Statistical Evaluation of Algorithmic Trading and Financial Ethics

Abstract

Artificial intelligence integration has ushered in a new era of efficiency and complexity in the world of modern finance. One of the most notable examples of AI in the financial markets is algorithmic trading, which has fundamentally altered how traders operate and how markets behave. The ethical implications of algorithmic trading must be examined as financial systems adopt new technology, posing concerns about accountability, equity, and transparency. This study delves into the complex interplay between ethical considerations in financial markets and algorithmic trading practices. The growing impact of AI on consumer behavior and the pressing need to consider its ethical implications are what spurred me to conduct this investigation. The purpose of this study is to investigate the following question: How does algorithmic trading impact stock returns, and how does this impact pertain to ethical principles in finance? The following sections offer a comprehensive literature review that puts my investigation into context and sheds light on previous studies on algorithmic trading, financial ethics, and their relationship. Afterwards, I'll give a detailed explanation of algorithmic trading, including its history, various approaches, and wider effects on market dynamics. In a similar fashion, I will analyze the components of financial ethics and lay the groundwork for a detailed analysis of how they relate to algorithmic trading techniques. I will then use statistical methods and a complex research design to assess how algorithmic trading affects stock returns. This will give the investigation a quantitative component and enable me to determine the degree of uncertainty surrounding our conclusions thanks to the supporting confidence interval. In conclusion, the paper provides an overview of the main findings, explores their implications for financial ethics, and offers recommendations for further research in this rapidly developing area.