Computational Finance, BS

Program Introduction

The Bachelor's Program in Computational Finance at Carnegie Mellon University (CMU) is an interdisciplinary program that integrates finance, mathematics, statistics, and computer science to provide a deep understanding of financial markets and quantitative financial analysis. The program is designed to equip students with the ability to combine financial theory and advanced computing techniques to solve complex financial problems, analyze financial data, and develop financial models. The Computational Finance major operates through collaboration between the Departments of Mathematical Sciences, Statistics, Economics, the Business School, and the School of Computer Science. This program is designated as a STEM (Science, Technology, Engineering, and Mathematics) field, allowing international students to benefit from up to 36 months of Optional Practical Training (OPT) after graduation. Carnegie Mellon's Computational Finance program provides students with strong theoretical knowledge and practical skills in areas such as mathematical finance, derivative pricing, risk management, portfolio optimization, and algorithmic trading. A unique strength of the program is its balanced emphasis on solid foundations in financial theory alongside advanced programming, data analysis, and machine learning techniques. Students gain experience applying theoretical concepts through hands-on projects using real financial data and scenarios, learning about the latest trends and technologies in the financial industry. Through academic-industry partnerships with financial institutions, investment banks, hedge funds, and technology companies, students acquire the knowledge and skills necessary to address real-world financial challenges.