A master's degree in quantitative finance concerns the application of mathematical methods to the solution of problems in financial economics.[1] There are several like-titled degrees which may further focus on financial engineering, computational finance, mathematical finance, and/or financial risk management.

In general, these degrees aim to prepare students for roles as "quants" (quantitative analysts), including analysis, structuring, trading, and investing; in particular, these degrees emphasize derivatives and fixed income, and the hedging and management of the resultant market and credit risk.

Formal master's-level training in quantitative finance has existed since 1990.[2]

Structure

The program is usually one to one and a half years in duration, and may include a thesis component. Entrance requirements are generally multivariable calculus, linear algebra, differential equations and some exposure to computer programming (usually C++);[3] programs emphasizing financial mathematics may require some background in measure theory.

Initially, the curriculum builds quantitative skills, and simultaneously develops the underlying finance theory:

The components are then integrated, addressing the modelling, valuation and hedging of equity derivatives, commodity derivatives, foreign exchange derivatives, and fixed income instruments and their related credit- and interest rate derivatives; see Mathematical finance § Derivatives pricing.

Programs often include dedicated modules in market risk and credit risk, with some degrees offered as specialized “Masters in Financial Risk Management”; [8] the techniques covered are [9] value at risk, stress testing, and "sensitivities" analysis, and in parallel, the Basel capital / liquidity requirements. Increasingly, programs include quantitative portfolio management and -optimization; [10][11][12][13][14] see Outline of finance § Quantitative investing and § Portfolio theory. Recently, topics (or specializations)[15] in data science and machine learning are becoming common.[16]

The title of the degree will depend on emphasis,[1] the major differences between programs being the curriculum's distribution between mathematical theory, quantitative techniques and financial applications.[3] The more theoretically oriented degrees are usually termed "Master's in Mathematical Finance" or "Master's in Financial Mathematics" while those oriented toward practice are termed "Master's in Financial Engineering" (MFE or MSFE), "Master's in Computational Finance" (MCF or MSCF), or sometimes[17][18] simply "Master's in Finance" (MFin). "Master's in Quantitative Finance" is the more general degree title, although "MQF" degrees are often less theoretical and more practical. The practice oriented programs are often positioned as professional degrees (and in the United States, are sometimes offered as Professional Science Master's).[19] Programs are sometimes offered as a Master of Engineering,[20][21] or as a Master of Operations Research. [22]

Comparison with other qualifications

The program differs from a Master of Science in Finance (MSF), and an MBA in finance, in that these degrees aim to produce finance generalists as opposed to "quants", and therefore focus on corporate finance, accounting, equity valuation and portfolio management. The treatment of any common topics—usually "derivatives", financial modeling, and risk management—will be less (or even non) technical. Entrance requirements are similarly less mathematical. Note that Master of Finance (M.Fin.) and MSc. in Finance degrees, as distinct from the MSF, may be substantially similar to the MQF.

There is some overlap with degrees in actuarial science,[23] and both degrees are occasionally offered by the same department.[7] Nevertheless, the programs are almost always separate and distinct.[24] Specifically, whereas actuarial programs cover risk and uncertainty as applied to pensions, insurance and investments, quantitative finance programs are broader (although offer less depth in these areas), and prepare graduates for various of the highly numerate roles in finance[23] and for other areas that require "quants".[2]

There is similarly overlap with a Master of Financial Economics, although the emphasis is very different. That degree focuses on the underlying economics, and on developing and testing theoretical models, and aims to prepare graduates for research based roles and for doctoral study. The curriculum therefore emphasises coverage of financial theory, and of econometrics, while the treatment of model implementation (through mathematical modeling and programming), while important, is secondary. Entrance requirements are similarly less mathematical. Some Financial Economics degrees are substantially quantitative, and are largely akin to the MQF.

For students whose interests in finance are commercial rather than academic, a Master's in Quantitative Finance may be seen as an alternative to a PhD in finance. At the same time though, "Master's in Mathematical Finance" programs are often positioned as providing a basis for doctoral study.

History

The first quantitative finance master's programs in the US were offered by Illinois Institute of Technology in 1990, under Dr. Michael Ong.[25] The programs offered were the "Master of Science in Quantitative Finance" and "Master of Science in Financial Markets and Trading", and were combined in 2008 to become the "Master of Science in Finance, with Financial Engineering Concentration".[26]

The NYU-Poly Financial Engineering degree was the second program of its kind,[27] and the first to be certified by the International Association of Financial Engineers.[28][29] Carnegie Mellon introduced its "Master of Computational Finance" program in 1994.[30] OGI's Computational Finance Program (1996, now discontinued) was the first such program based in a computer science department.[31][32] Other pioneering programs include those at NYU's Courant Institute, Columbia, Princeton, Cornell, UCLA, DePaul and MIT.

Subsequent growth in the number and location of programs has paralleled the growth of financial engineering—with its growing importance across all aspects of the financial services industries—and of risk management as professions.[33] Programs are now widely offered internationally—see links below—and in some cases are available online or via distance education (e.g. Washington,[11] York,[12] Stevens,[14] USC,[34] NUS,[35] TU Kaiserslautern,[36]). In a few cases, a quantitative-finance MBA-specialization is offered. [37] [38] [39] More recently undergraduate programs are available, both in the US (e.g. Ball State,[40] James Madison,[41] McIntire.[42]) and internationally (e.g. Essex,[43] HKUST,[44] UNISA[45]).

See also

References

  1. 1 2 3 "Quantitative & Mathematical Finance". Mathematics in Finance. Archived from the original on 2012-01-30. Retrieved 2012-01-23.
  2. 1 2 Derman, Emanuel. "Finding a job in finance" (PDF). Archived from the original (PDF) on 8 September 2017.
  3. 1 2 "Resources : Student FAQ". International Association of Financial Engineers. Archived from the original on 2008-06-04. Retrieved 2008-06-18.
  4. "MSc Finance (Quantitative Finance)". University of London Centre for Financial and Management Studies. Retrieved 26 July 2021.
  5. "Quantitative Finance MSc Econometrics and Management Science". Erasmus School of Economics. Retrieved 2021-07-26.
  6. "Resources : FE Core Body of Knowledge". International Association of Financial Engineers. Archived from the original on 2006-08-22. Retrieved 2008-06-18.
  7. 1 2 "Financial Engineering, MS". NYU Tandon School of Engineering. Retrieved 26 July 2021.
  8. Financial Risk Management MSc, UCL; Masters Programme in Financial Risk Management, Stellenbosch University; Financial Risk Management MSc, University College, London; Masters in Financial Risk Management - ICMA; Programme in Quantitative Risk Management - North-West University
  9. See generally, Roy E. DeMeo (N.D.) Quantitative Risk Management: VaR and Others
  10. "Quantitative Methods in Investment Management". www.math.columbia.edu. Retrieved 2021-07-26.
  11. 1 2 "Computational Finance & Risk Management". University of Washington. Archived from the original on 25 March 2012. Retrieved 2021-07-26.
  12. 1 2 "Portfolio Theory and Risk Management". University of York Department of Mathematics. 7 January 2013. Archived from the original on 12 January 2013.
  13. "Curriculum – Asset Management | Questrom School of Business". Boston University. Retrieved 2021-07-26.
  14. 1 2 "Master of Science - Financial Engineering". Stevens Institute of Technology. Archived from the original on 7 May 2015.
  15. "Machine Learning for Finance - MSc (Online)". University of Limerick. Retrieved 2021-07-26.
  16. "Quantitative Finance". Fordham University Gabelli School of Business. Retrieved 2021-07-26.
  17. "Master in Finance". Princeton University. Archived from the original on 2013-11-24. Retrieved 2009-02-14.
  18. "Master of Finance". MIT Sloan School of Management. Archived from the original on 2009-02-25. Retrieved 2009-02-16.
  19. "Programs By Field". Professional Science Master's. Archived from the original on 18 June 2007.
  20. "Master of Engineering". School of Operations Research and Information Engineering - Cornell Engineering. Archived from the original on 25 January 2012.
  21. "MS in Financial Engineering". Columbia University. Retrieved 26 July 2021.
  22. "Operations Research - Methods in Finance Master's Degree". The Fu Foundation School of Engineering and Applied Science. Columbia University. Retrieved 26 July 2021.
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  30. Bryant, Richard. "THE MSCF PROGRAM". Carnegie Mellon MSCF. Archived from the original on 25 July 2008.
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  32. "OGI'S COMPUTATIONAL FINANCE PROGRAM SHIFTS GEARS, BECOMES A NEW TRACK FOR MST STUDENTS". MST Monitor. 2003. Archived from the original on 18 October 2004.
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  34. "MS in Financial Engineering". USC Viterbi. Retrieved 26 July 2021.
  35. "Master of Science in Financial Engineering (Part-Time, Full-Time or Distance Learning)". National University of Singapore. Archived from the original on 2015-10-07. Retrieved 2015-10-21.
  36. "Master's Programme Financial Engineering". Technische Universität Kaiserslautern.
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  38. "Financial Risk Management". The Schulich School of Business. York University. Retrieved 26 July 2021.
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  40. "Financial Mathematics". Ball State University. Archived from the original on 21 April 2014.
  41. "Major in Quantitative Finance Program of Finance and Business Law". James Madison University. Retrieved 26 July 2021.
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  43. "BSc in Computational Finance (Archived copy)". Archived from the original on 2013-12-03. Retrieved 2013-11-28.
  44. "Curriculum for BSc in Quantitative Finance" (PDF). Hong Kong University of Science and Technology.
  45. "Bachelor of Commerce Honours in Financial Modelling". University of South Africa. Retrieved 26 July 2021.
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