Traditional finance, according to financial risk manager Dimitri Bianco, prices assets "based on financial theory and time value of money… you spend time looking at companies, analyzing their accounting, their 10-Ks, and trying to figure out what their cash flows will be in the future." That's all well and good for stocks, bonds, commodities, and other tangible assets, he continues, but how does one value a derivative, "which is more about buying and selling the right to do something" and therefore "can't be priced with the time value of money"?
That's where quantitative finance, "which looks at finance from a much more scientific perspective," comes into play. As Bianco explains, "To do quantitative finance you need a degree in mathematics, statistics, and technology" in order to build "complex models that can do computations in a computer that would take days, weeks, or even months for somebody to do by hand." While "you have to know financial theory as well" to excel in financial engineering, the truly essential qualification is "a degree in mathematics, statistics, and technology," which provide the tools necessary to evaluate the modern assets that drive today's "much more competitive banking industry."
The Master of Science in Quantitative Finance (MSQF or MScQF) is just such a degree. Yes, 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 an MSQF offers the most in-depth training in the tools of the trade and will better equip you to enter the world of quants.
__(Is this you? People who work in quantitative finance are driven, analytical, and extremely intelligent.)__
The degree, which may be offered through a university's school of business or through its mathematics department, covers investment theory, stochastic calculus, financial markets, derivatives, econometrics, risk analysis, portfolio theory, and computer programming. High proficiency in advanced mathematics and computer science are prerequisites to entering this program.
How do you find the program that's best for you? The International Association of Quantitative Finance (IAQF) lists all academic programs in the field (although you may find its list is not always 100 percent up-to-date, it is still a worthwhile resource). Their site includes a handy tool that allows you to compare up to five programs at a time. Also, QuantNet.com ranks the top 30+ financial engineering/quantitative finance programs annually. You should also take a look at our article on the few available online quantitative finance master's programs.
IAQF recommends the following criteria for evaluating MSQF programs: curriculum; practical vs. theoretical training; faculty; resources and facilities; and placement results.
The IAQF does not prescribe any curricular requirements, so you'll want to review the curriculum of each program you consider to make sure it provides sufficient instruction in mathematics, computer science, and business finance. As you review, be aware that some programs emphasize the risk assessment functions of quantitative finance while others lean more toward derivatives valuation. Peruse the curriculum to make sure you're getting the balance you want. Some programs offer areas of specialization—Boston University, for example, allows specialization in asset management, quantitative analytics, risk management, and analytics & research—while others offer only a generalized quantitative finance degree. Some programs offer a wide variety of electives, others only a few or none. If you're interested in a particular elective, ask an admissions counselor how often it is offered; some schools pad their elective lists with infrequently offered courses.
When considering the balance between practical applications and theoretical training, look first at which school or department offers the MSQF degree. Degrees offered through the business school tend to be more practical, those offered through mathematics departments more theoretical. Those offered jointly tend to split the difference. Take a look at the career/placement section of each program's website: those that emphasize theory will likely have more academic placements, while those with a practical bent should have more placements with banks and brokerages. Look also to see what opportunities exist for hands-on experience. Are internships required? Encouraged? Be aware that schools located in big banking and financial centers have access to many more opportunities for off-campus experiential learning.
Quantitative finance faculties can be drawn from academia or from practicing professionals. Most programs employ a mix of the two. You should be able to review faculty biographies online; these will tell you about faculty research and perhaps about instructors' experience in the field. They won't tell you much about how well they teach, however. For that information, you'll need to conduct some independent online digging. Google faculty members' names, restricting your search to sites like Reddit and Quora. These threaded-discussion sites may contain some conversations about specific faculty members' teaching skills. Sites like RateMyProfessors.com are used primarily by undergraduate students, so the information there will likely be less helpful.
Massive computing power drives quantitative finance in the business world, so it is critical that any MSQF program have access to computers that can handle giant data loads and processor-straining apps. Also, what databases can students access through the program? What sort of lab facilities are available? Does the university host research centers dedicated to finance and quantitative analysis, and is the MSQF program actively involved in them? Resources like these are not only useful in their own right, but also good indicators of how committed the university is to supporting its quant programs.
Most MSQF programs post internship and post-graduation placement information on their websites. Look these over carefully, not just for placement rates and median, high, and low salaries, but also to see which employers hire graduates; this will give you some idea where you might wind up after you complete your degree. If a program does not provide placement data on its website, ask an admissions officer why not. There may be a perfectly reasonable explanation (e.g. their students typically are already employed and not looking to change jobs) but it may also indicate that the program does not fare well in the job market.
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