Today's Question: Is a Comeback in Financial Engineering Really That Easy?
1. The Stringent Requirements of Financial Engineering and Financial Math
Looking at data from the previous three years, we can see that the average undergraduate GPA of admitted students was 3.75, 3.8, and 3.66, and the average GRE/GMAT quantitative percentile was around 94.
Additionally, here is a summary of past admitted student backgrounds for UCLA's Financial Engineering program, ranked 11th in financial engineering/financial math in 2019.
We can see that the average undergraduate GPA for admitted students was 3.65, graduate GPA 3.75, average GMAT score 720 (quant section 50), and average GRE quant score 166.
Meanwhile, Baruch College, ranked second in financial engineering this year, released information on previously admitted students—a screen full of Peking University and Tsinghua University graduates with such impressive backgrounds that it's almost intimidating to read through thoroughly.
Given how difficult and demanding financial engineering/financial math programs are, is applying for a Master's in Finance much easier? What are the differences between them?
2. Key Differences Between Financial Engineering/Financial Math and Finance
MSF (Master of Science in Finance)
MSF programs are typically offered by business schools. Among the top 50 universities ranked by U.S. News & World Report, not many offer a Master of Science in Finance (MSF); well-known ones include Princeton, MIT, Vanderbilt, Washington University in St. Louis, Johns Hopkins, USC, and the University of Rochester.
The MSF curriculum typically includes risk management, corporate M&A, financial derivatives, financial statements, corporate decision management, and investment analysis. Its goal is to cultivate a comprehensive understanding of finance, enabling students to research and analyze capital market operations and corporate finance. Most MSF programs do not emphasize in-depth mathematical training (except for Princeton and MIT), making them more suitable for those with some experience in finance and accounting who want to further their education.
MFE (Financial Engineering) / MFF (Financial Mathematics)
At its core, finance is mathematics.
Financial Engineering (MFE) and Financial Mathematics (MMF) are essentially the same field, just named differently at different schools. It is an interdisciplinary domain integrating finance with mathematics, statistics, economics, and computer science, typically taught jointly by business, engineering, and mathematics departments.
Financial engineering extensively uses models and applies mathematical and engineering methods to solve financial problems, including analyzing stock trends, yield curves, pricing various financial derivatives, as well as risk management, portfolio management, and scenario simulation.
With the acceleration of financial innovation, quantitative analysis plays an increasingly vital role in financial markets and investment processes, driving up demand for highly skilled financial engineering professionals. Programs typically last 1–2 years, making it a short-term investment with quick returns.
3. Recommended Financial Engineering/Financial Math and Finance Programs
According to QuantNet's latest 2019 ranking of financial engineering/financial math programs, NYU Tandon School of Engineering's financial engineering program jumped from 12th place in 2018 into the top 10, now ranked 9th, tying with MIT.
As for finance programs, in recent years, an increasing number of U.S. universities have added the MSF program under their business schools to the STEM-designated list, allowing graduates more OPT time to work and intern in the U.S.
By now, do you have a better understanding of financial engineering/financial math? Curious about what tier of programs your GPA, internship experience, and GRE scores could get you into?
We've opened a fast-track evaluation channel for all of you. Students who want an instant application assessment can scan the QR code at the bottom of our homepage to chat one-on-one with a consultant.
