes of data. As a result, algorithms for machine learning (ML) and artificial intelligence (AI) use this data to identify even the slightest market irregularities and profit from them. Understanding and evaluating these AI and ML systems' capabilities, constraints, and technological underpinnings is essential to making the most of them. Artificial intelligence drastically changed the stock trading sector. To maximize the potential of these AI systems, it is imperative to comprehend and assess their scope, limits, and technological aspects. The present study highlighted that the machine learning and AI model has to include indicators like the simple moving average and triangular moving average that have a strong link with stock prices. This study also identifies two major issues with this technology: the amount of human labor needed to operate systems and the difficulty in locating enough high-quality data to feed and train them. There is a strong desire to never stop exploring due to the global advancements in technology and industry. The most promising area of stock trading research has been the incorporation of artificial intelligence. Trading with artificial intelligence and machine learning is similar to what fire was to cavemen. Artificial intelligence (AI) enables robotic advisors to analyze vast amounts of data, support trade execution at the best and most profitable prices, analyze projections more accurately, and help trading businesses calculate risks more effectively and provide investors higher returns. Artificial intelligence (AI) is permeating every aspect of our life, frequently without our knowledge.