Interdisciplinary Research at the Nexus of Finance, Economics, Mathematics, and Statistics: A Review

Abstract

The integration of finance, economics, mathematics, and statistics has led to the development of advanced analytical frameworks for understanding financial markets, risk management, and economic policy. This review explores key interdisciplinary approaches, including financial econometrics, quantitative finance, and machine learning applications in economic modeling. Additionally, we discuss the challenges and future directions of interdisciplinary research in this domain, emphasizing the role of big data, artificial intelligence, and computational techniques in shaping modern financial analysis.