Impact of Predictability on Traders in Financial Market

Abstract

The growth of artificial intelligence (AI) is changing financial markets. This growth increases accuracy in predictions and affects decision-making in trading, analyses, and portfolio management. The purpose of this study is to explore the use, advantages, and disadvantages of AI in finance. The evaluation looked at whether AI could make prediction more accurate, what efficacy various AI models hold, and what ethical challenges come with AI’s use. The goal was to see whether AI could help with financial decision-making using data, and at the same time, human rationality. Insights were garnered through semi-structured interviews of ten financial professionals, including traders, analysts, and portfolio managers who actively use AI tools. Researcher used thematic analysis approach to determine responses of participants and interpret them. Key developments focused on how safe AI technology can predict results better, that not all AI models are equally useful, and ethical issues such as algorithmic bias and transparency. Through purposive sampling, the chosen subjects had significant experience with AI technologies which made it convenient to study its applications in financial markets. The results showed that AI technologies significantly enhance prediction accuracy, especially in stable market conditions, although human oversight is still essential in volatile conditions. Neural networks and machine learning algorithms are the most effective models, although these depend on the quality of input data and need to be recalibrated regularly. The presence of bias in the algorithms and their untransparency was pointed out as an ethical challenge which will call for ethical guidelines and periodic auditing of AI. The study showed that while it is a great asset to aid in financial prediction, AI should not be used in it entirely. It is to note that there are ethical factors involved in its integration.