Optimizing Algorithmic Trading and Financial Crime Detection: Machine Learning Applications in the US Stock Market and Global Transactions

Аннотация

Recently, the integration of machine learning techniques into finance has caused a revolution in both algorithmic trading and the detection of financial crimes. The paper discusses applications of machine learning to optimize algorithmic trading strategies within the US stock market and also addresses the critical issue of financial crime detection in global transactions. In line with that, this paper will explain in detail the methodologies, benefits, and synergizing of some applications of machine learning towards bettering performance and financial security. Based on the findings it was pinpointed that machine learning increases trading efficiency, profitability, detection, and prevention of fraud. Key Words: Algorithmic Trading; Financial Crime Detection; U.S. Stock Market; Machine Learning; Anomaly Detection