Mathematical Models in Financial Engineering and Risk Analysis

Dear Colleagues,

Applied mathematics is an interdisciplinary field that utilizes mathematical theories and methods to solve practical problems, aiming to optimize real-world decision-making through modeling, analysis, and computation. Its core value lies in providing rigorous quantitative tools to enhance prediction accuracy, reduce uncertainty, and propel technological and economic advancement—particularly in achieving efficient resource allocation and risk control within complex systems. Key theoretical approaches include differential equations (modeling dynamic systems), optimization theory (e.g., linear programming for optimal solutions), probability and statistics (managing randomness), operations research (resource scheduling), and game theory (analyzing strategic interactions). In practice, it is extensively applied in financial engineering (e.g., portfolio optimization and derivative pricing) and artificial intelligence (e.g., machine learning algorithms), significantly improving decision efficiency and system robustness, thus serving as an indispensable cornerstone of modern innovation.

This Special Issue of Mathematics aims to systematically collect the latest application progress of applied mathematical theories and their methods in the fields of financial engineering, financial risk management, and financial risk measurement. Given that the cutting-edge development of financial engineering and risk management driven by artificial intelligence is facing many new challenges, we invite scholars to submit research papers that use the cutting-edge applied mathematics theories to in-depth exploration and solve related practical problems to promote innovation and practice in this field.

Prof. Dr. Tingqiang Chen
Guest Editor

Manuscript Submission Information

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