What do quantitative analysts do? According to Melissa Brown, director of applied sciences at Axioma, quantitative analysts “take the same kinds of data that any kind of investor looks at, whether it’s earnings or book values or cash flows… and look at it in a very systematic and disciplined way. And importantly, given the same set of data they always come up with the same conclusion.” That “systematic and disciplined” approach includes the application of a broad range of complex mathematical formulae and software applications to enormous data sets, so it’s not quite as simple as Brown makes it sound. Perhaps this metaphor offered by Corvin Codirla of Partner Capital comes a little closer to capturing the difficulty level: “There’s nothing more fascinating than knowing that you’re faced with a pile of spaghetti but somehow you managed to disentangle it and it comes out clean.”
Quantitative finance is similar to financial engineering, and the two terms are sometimes used interchangeably although the fields do, in fact, differ in an important way. While both draw from advanced mathematics, computer science, and business to analyze financial markets, quantitative finance is more nearly a pure applied mathematics discipline, while financial engineering more closely considers finance theory and other, more pragmatic business principles. On the theoretical-pragmatic continuum, quantitative finance sits considerably closer to the theoretical pole.
Quantitative finance is a highly specialized STEM field in which an advanced degree should be beneficial to your career advancement. You could pursue an MBA with a quantitative finance concentration, a master’s in finance with a quantitative finance specialization, or a certificate in quantitative finance, but a Master of Science in Quantitative Finance (MSQF or MScQF) will dig deeper and offer more hands-on practice than any of these. If you’re sure you want to build your career as a quant, this master’s is a good choice for you.
The Master of Science in Financial Mathematics (MSFM or MScFM) may be offered through a university’s school of business or through its mathematics department. Core curricula typically cover investment theory, stochastic calculus, financial markets, derivatives, econometrics, risk analysis, portfolio theory, and computer programming.
Currently, only a few schools offer this degree online. These are small online programs that do little more than make content from on-campus courses available to distance learners; don’t expect high-end video or any of the other fancy frills associated with larger, more lucrative graduate programs (e.g. online MBAs). Online programs are great for far-flung students who don’t want to relocate and for part-time students who want to continue working while earning a degree (campus programs tend to be full-time, while online programs are typically designed for part-time students). What you lose in the tradeoff are the increased networking opportunities that on-campus participation facilitates.
The top online Master’s in Quantitative Finance programs
Only three schools in the United States offer the MSFE online. They are:
DePaul University
- Degree: Master of Science in Computational Finance (MSCF)
- Tuition: $850 per credit hour College of Computing and Digital Media (CDM); $1060 per credit hour Kellstadt Graduate School of Business (KGSB)
- Graduation requirements: 52 credit hours
- Core courses: Data Analysis and Regression; Time Series Analysis and Forecasting; Scientific Computing OR Numerical Analysis I; Monte Carlo Algorithms; Financial Accounting; Economics for Decision-Making; Financial Management; Investment Analysis; Portfolio Management; Risk Management; Derivatives Evaluation
- Electives: Master’s Research OR Graduate Internship OR Software Engineering for Financial Markets; one 500+ level course from CDM, KGSB, or the Department of Math
- Features: Offered jointly through CDM and KGSB; all CDM courses available online; some KGSB courses available on-campus only; recorded lectures available online two hours after class ends and remain available until one week after final exam period; STEM-designated program
Johns Hopkins University
- Degree: Master of Science in Financial Mathematics
- Tuition: $4,250 per course; $42,500 to complete the program
- Graduation requirements: 10 courses; nine core courses and one elective
- Core courses: Investment Science; Introduction to Financial Derivatives; Interest Rates and Credit Derivatives; Financial Risk Management and Measurement; Statistical Methods and Data Analysis; Optimization in Finance; Monte Carlo Methods; Time Series Analysis and Dynamic Modeling; Introductory Stochastic Differential Equations with Applications
- Electives: One: Quantitative Portfolio Theory & Performance Analysis OR Financial Engineering and Structured Products
- Features: Offered through Johns Hopkins Whiting School of Engineering; curriculum offers real-world examples in financial derivatives, risk management, data analysis, Monte Carlo methods, and quantitative portfolio theory; Blackboard-based learning management system; Adobe Connect for office hours and other online meetings; course content largely/completely asynchronous (i.e. no live classes)
University of Washington
- Degree: Master of Science in Computational Finance and Risk Management (MSCFRM)
- Tuition: $975 per credit; $40,950 to complete the 42-credit program
- Graduation requirements: 42 credits; six core courses and one additional required course; 16 credits in electives (typically four courses)
- Core courses: Investment Science; Financial Data Science; Asset Allocation and Portfolio Management; Options and Other Derivatives; Monte Carlo Methods in Finance; Ethics in the Finance Profession; either Financial Data Access & Analysis with SQL, VBA, Excel OR Optimization Methods in Finance
- Electives include: Machine Learning for Finance; Advanced Trading Systems; Advanced C++ for Finance; FinTech, Blockchain, and Cryptocurrencies; Risk in Financial Institutions; Credit Risk Management; Stochastic Calculus for Quantitative Finance; Energy Markets Analytics and Derivatives
- Features: Part-time online students can complete the program in three years by taking one course per quarter; majority of courses are lecture format, but some are conducted via a web conferencing app; students may stream lectures live or watch archived recordings of lectures at a later time; web conference recordings are audio only; online students take courses with on-campus students and interact with on-campus peers via email, course discussion forums, and web conferencing; program is 100 percent remote; exams may be taken off-campus but must be proctored by a university-approved proctor
One school outside the United States also offer an online master’s in quantitative finance:
University of York
- Degree: Master of Science in Mathematical Finance
- Tuition: £5,680/per stage, £17,040 to complete three-stage program
- Graduation requirements: 120 academic credits; can be completed in 1.5 to three years
- Core courses: Certificate stage: Mathematical Methods of Finance; Discrete Time Modelling and Derivative Securities; Portfolio Theory and Risk Management. Diploma Stage: Stochastic Calculus and Black-Scholes theory; Numerical Computing Techniques in Finance; Modelling of Bonds, Term Structure, and Interest Rate Derivatives. Dissertation stage: dissertation.
- Electives: None
- Features: Offered through Department of Mathematics; one-to-one online “Oxbridge style” tutorials and supervisory sessions; lectures delivered asynchronously with accompanying lecture notes and worked exercises; student interaction facilitated through online discussion forums
Works cited
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About the Author
Tom Meltzer began his career in education publishing at The Princeton Review, where he authored more than a dozen titles (including the company's annual best colleges guide and two AP test prep manuals) and produced the musical podcast The Princeton Review Vocab Minute. A graduate of Columbia University (English major), Tom lives in Chapel Hill, NC.
About the Editor
Tom Meltzer spent over 20 years writing and teaching for The Princeton Review, where he was lead author of the company's popular guide to colleges, before joining Noodle.
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