Chapter 3
A Profile of Programs and Curricula with a Financial Engineering Component
INTRODUCTION
As should have been made clear from the preceding chapter on career paths, financial engineers pursue employment in a number of different functional areas that may be thought of as subspecialties within the discipline. As the demand for quantitatively trained finance professionals has grown across many industries, so too have the programs offered by colleges and universities. Today, worldwide, an estimated 5,000 students graduate each year with some substantive training in financial engineering.1 As also noted in the preceding chapter, different jobs within the broader field of quantitative finance require somewhat different skill sets. Employers’ job postings may seek individuals with expertise in derivatives, risk management, mathematical modeling, computer programming, structured finance, and/or other specialized areas. Not surprisingly, many of the programs now offered do not explicitly incorporate the term “financial engineering” in their degree title. Nevertheless, they do provide the requisite training that distinguishes quantitative finance and financial engineering graduates from other degree majors. Even though the program titles and contents vary, for ease of discussion we refer to them all, in this chapter, as financial engineering programs.2
An understanding of the similarities and differences among financial engineering programs is important both to prospective students who are considering enrolling in a quantitative finance program and to employers who are seeking to hire properly trained financial engineers. The differences are also important to practitioners who are required to keep current on emerging trends in the field and to academics who are seeking input to their own programs. Despite the interest that employers, academics, and practitioners should have in program content, this chapter is written, for the most part, for the benefit of the prospective student.
The chapter on financial engineering careers should have helped to broaden the prospective student's appreciation for the diversity of jobs available to graduates trained in financial engineering. It should also have helped to explain why a similar level of diversity has evolved within the programs that offer some type of training in financial engineering. This is important to consider when choosing a program. While this chapter will not rank the various programs and has no opinion on which is “best,” it should be clear that not all programs are created equal in relation to a particular student's academic and professional goals. Likewise, not all programs are created equal with respect to the knowledge base and skill set sought by an employer.
Also important for the student to consider is that, while the aggregate demand for trained financial engineers has increased steadily over the years, the demand for financial engineers in specific niche roles has varied. This variability in demand is a reflection of a business environment that continues to evolve and adapt to changing conditions. For example, in response to the credit crisis that began in 2007, the role of risk management has been in the spotlight throughout the global financial community. Increased demand for competent risk managers and for specialty risk management consulting firms will undoubtedly grow in response. Educational programs will adapt as well, by increasing their focus on risk measurement and risk management. Conversely, the decade prior to the burst of the housing bubble saw a steady increase in demand for financial engineers in structured finance departments, particularly those who could structure collateralized debt obligations backed by home mortgages, commercial mortgages, credit cards, automobile loans, and virtually any other asset with predictable cash flows. As the credit crisis spread in 2007–2008, liquidity for these sorts of assets dried up, and the demand for new structured products virtually disappeared. As a result, the demand for financial engineers to structure these products declined as well. This is not to say that demand for structuring specialists will not return. Indeed, some of the same people hired to structure the products are now working to restructure the products. The upshot of these examples is that the current business climate and expectations about the future business climate should be important to the prospective student when choosing a program.
It is important for the prospective student to consider the recent and expected future evolution of each of the markets and each of the subject areas that relate to financial engineering. Consider, for example, the subject area known as legal risk, which is covered later in this book. Pending regulations around the world threaten to restrict proprietary trading at large banks. For the individual hoping to get a job as a quantitative trader on a proprietary trading desk at a large financial institution, it is important to understand how pending or current legislation may affect each jurisdiction and to plan his/her enrollment and curriculum accordingly.
It is not the goal of this chapter to endorse a particular program. Rather, the purpose of this chapter is to introduce the prospective student to variations among the programs offered worldwide. It is up to the prospective student to identify his or her academic and professional goals and to consider the list of available programs through that lens. This chapter first presents some background information on programs offering training in financial engineering. As noted earlier, these programs carry different labels and are sponsored by different departments at different academic institutions. For example, some programs are offered by engineering schools, others by mathematics departments, and still others by business schools. Next, we discuss the curricula offered across the range of programs including a discussion of required and elective courses, course tracks, internships, research, and faculty. Finally we wrap up with a discussion of the advantages offered by various programs with respect to job placement.
Most of the information offered in this chapter comes directly from the academic institutions offering the programs. We distributed a survey to 150 programs offered by academic institutions worldwide and compiled the responses. A list of programs contacted appears in the Appendix at the end of the chapter. The survey asked for the following information:
- Program contact
- Program website
- Describe awards/recognition of the program
- What aspects of the program distinguish it from similar ones offered at other universities?
- Degrees offered (up to six)
- What are the fundamental and advanced core classes (up to six)?
- What are the available electives (up to six)?
- What course tracks are available (up to six)?
- What type of research is required (up to six)?
- Dean/Department Chair
- Program e-mail address
- Students per faculty member
- Professor/Instructor (up to six)
- Name
- Title
- Department
- Full/part-time
- Areas of interest
- Degrees received
- Number of applications
- Acceptance rate
- Average test scores of accepted students
- Undergraduate students
- Graduate students
- Full-time students
- Part-time students
- Primary nationality of students (up to five)
- Total number of countries represented
- Work experience (up to six jobs)
- Minimum time to complete program
- Job placement
Not every program to which the survey was distributed responded in time to meet our publishing deadline, and the sample lists that appear throughout the chapter as exhibits are not intended to be exhaustive. Further, the information provided in this chapter for each and every program cited is necessarily incomplete. For these reasons, prospective students should thoroughly research any programs they are interested in before making any enrollment decisions. Another useful resource for information on financial engineering programs is the International Association of Financial Engineers (IAFE), which posts information about programs on its website, www.iafe.org.
BACKGROUND INFORMATION ON FINANCIAL ENGINEERING PROGRAMS
While more established programs of study in other disciplines are relatively uniform in nature across academic institutions that offer them, financial engineering is an evolving field of study and distinctly unique, in that degree programs are offered under a variety of names and are sponsored by many different university departments. Program names and sponsoring departments are worth a little elaboration.
Program Name
The first programs offering training in financial engineering were developed as master's programs. Today, most degrees are still offered at the master's level; however, some universities offer training in financial engineering at the bachelor's and doctoral levels. Some universities also offer certificate programs, which are typically geared towards students holding a graduate degree who wish to expand their areas of proficiency.
School | Degree |
Georgia State University (U.S.) | MS in Mathematical Risk Management (MS MRM) |
North Carolina State University (U.S.) | Masters of Financial Mathematics |
University of Westminster (UK) | MSc in Investment and Quantitative Finance |
Lehigh University (U.S.) | Master of Science in Analytical Finance |
Dublin City University (IE) | MSc in Financial and Industrial Mathematics |
Columbia University (U.S.) | MA in Mathematics of Finance |
Case Western Reserve University (U.S.) | MSM Finance |
Oxford University (UK) | MSc in Mathematical and Computational Finance |
University of Twente (NL) | Master in Applied Mathematics |
University of the Witwatersrand– Johannesburg (ZA) | BSc Honours in Advanced Mathematics of Finance |
Boston University School of Management (U.S.) | Ph in Mathematical Finance |
University of Minnesota (U.S.) | Post Bacaulareate Certifications— Fundamentals of Quantitative Finance (FQF) |
Within each of the bachelor’s, master's and doctoral levels, there are a variety of financial engineering-related degrees under names other than “financial engineering.” Often the name of the degree depends on the department or departments sponsoring the degree. The next section will discuss the variety of departments that offer financial engineering–related degrees. Examples of program names that do not include the term “financial engineering” are provided in Exhibit 3.1. Note that this is not a complete list. It is for illustration purposes only.
Department
Financial engineering draws on many disciplines. These include mathematics, statistics, finance, computer science, and engineering. It makes sense, therefore, that financial engineering programs have originated independently within various departments across the spectrum of academic institutions. Examples of departments offering financial engineering-like programs are provided in Exhibit 3.2.
School | Degree | Department |
Columbia University (U.S.) | Master of Science in Financial Engineering | Industrial Engineering and Operations Research Department |
University of Waterloo (CA) | Master of Quantitative Finance | Centre for Advanced Studies in Finance |
The Hong Kong University of Science and Technology (CN) | Master of Science in Mathematics (Financial Mathematics and Statistics) | Department of Mathematics |
Nanyang Technological University (SG) | Master of Science (Financial Engineering) | Nanyang Business School |
Rensselaer Polytechnic University (U.S.) | MS in Financial Engineering and Risk Analytics | Lally School of Management and Technology |
Financial engineering programs are sometimes jointly sponsored by multiple departments within a university. Exhibit 3.3 provides some examples.
School | Degree | Departments |
University of Illinois (U.S.) | Master of Science in Financial Engineering | College of Engineering and College of Business |
University of Dayton (U.S.) | Master's of Financial Mathematics | MBA program and Department of Mathematics |
Bogazici University (TR) | MS in Financial Engineering | Engineering, Management, and Mathematics departments |
University of Birmingham (UK) | MSc in Mathematical Finance | School of Mathematics and Business School's Department of Economics |
Claremont Graduate University (U.S.) | MS Financial Engineering (MSFE) | The Peter F. Drucker Graduate School of Management and The School of Mathematical Sciences |
The department or departments that offer a financial engineering degree are significant factors in determining the program's content. Nevertheless, the content of each program will vary even when programs have similar titles and are offered by offered by similar departments.
CURRICULA
The variety of firms and institutions seeking financial engineers and the resulting variety of programs offered means that prospective students must carefully consider how prepared they can reasonably expect to be for their desired professional field given the strengths and weaknesses of each program. The term “strengths and weaknesses” does not mean “good or bad.” Rather, it is an acknowledgement that some programs focus more on math and less on finance, or more on finance and less on math, have a more theoretical or a more practical focus, offer greater or lesser flexibility with electives, and so on.
Consider the difference between the following two prospective students: Student A has a BS in computer programming and has two years of work experience at a well-respected software development firm. Student B has a BS in Finance and has two years of work experience at an investment banking firm. Both students plan to compete for jobs as quantitative traders. In order to be effective in their desired careers, each student will need to supplement their existing qualifications with a different knowledge base and skill set.
In this section we discuss the similarities and differences in pre-enrollment requirements (prerequisites), required courses and electives, course tracks, and faculty assigned to various programs that offer financial engineering programs.
Pre-Enrollment Requirements
Most programs do not require prior work experience. The nature of required course work completed prior to enrollment varies. Generally, programs look for students who have completed a significant number of courses in either math or finance. Oklahoma State University's (U.S.) Master of Science in Quantitative Financial Economics (MSQFE) program is representative of most programs in this regard:
The MSQFE Program offers a flexible curriculum suitable for two streams of students. Students entering the program from engineering, physics, mathematics and statistics have highly-developed analytical abilities and seek to gain insight into the financial applications of these skills. Students with a background in business and economics tend to have a better understanding of the context of financial applications, yet seek additional refinement of their analytical abilities.
Required Courses and Electives
The range of required and elective courses in each program's curriculum varies greatly. Some common themes across curricula for master's programs include required courses on stochastic processes or time series analysis, computational finance, derivatives, fixed-income securities, financial modeling, investment, and asset pricing. Generally, these will not all be required courses within the same program.
Some programs require students to take courses in basic finance or economics, such as the University of Alabama's (U.S.) Master of Finance program, which requires courses in Financial Management, Microeconomics, and Macroeconomics. Some do not. Interestingly, programs requiring a course in pure computer programming, such as The Hong Kong University of Science and Technology's (CN) Master of Science program, which requires a course in C++ programming, are in the minority. However, what you do not take as a required course you can often take as an elective course.
Elective courses range from those centered on the fundamentals of finance or math to those focused on specific subject matter. Elective courses with a more general focus can offer students an opportunity to catch up on relatively basic subject matter, which perhaps was not the focus of their prior coursework. For example, the student seeking to supplement their training in basic finance can find elective courses such as Financial Statement Analysis at Claremont Graduate University (U.S.), Bond Markets or Macro Economic Analysis at North Carolina State University (U.S.), Corporate Finance or Financial Accounting at the University of Illinois (U.S.), International Finance at Case Western Reserve University (U.S.), and Valuation of Equity Securities or Financial Statement Analysis at New York University's Polytechnic Institute (U.S.). The prospective student seeking to supplement their training in math can find courses such as Intro to Financial Mathematics at Rensselaer Polytechnic Institute (U.S.), Data Mining and Analysis at Stanford University (U.S.), Mathematical Statistics at the University of Southern California (U.S.), and Regression Analysis at the University of Dayton (U.S.).
Typically, it is electives that afford the student some flexibility to tailor the curriculum to their preferred career path and to gain the knowledge base and skill set they need in order to pursue it. There are many different electives offered across the range of programs. Consider the sample depicted in Exhibit 3.4.
School | Degree | Elective |
University of Waterloo (CA) | Master of Quantitative Finance | Portfolio Optimization |
Baruch College, City University of New York (U.S.) | MS in Financial Engineering | Time Series Analysis and Algorithmic Trading |
Bogazici University (TR) | MS in Financial Engineering | FE 538 Valuation with Real Options |
Nanyang Technological University (SG) | MSc (Financial Engineering) | Exotic Options & Structured Products |
NYU–Polytechnic Institute (U.S.) | Master of Science in Financial Engineering | Behavioral Finance, Trading and Investment Strategy |
Georgia State University (U.S.) | MS in Mathematical Risk Management (MS MRM) | Stochastic Term Structure and Credit Risk Models |
Baruch College, City University of New York (U.S.) | MS in Financial Engineering | Commodities and Futures Trading |
University of the Witwatersrand– Johannesburg (ZA) | MSc in Advanced Mathematics of Finance | Swaps & Exotic Options |
Ecole Polytechnique Fédérale de Lausanne (CH) | Master of Sciences in Financial Engineering | Private equity |
Nanyang Technological University (SG) | MSc (Financial Engineering) | Energy Derivatives |
Rensselaer Polytechnic Institute (U.S.) | Master of Science in Financial Engineering and Risk Analytics | Risk Management |
North Carolina State University (U.S.) | Masters of Financial Mathematics | Dynamic Programming |
Olin Business School, Washington University in St. Louis (U.S.) | Master of Science in Finance | Fixed Income Derivatives |
University of Limerick (IE) | MSc in Computational Finance | Portfolio Risk Analysis |
Carnegie Mellon University (U.S.) | Masters of Science in Computational Finance | Credit Derivatives |
Olin Business School, Washington University in St. Louis (U.S.) | Master of Science in Finance | Finance Consulting Seminar (applied learning course) |
University of Alabama (U.S.) | Master of Science in Finance | Mergers and Acquisitions |
University of California–Los Angeles (U.S.) | Master of Financial Engineering | MBS & ABS Markets |
Columbia University (U.S.) | MA in Mathematics of Finance | Emerging Markets |
Some programs will offer electives focused on particular applications. These will be useful for prospective students who are relatively certain of a career path, and who know the specific skills they need to competitively pursue it. Exhibit 3.5 provides examples of these.
School | Degree | Elective |
Dublin City University (IE) | MSc in Financial and Industrial Mathematics | Coding and Cryptography |
University of Birmingham (UK) | MSc in Mathematical Finance | Semidefinite Programming |
University of Birmingham (UK) | MSc in Mathematical Finance | Combinatorial Optimisation |
University of Twente (NL) | Master in Applied Mathematics | Stochastic Filtering and Control Theory |
Oklahoma State University (U.S.) | Masters of Science in Quantitative Financial Economics | Power Systems and Regulation |
Course Tracks
Some programs offer course tracks that will provide the student with a more structured curriculum. Some examples include American University (U.S.), which offers five different tracks, including Investments, Corporate Finance, Risk Management, International Finance, and Real Estate; Rensselaer Polytechnic Institute (U.S.), which offers a Financial Technology track and a Financial Analysis track; the University of Twente (NL), which offers a Management track and a Mathematics track; and Florida State University (U.S.) which offers a Concentration in Actuarial Science track and a Concentration in Regression and Financial Time Series track.
Conversely, some programs, such as the University of Florida's (U.S.) Master of Science in Finance program, have very few required courses and are extremely flexible in their curricula. Both tracked programs and flexible programs have their pros and cons, but only the prospective students can determine which is best for them and should do so in the context of their career goals.
Internships/Research
Some programs require an internship or research experience as part of their curriculum. Kent State University's (U.S.) Master of Science in Financial Engineering program, for example, requires relevant internship experience as part of its program. The University of Twente's (NL) Master in Applied Mathematics program requires full-time research in a financial institution during the second semester of the second year of study.
Faculty
Faculties across the range of programs offering training in financial engineering typically include some faculty who can offer a solid theoretical foundation and other faculty who can offer experience in real-world financial engineering–related problem solving. Faculty members offering real-world experience are often practitioners who contribute to the program as adjunct faculty. Many full-time faculty also have real-world experience in financial engineering, however, and a review of faculty across programs will reveal a broad range of experience upon which students can draw.
Some programs are more balanced than others in terms of offering both a theoretical foundation and real-world problem solving experience. The importance of each depends on the knowledge base and skill set sought by the prospective student.
Hands-on experience can be important to employers who are seeking graduates with specific and immediately applicable skills. Two professors teaching a course by the same name will impart to their students different levels of practical experience and different depths of theoretical foundation. An employer will want to gauge the level of each when hiring a graduate. Some employers will prefer to hire a graduate who has a solid theoretical foundation and who can be taught a number of skills on the job. Others are looking for specific skills and problem solving abilities, which may or may not have been taught depending on the faculty. Either way, a review of the faculty teaching in a degree program will be important in determining the suitability of the graduating student to a particular position within a firm.
JOB PLACEMENT
The goal of the prospective student is employment. Some students will know generally which field they wish to enter. Others will know the geographical area. Others will know exactly the firm for which they wish to work. However specific the employment goals are of the prospective student, there are also considerations to be made outside of the classroom regarding each program's ability to help the student meet them. For example, most programs provide an internship and job placement rate, which the prospective student can review in advance of enrolling. This section will discuss some additional considerations: institutional relationships, alumni networks, and geography.
Institutional Relationships
Most programs have developed institutional relationships, which their students are able to leverage when seeking employment. The strength and nature of these relationships differ among programs. Some programs have relationships with employers across a broad range of industries, and others have very strong ties to a particular industry. Some programs have developed strong ties to local industries, which may offer an advantage to the prospective student who knows they want to work in a particular location. For example, consider Case Western Reserve University's MSM Finance and MSM Finance/MBA Dual Degree programs, which offer the following unique advantage:
Cleveland offers visibility to a wealth of banking firms, a Federal Reserve, financial institutions, hedge funds and medium/large international firms. The faculty work closely with many of these firms and our alumni are a terrific resource for seminars, internship opportunities, etc.
Or the University of Witwatersand's BSc Honours, MSc, and PhD in Advanced Mathematics of Finance programs, which boast the “largest faculty in South Africa” and have “long-standing connections to the SA financial sector.”
Some programs offer a unique opportunity to gain exposure in foreign markets. The China Center at the University of Minnesota, for example, offers students exposure to China's emerging markets.
All schools have some form of Alumni network which the student can leverage.
Geographic Location
Today there are financial engineering programs in all of the developed markets and in many of the less developed ones as well. For the prospective student who knows in which geographic market they wish to work, and even for the prospective student who is not yet sure, the location of the program should play a role in the decision making process. But it should not be the deciding factor. For example, employers in Singapore hire graduates from programs in New York, and employers in New York hire graduates from programs in Singapore. Prospective students should consider the markets in which, and the firms for which, they wish to work and should research which programs are most likely to gain them access to those markets or firms. Employers should understand the range of programs outside the firm's immediate geographical market, from which qualified graduates may be recruited.
Some programs have developed across borders, offering students exposure to multiple geographic markets. The Nanyang Business School's MSc (Financial Engineering) program in Singapore, for example, is offered in collaboration with Carnegie Mellon University in the United States. Students spend seven weeks taking courses at Carnegie Mellon University and earn a Certificate in Computational Finance from Carnegie Mellon, in addition to the MFE degree awarded by Nanyang Technological University.
CONCLUSION
The common theme in any discussion of financial engineering programs is variety. There are a number of different departments at academic institutions around the world offering different degrees with varying curricula. This presents prospective students of financial engineering with an excellent opportunity to tailor their decision regarding program enrollment to their career goals. It should be stressed that the variety among financial engineering programs means that nothing should be taken for granted with respect to a particular program. Each program should be researched fully before the prospective student makes a judgment about the suitability of a program to his/her goals.
APPENDIX: PROGRAMS CONTACTED
For inclusion in the survey please contact [email protected].
School | Program | Location |
Birkbeck College, University of London | MSc Financial Engineering | London, UK |
Birkbeck College, University of London | MSc Finance | London, UK |
Birkbeck College, University of London | MSc Finance & Commodities | London, UK |
Brunel University | MSc Modelling and Management of Risk | Middlesex, UK |
Cambridge University, Judge School | Master of Finance | Cambridge, UK |
Cambridge University, Judge School | MPhil Finance (Financial Engineering Specialisation) | Cambridge, UK |
City University, Cass School | MSc Financial Mathematics | London, UK |
City University, Cass School | MSc Quantitative Finance (Formerly FEE) | London, UK |
City University, Cass School | MSc Mathematical Finance & Trading | London, UK |
Dublin City University | MSc Financial & Industrial Mathematics | Dublin, Ireland |
Herriot Watt University | MSc Financial Mathematics | Edinburgh, UK |
Imperial College Business School | MSc Mathematics & Finance | London, UK |
Imperial College Business School | MSc Risk Management and Financial Engineering | London, UK |
King's College, London | MSc Financial Mathematics | London, UK |
Queen's University, Belfast | MSc Finance | Belfast, Ireland |
Leeds University | MSc Financial Mathematics | Leeds, UK |
Leicester University | MSc Financial Mathematics & Computation | Leicester, UK |
Liverpool John Moores University | MSc International Banking & Finance | Liverpool, UK |
London Business School | MSc Finance | London, UK |
Manchester Business School, Manchester University | MSc Finance | Manchester, UK |
Manchester Business School, Manchester University | MSc Finance & Economics | Manchester, UK |
Manchester Business School, Manchester University | MSc Quantitative Finance (Financial Engineering or Risk Management Track) | Manchester, UK |
Manchester Business School, Manchester University | MSc Mathematical Finance | Manchester, UK |
Oxford University, Saïd Business School | MSc Financial Economics | Oxford, UK |
Oxford University | MSc Mathematical & Computational Finance | Oxford, UK |
University of Birmingham | MSc Mathematical Finance | Birmingham, UK |
University College Dublin, Smurfit School | MSc Finance | Dublin, Ireland |
University College Dublin, Smurfit School | MSc Quantitative Finance | Dublin, Ireland |
University College Dublin, Smurfit School | MSc Risk Management | Dublin, Ireland |
ICMA Centre, University of Reading | MSc Financial Engineering | Reading, UK |
ICMA Centre, University of Reading | MSc International Securities, Investment and Banking | Reading, UK |
ICMA Centre, University of Reading | MSc Financial Risk Management | Reading, UK |
University of Dublin, Trinity College | MSc Finance | Dublin, Ireland |
University of Essex | MSc Computational Finance | Essex, UK |
University of Exeter | MSc Financial Mathematics | Exeter, UK |
University of Limerick, Kemmy School | MSc Computational Finance | Limerick, Ireland |
University of Westminster | MSc Investment & Risk Finance | London, UK |
University of York | MSc Mathematical Finance | York, UK |
Warwick University | MSc Financial Mathematics | Warwick, UK |
American University, Kogod School of Business | MS Finance | Washington, DC |
Asbury College | BA Financial Mathematics | Wilmore, KY |
Baruch College (City University of New York) | MS Financial Engineering | New York, NY |
Ball State University | BS Financial Mathematics | Muncie, IN |
Bentley College | MS Finance | Waltham, MA |
Boston College, Carroll School | MS Finance | Boston, MA |
Boston University | MS Mathematical Finance | Boston, MA |
Brandeis University | MS Finance | Waltham, MA |
Carnegie Mellon University, Tepper School | MS Computational Finance | Pittsburgh, PA |
Carnegie Mellon University, Tepper School | MBA Financial Engineering | Pittsburgh, PA |
Case Western University, Weatherhead School | Master of Science in Management in Finance | Cleveland, OH |
Claremont Graduate University, Drucker School | MS Financial Engineering | Claremont, CA |
Clark University | MS Finance | Worcester, MA |
Columbia University | MA Mathematics of Finance | New York, NY |
Cornell University | MSc Engineering (Concentration in Financial Engineering) | Ithaca, NY |
DePaul University | MS Computational Finance | Chicago, IL |
DePaul University, Kellstadt School | MS Finance | Chicago, IL |
Drexel University | MS Finance | Philadelphia, PA |
Fairfield University, Dolan School | MS Finance | Fairfield, CT |
Florida State University | MS Financial Mathematics | Tallahassee, FL |
Fordham University | MS in Quantitative Finance | New York, NY |
Fordham University | Advanced Certificate in Financial Computing | New York, NY |
George Washington University | MS Finance | Washington, DC |
Georgia Institute of Technology | MS Quantitative and Computational Finance | Atlanta, GA |
Georgia State University | MSc Mathematical Risk Management | Atlanta, GA |
Golden Gate University | MS Finance | San Francisco, CA |
Hofstra University | MS Quantitative Finance | Hempstead, NY |
James Madison University | BS Quantitative Finance | Harrisonburg, VA |
Johns Hopkins University—Carey School | MS Finance (Part-Time) | Baltimore, MD |
Illinois Institute of Technology, Stuart School | MS Finance | Chicago, IL |
Kent State University | MS Financial Engineering | Kent, OH |
Lehigh University | MS Analytical Finance | Bethlehem, PA |
Louisiana State University, EJ Ourso School | MS Finance with Minor in Mathematics | Baton Rouge, LA |
Loyola College, Sellinger School | MS Finance | Baltimore, MD |
Massachusetts Institute of Technology | MF in Finance | Cambridge, MA |
New Mexico State University | Professional MS in Financial Mathematics | Las Cruces, NM |
New York University, Courant Institute | MS Mathematical Finance | New York, NY |
North Carolina State University | MS Financial Mathematics | Raleigh, NC |
Northwestern University, Kellogg School | Ph in Finance | Evanston, IL |
Oklahoma State University, Spears School | MS Quantitative Financial Economics | Stillwater, OK |
Polytechnic Institute of New York University | MS Financial Engineering | New York, NY |
Princeton University | MF in Finance | Princeton, NJ |
Purdue University, Krannert School | MS Finance | West Lafayette, IN |
Purdue University | MS Mathematics with specialisation in Computational Finance | West Lafayette, IN |
Purdue University | MS Statistics with specialisation in Computational Finance | West Lafayette, IN |
Queens College (City University of New York) | MS in Risk Management | New York, NY |
Rensselaer Polytechnic Institute, Lally School | MS in Management (Concentration in Financial Engineering & Risk Analytics) | Troy, NY |
Rutgers University (New Brunswick–Piscataway) | MS Mathematical Finance | Piscataway, NJ |
Rutgers University | MS Quantitative Finance | Newark, NJ |
Saint Mary's College of California | MS Financial Analysis and Investment Management (FAIM) | Morago, CA |
San Diego State University | BS in Applied Mathematics (Emphasis in Mathematical Finance) | San Diego, CA |
Seattle University, Albers School | MS Finance | Seattle, WA |
Stanford University | MSc Financial Mathematics | Stanford, CA |
State University of New York–Buffalo | MS Finance | Buffalo, NY |
Stevens Institute of Technology | MS Financial Engineering (Technology Track)— Distance Learning | Hoboken, NJ |
Stony Brook University | MS Financial Mathematics | Stony Brook, NY |
Temple University, Fox School of Business | MS Financial Engineering | Philadelphia, PA |
Texas A&M University | MS Financial Mathematics | College Station, TX |
Tulane University, Freeman School | MF in Finance | New Orleans, LA and Houston, TX |
UC Berkeley, Haas School | MS Financial Engineering | Berkeley, CA |
University of Alabama–Culverhouse | MS Finance | Tuscaloosa, AL |
University of Arizona–Eller | MS Finance | Tucson, AZ |
University of California–Los Angeles | MS Financial Engineering | Los Angeles, CA |
University of California–Santa Barbara | BS Financial Mathematics and Statistics | Santa Barbara, CA |
University of Chicago | MS Financial Mathematics | Chicago, IL |
University of Connecticut | Professional MS Applied Financial Mathematics | Storrs, CT |
University of Dayton | Master in Financial Mathematics | Dayton, OH |
University of Denver, Daniels College of Business | MS Finance | Denver, CO |
University of Florida, Hough Graduate School | MS Finance | Gainesville, FL |
University of Hawaii, Shidler College of Business | MS Financial Engineering | Honolulu, HI |
University of Houston, Bauer College of Business | MS Finance | Houston, TX |
University of Illinois at Urbana-Champaign | MS Finance | Urbana- Champaign, IL |
University of Illinois at Urbana-Champaign | MS Financial Engineering | Urbana- Champaign, IL |
University of Michigan | MS Financial Engineering | Ann Arbor, MI |
University of Minnesota | Master in Financial Mathematics | Minneapolis, MN |
University of North Carolina at Charlotte | MS Mathematical Finance | Charlotte, NC |
University of Pittsburgh | Professional Science MS Mathematical Finance | Pittsburgh, PA |
University of Rochester, Simon School | MS Finance | Rochester, NY |
University of Southern California | MS Mathematical Finance | Los Angeles, CA |
University of Tulsa | MS Finance | Tulsa, OK |
University of Wisconsin–Madison | Quantitative Masters in Finance | Madison, WI |
Vanderbilt University, Owen School | MS Finance (Quantitative Track) | Nashville, TN |
Washington University in St. Louis, Olin School | MS Finance | St. Louis, MO |
Worchester Polytechnic Institute | MSc Financial Mathematics | Worchester, MA |
HEC Montreal | MSc Financial Engineering | Montreal, QB |
McMaster University | MSc in Financial Mathematics | Hamilton, ON |
Université de Montreal | MSc Financial Mathematics & Computational Finance | Montreal, QB |
Université Laval | MSc Financial Engineering | Quebec, QB |
University of Toronto | MS Mathematical Finance | Toronto, ON |
University of Waterloo | MSc Quantitative Finance | Waterloo, ON |
University of Western Ontario | MS Applied Mathematics (Research in Financial Mathematics) | London, ON |
Université du Québec à Montréal (UQAM) | MSc Applied Finance | Montreal, QB |
York University | MS Financial Engineering | Toronto, ON |
City University–Hong Kong | MSc Finance | Hong Kong, Hong Kong |
City University–Hong Kong | MSc Financial Engineering | Hong Kong, Hong Kong |
Hong Kong University (HKU) | MF in Financial Engineering | Hong Kong, Hong Kong |
Hong Kong University of Science of Technology (HKUST) | MSc Investment Management | Hong Kong, Hong Kong |
Hong Kong University of Science of Technology (HKUST) | MSc Financial Analysis | Hong Kong, Hong Kong |
Hong Kong University of Science of Technology (HKUST) | MSc Mathematics (Financial Mathematics & Statistics) | Hong Kong, Hong Kong |
Macquarie University | Masters of Applied Finance | Sydney, Australia |
Nanyang Technological University (NTU) | MSc Financial Engineering | Singapore, Singapore |
National Tsing Hua University | MSc Quantitative Finance | Taipei, Taiwan |
National University of Singapore (NUS) | MSc Financial Engineering | Singapore, Singapore |
National University of Singapore (NUS) | MSc Quantitative Finance | Singapore, Singapore |
Singapore Management University (SMU) | MSc Applied Finance | Singapore, Singapore |
University of Melbourne | MSc Applied Finance | Melbourne, Australia |
University of New South Wales | MSc Finance | Sydney, Australia |
University of Technology Sydney | MSc Quantitative Finance | Sydney, Australia |
Bar Ilan University | MSc Financial Mathematics | Ramat Gan, Israel |
Bogaziçi University | MSc Financial Engineering | Istanbul, Turkey |
Duisenberg School of Finance | MSc Risk Management | Amsterdam, Netherlands |
Duisenberg School of Finance | MSc Corporate Finance and Banking | Amsterdam, Netherlands |
Ecole Polytechnique Fédérale de Lausanne | MSc Financial Engineering | Lausanne, Switzerland |
EDHEC | MSc Finance | Lille, France |
ETH/UZH–Zurich | Master of Science in Quantitative Finance | Zurich, Switzerland |
European School of Management (ESCP-EAP) | Specialized Master in Finance | Paris, London, Madrid |
Frankfurt School of Finance & Management | MSc Quantitative Finance | Frankfurt, Germany |
Frankfurt School of Finance & Management | MSc Finance | Frankfurt, Germany |
HEC | MSc International Finance | Paris, France |
International University of Monaco | Masters in Finance | Monaco, Monaco |
ISCTE Business School | MSc Finance | Lisbon, Portugal |
Middle East Technical University | MSc Financial Mathematics | Ankara, Turkey |
Tilburg University | MSc Quantitative Finance and Actuarial Science | Tilburg, The Netherlands |
Tilburg University | MSc Finance | Tilburg, The Netherlands |
Universidad Carlos III de Madrid | MSc Financial Analysis | Madrid, Spain |
Università Bocconi | MA Quantitative Finance & Risk Management | Milan, Italy |
Universität Konstanz | Masters in Mathematical Finance | Constance, Germany |
Université de Genève (HEC) | MSc Finance | Geneva, Switzerland |
Université de Lausanne (HEC) | MSc Finance | Lausanne, Switzerland |
Université de Neuchâtel | MSc Finance | Neuchâtel, Switzerland |
Université Panthéon–Assas | MS Finance | Paris, France |
University of St. Gallen | MSc Quantitative Economics and Finance | St. Gallen, Switzerland |
University of Twente | MSc Applied Mathematics and MSc Industrial Engineering & Management (Specialisation in Financial Engineering) | Twente, The Netherlands |
Universiteit van Amsterdam, Amsterdam Business School | Master in International Finance (Quantitative Finance Track) | Amsterdam, The Netherlands |
Universiteit van Amsterdam, Korteweg-de Vries Institute with Vrije Universteit & Universiteit Utrecht | MSc Stochastics and Financial Mathematics | Amsterdam, The Netherlands |
Università di Torino | MSc Quantitative Finance | Torino, Italy |
University of Piraeus | MSc in Banking and Financial Management | Piraeus, Greece |
Vienna Institute of Technology | Masters in Finance | Vienna, Austria |
Warsaw University | Masters in Quantitative Finance | Warsaw, Poland |
North-West University | MSc Financial Mathematics | Potchestroom, South Africa |
North-West University | MSc Quantitative Risk Management | Potchestroom, South Africa |
University of Capetown | MSc Mathematics of Finance | Capetown, South Africa |
University of Pretoria | MSc Financial Engineering | Pretoria, South Africa |
University of Pretoria | MSc Mathematics of Finance | Pretoria, South Africa |
University of São Paulo (Portuguese) | Professional Masters—Mathematical Modeling in Finance | São Paulo, Brazil |
University of Stellenbosch | MComm in Financial Risk Management | Stellenbosch, South Africa |
University of the Free State | MSc Mathematical Statistics | Bloemfontein, South Africa |
University of the Witwatersrand | MSc Mathematics of Finance | Johannesburg, South Africa |
NOTES
1. Median number of students (36) enrolled in programs who responded to the survey multiplied by number of programs having substantial components of financial engineering in their curricula worldwide (approximately 150).
2. Note that some universities interpret the term “financial engineering” more narrowly than we do, often limiting their interpretation to structuring roles. Some of these institutions prefer to think of financial engineering as a subset of quantitative finance. We employ a broader interpretation here that is consistent with that used by the International Association of Financial Engineers (IAFE).
ABOUT THE AUTHOR
John Cornish is an analyst at SBCC Group Inc. Since joining SBCC in January of 2009, John's independent advisory projects have spanned a diverse range of clients including hedge funds, multibillion-dollar asset management complexes, large global banks, endowments, municipalities, insurance companies and corporations. John's experience includes equities, fixed income, derivatives (both exchange traded and OTC) and structured products, the valuation of complex financially engineered securities, merger arbitrage, quantitative trading, transition trading and the liquidation of both equity and fixed income portfolios. John received his BSM in finance from the A.B. Freeman School of Business at Tulane University in 2008 and is a Level II candidate in the CFA program.