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Financial Engineering (FE) Booklet

Prepared and published by: Nariman H.B.

www.NarimanHB.com

Dec. 2011

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THIS BOOKLET INCLUDES THREE PARTS,

I. 10 Definitions about FE and their references

II. List of top 10 universities which offer financial engineering programs and their detail

information

III. Table for about 90 universities which offer FE programs all around the world

DISCLAIMER AND TERMS OF USE AGREEMENT FOR USING THIS BOOKLET

The author and publisher of this E-booklet and the accompanying materials have used their best

efforts in preparing this E-booklet. The author and publisher make no representation or warranties

with respect to the accuracy, applicability, fitness, or completeness of the contents of this E-

booklet. The information contained in this E-booklet is strictly for educational purposes.

Therefore, if you wish to apply ideas contained in this E-booklet, you are taking full responsibility

for your actions.

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PART I

FINANCIAL ENGINEERING

10 DEFINITIONS

Based on International Association of Financial Engineers (IAFE) definition, Financial

Engineering is the creation of new and improved financial products through innovative design or

repackaging of existing financial instruments.

***

Financial engineering is an engineering discipline which deals with the creation of new and

improved financial products through innovative design or repackaging of existing financial

instruments. Financially, engineered products like American Depository Receipt (ADR) and

Global Depository Receipt (GDR) have provided companies access to international financial

markets to raise funds. However, financial engineering is considered as being responsible for

triggering the global financial crisis by increasing leverage and price risks (Shah & Srinivasan,

2010).

***

Financial Engineering is a multidisciplinary field involving financial theory, the methods of

engineering, the tools of mathematics and the practice of programming. It is about the securities,

banking, and financial management and consulting industries, or as quantitative analysts in

corporate treasury and finance departments of general manufacturing and service firms

(Swishchuk & Manca, 2010).

***

Mainstream financial engineering as a study of methods that stand upon the assumptions of

behavior, markets and institutions of the neoclassical vintage is critically examined (Choudhury,

2009).

***

Financial engineering is a process in which financial securities are designed and packaged with

innovative features. Typically, financial engineering involves creating certain type of derivative

securities. House construction is to civil engineering what security packaging is to financial

engineering. They both involve putting raw materials together to come up with something for a

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particular purpose. Civil engineers wear hard hats and heavy boots for protection and safety

while financial engineers “wrap” themselves in legal papers full of cryptic fine prints (Wei,

2005).

***

FINANCIAL ENGINEERING is a process involving the creation and combination of a variety

of financial instruments in order achieve a defined financial objective within certain cost, tax and

legal constraints, e.g. combining or dividing existing financial products to create new financial

products (Gastineau & Kritzman, 1999).

***

Financial engineering sometimes also refers to the strategies companies use to maximize profits

or other important performance metrics. Examples include creating derivatives that address

unusual risks faced by a party to a transaction, structuring a purchase or sale in a way that better

addresses the interests of the buyer and the seller, and using new methods to compute the

fair market value of new or existing financial instruments (Zopounidis, 1999).

***

Financial engineering works in other environments as well. The financial theory of offering

several existing products under one package has become very common in the

telecommunications industry. Many providers today offer bundled service packages that include

local phone service, unlimited national long distance, Internet service, and cable or digital

satellite television. The end result of this type of arrangement means one lower price to obtain

three or more services at significant cost savings to the consumer (Smithson, 1998).

***

Financial engineering is the innovation and creation of new financial instruments. The most

important products of financial engineering are speculative bonds, zero coupon, securities

assets, financial derivatives and repurchase agreements (Moles & Terry, 1997).

***

Computational finance, also called financial engineering, is a cross-disciplinary field which

relies on computational intelligence, mathematical finance, numerical methods and computer

simulations to make trading, hedging and investment decisions, as well as facilitating the risk

management of those decisions. Utilizing various methods, practitioners of computational

finance aim to precisely determine the financial risk that certain financial instruments create

(Bradman, Rouge, Pentecostalism, Pentecostal, & Woroniecki).

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References

Bradman, D., Rouge, B., Pentecostalism, O., Pentecostal, O., & Woroniecki, M. P.

Encyclopedia> Cheminformatics.

Choudhury, M. A. (2009). Islamic Critique and Alternative to Financial Engineering Issues.

Islamic Economics, 22(2).

Gastineau, G. L., & Kritzman, M. P. (1999). The dictionary of financial risk management (Vol.

52): Wiley.

Moles, P., & Terry, N. (1997). The handbook of international financial terms: Oxford University

Press, USA.

Shah, V., & Srinivasan, P. (2010). Financial Engineering and Innovation as Risk Management

Tools: The Case of Indian Companies During Global Financial Crisis. IUP Journal of

Risk & Insurance, Vol. 7, Nos. 1 & 2, pp. 50-66, January & April 2010.

Smithson, C. W. (1998). Managing financial risk: a guide to derivative products, financial

engineering, and value maximization: McGraw-Hill Professional.

Swishchuk, A., & Manca, R. (2010). Modeling and Pricing of Variance and Volatility Swaps for

Local Semi-Markov Volatilities in Financial Engineering. Mathematical Problems in

Engineering, 2010.

Wei, J. Z. ( 2005). A Layman's Guide to Financial Terms. 24.

Zopounidis, C. (1999). Multicriteria decision aid in financial management. European Journal of

Operational Research, 119(2), 404-415.

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PART II

List of top 10 universities offer financial engineering programs and their detail information

Up to Nov. 2011

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1. University of York, UK

Financial Engineering MSc

Venue / office name UNIVERSITY OF YORK

Address Heslington York York YO10 5DD

Website http://www.york.ac.uk/

UK Provider Reference Number (UKPRN): 10007167

Study mode Duration Department/Faculty

Full time 1 year department of mathematics & department of economics

Course summary This course is delivered jointly by the department of mathematics and the department of economics and related studies; it is intended for candidates who want to combine a rigorous study of relevant topics in applied and computational mathematics with econometrics and quantitative finance.

Program modules All years: Econometric methods for research; mathematical methods of finance; time series; C++ programming with applications in finance; financial statement analysis and security valuation; portfolio selection and management; discrete time modeling and derivative securities; econometric methods for research; financial engineering; topics in financial econometrics; stochastic calculus and black-scholes theory; financial risk management; modeling of bonds, term structure, and interest rate derivatives; dissertation.

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Term 1 (autumn)

Core modules: : modules: Econometric Methods for Research (20 credits, taught module, continues into Term 2) Mathematical Methods of Finance (20 credits, taught module) Time Series (10 credits, taught module) Optional modules: C++ Programming with Applications in Finance (10 credits, taught module, continues into Term 2) Financial Statement Analysis and Security Valuation (10 credits, taught module) Portfolio Selection and Management (10 credits, taught module) Discrete Time Modeling and Derivative Securities (20 credits, taught module)

Term 2 (spring)

Core modules: Econometric Methods for Research (continued from Term 1) Financial Engineering (10 credits, taught module) Topics in Financial Econometrics (10 credits, taught module) Stochastic Calculus and Black-Scholes Theory (20 credits, taught module)

Optional modules:

C++ Programming with Applications in Finance (continued from Term 1)

Financial Risk Management (10 credits, taught module)

Modeling of Bonds, Term Structure, and Interest Rate Derivatives (20 credits, taught module)

Term 3 (summer)

Core module:

Dissertation (60 credits, independent study module)

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2. Carnegie Mellon University, USA Master of Business Management - Financial Engineering Venue / office name Tepper School of Business

Address Carnegie Mellon University 5000 Forbes Avenue PITTSBURGH Pennsylvania 15213

Website

http://tepper.cmu.edu

Study mode Duration Department/Faculty

Full time/Part time Variable Tepper School of Business

Venue description The Tepper School of Business at Carnegie Mellon, located in Pittsburgh, Pennsylvania, consistently ranks among the top business schools in the world. In 2007, the Wall Street Journal ranked the Tepper School 5 among the top MBA programs in the U.S., and the undergraduate program has been ranked a Top Ten business program by U.S. News and World Report for several consecutive years. The Department of Economics in the College of Humanities and Social Science is jointly administered by Tepper School of Business. This business school is most recognized for research and teaching within the areas of organizational behavior, finance, economics, operations, computational marketing and operations research

Institution name Carnegie Mellon University

Telephone +1 412 268 5231

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Course summary Introduced in 1994, Carnegie Mellon's pioneering Master of Science in Computational Finance (MSCF) is considered by many today to be the top quantitative financial engineering program in the country. The MSCF program is the joint venture of four colleges on our campus - the Tepper School of Business, the Mathematical Sciences Department, the Department of Statistics, and the Heinz College. Administered by the Tepper School of Business, the MSCF student enjoys the advantages of the business school environment, including the full resources of the School's placement services. As a result of the collaborative efforts of these four colleges, MSCF's twenty-five courses are both balanced and deep. Designed expressly for the MSCF student and the needs of the industry, the curriculum seamlessly integrates instruction in probability, statistical analysis, numerical methods, computation and simulation methods, stochastic processes, economics, and their application in today’s quantitative financial markets. The MSCF program is intense and extremely demanding - recruiters know the students graduating from MSCF are bright, highly motivated and keenly interested in the financial engineering industry. Our employment rates remain high, even in these challenging time. This program prepares students for careers in derivatives trading, structuring, and risk management. The track consists of the finance and mathematics core of the well-respected Masters in the Science of Computational Finance (MSCF) program. Students completing the track will be proficient in using cutting-edge option pricing techniques. Track participants will gain proficiency in the mathematical theory underlying these models and be able to implement numerical methods for computing derivative prices and risk sensitivities; skills which will give them an advantage on the trading desk, in creating new structured products, and in managing derivative risk.

Entry requirement for international students Students should possess a wide variety of backgrounds and profiles. Half of the students have GMAT scores below the average, and although most students have between 2 and 8 years of professional experience, there are several that joined Tepper directly after their undergraduate study or that have more than 8 years of experience. They must also come from the background of engineering/science or from all academic disciplines, and in a typical year. Applicants must have an average GPA of 3.35. International students whose native language is not in English should have the Test of English as a Foreign Language (TOEFL) with a score of 600 on paper based test, 250 on computer based test is required for admission.

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3. University of California, Berkeley, USA Master's in Financial Engineering

Venue / office name Hass School of Business, Master's in Financial Engineering Program

Contact address F514 Haas School of Business BERKELEY California 94720

Website www.haas.berkeley.edu/MFE/

Study mode Duration Department/Faculty

Full time 1 year Hass School of Business

Venue description For over 100 years, the Haas School of Business at the University of California, Berkeley, has offered a superb management education to outstanding men and women from around the world. The School is one of the world’s leading producers of new ideas and knowledge for all areas of business, and a launching point for many new businesses. The Haas School is widely known for its diverse and talented faculty, staff, students and alumni. They have created an innovative academic culture that stresses cooperative teamwork, entrepreneurship, a global point of view, and an emphasis on new ideas and fresh perspectives. The school’s programs benefit significantly from the university’s practice of interdisciplinary research and teaching, and the school’s strong connections to nearby Silicon Valley.

Telephone +1 510 642 7405 +1 510 642 4417

Course summary The Master's in Financial Engineering Program provides students with a one-year graduate degree from UC Berkeley's Haas School of Business. Instruction is led by world-renowned faculty from Haas, UCLA's Anderson School, UC Irvine's Paul Merage School of Business, and UC San Diego's Rady School of Management. Students in the MFE program learn to employ theoretical finance and computer modeling skills to make pricing, hedging, trading and portfolio management decisions. Courses and projects emphasize the practical applications of these skills.

Program modules Graduates of the Master's in Financial Engineering are prepared for careers in: Investment Banking, Corporate Strategic Planning, Risk Management, Primary and Derivative Securities Valuation, Financial Information Systems Management, Portfolio Management, Securities Trading.

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4. University of California, Los Angeles, USA Master of Financial Engineering

Venue / office name Anderson School of Management

Contact address 110 Westwood Plaza Box 951481 LOS ANGELES California 90095

Telephone +1 310 825 3819 +1-310 825 1681

Website http://www.anderson.ucla.edu/x24272.xml

Study mode Duration Department/Faculty

Full time 1 year Anderson School of Management

Course summary This program prepares students for technically sophisticated jobs with financial institutions, financial service providers, suppliers of financial consulting services, financial software and systems providers, and in corporate treasuries. It serves students seeking comprehensive technical knowledge of arbitrage, hedging, futures and options pricing, portfolio management, trading, and dynamic investment strategies in bond, currency, options and other financial markets. The specialized one-year MFE curriculum integrates mathematical, statistical, and computer

science tools with finance theory as applied in institutional settings. MFE students are challenged with a curriculum that is solidly based on the business school paradigm of providing students not only with technical knowledge, but also with the business knowledge and skills they will need to function in management position in the financial industry. As part of the MFE Program students learn not only computational methods but also much of the foundational business knowledge taught in the UCLA Anderson MBA Program, including areas such as accounting, economics, econometrics, finance and much more. The Internship/Applied Finance Project serves as a capstone to the MFE curriculum.

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5. Nanyang Technological University, Singapore Master of Science in Financial Engineering - Computing

Venue / office name Nanyang Business School

Address Nanyang Technological University Nanyang Avenue Singapore 639798

Venue description Nanyang Business School (NBS) is a leading business school committed to educating tomorrow’s strategic leaders, through cutting-edge rigorous curricula that are relevant to business practice. It provides an outstanding learning environment, with the full range of undergraduate and graduate programmes, state-of-the-art facilities and world-class research centres.

Website http://www.mfe.ntu.edu.sg/Pages/Home.aspx

Study mode Duration Department/Faculty

Full time 1 year Nanyang Business School

Part time 2 years Nanyang Business School

Telephone +65 6790 5895 +65 6790 6033

Course summary This programme aims to groom the brightest and most intense minds in the region for a soaring career in the fast-paced and high-stakes arena of Financial Engineering. The programme started 1999 and has established itself in the region with many of the graduates working overseas.

Program modules Modules include Object Oriented Programming I; Object Oriented Programming II; Financial Computing (CMU); Financial Engineering Project (CMU); Web Programming (E); Artificial Intelligence Techniques in Finance (E).

Entry requirement for international students Admission to the programme requires a good undergraduate degree in applied mathematics, applied science, statistics, computer science, engineering, economics, or other quantitative fields, students must provide either GMAT /GRE scores although GRE is preferred. Also students whose medium of instruction at tertiary level is non-English should demonstrate with a minimum TOEFL is 260 (paper based), 650 (computer based) and 100 (internet based). For IELTS, the acceptable score is 7 and above.

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Structure Students will be required to complete:

20 core courses

4 elective courses MFE courses are half courses which carry 1.5AUs with the exception of Stochastic Calculus for Finance which is a full course offered over two mini terms, carrying 3AUs. The curriculum will be taught over 3 trimesters (1 year) in the full-time programme and 6 trimesters (2 years) in the part-time programme. Each trimester is divided into 2 mini terms of 7 weeks each.

Trimester One (Jul-Oct) Two (Oct-Feb) Three (Mar-Jun)

Mini Term 1

(Jul-Aug) 2

(Sep-Oct) 3

(Oct-Dec) 4

(Jan-Feb) 5

(Mar-Apr) 6

(May-Jun)

CMU Term Students will spend 5 mini terms in Nanyang Technological University, Singapore and the final 7-week mini term (mini term 6) in Carnegie Mellon University, USA (subject to the approval of US visa if applicable). The CMU term is compulsory for all full-time students. Part-time students may opt out of this according to work demands. The opting-out should be done during the time of application, and is subject to the final approval of the University. The remaining courses will be completed at NTU to fulfill graduation requirements. Tuition fees will remain unchanged for students who opt out.

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6. Bernard M. Baruch College of the City University of New York, USA

Master of Science in Financial Engineering Venue / office name Weissman School of Arts and Sciences, Department of Mathematics

Address One Bernard Baruch Way 24th Street and Lexington NEW YORK New York 10001

Website http://mfe.baruch.cuny.edu/

Study mode Duration Department/Faculty

Full time 3 semesters Weissman School of Arts and Sciences, Department of Mathematics

Telephone number +1 646 312 4110

Course summary This program is designed to provide the students with the background required for modeling and solving problems that arise in the financial-service industry. Courses such as Object Oriented Programming for Financial Applications, Market and Credit Risk Management, Elements of Structured Finance, and Deal Theory and Structured Analysis are taught by practitioners from the financial industry, enhancing the practical knowledge and the financial engineering skills of the students. This program consists of twelve three-credit courses. Eight of these courses are required courses. Four other courses will be chosen from a group of electives. Students attending full-time would complete the program in three semesters. Alternatively, students may attend part-time for a more extended period of five to six semesters. All courses start after 6 pm. Students entering the program with exceptional mathematical or financial skills may be permitted to replace one or more of the required courses with additional electives.

Program modules The program modules include: Courses in specialization (36 credits): the required courses (27 credits) are MTH 9814 A Quantitative Introduction to Pricing Financial Instruments 3 credits, MTH 9815 Object Oriented Programming for Financial Applications 3 credits, MTH 9821 Numerical Linear Algebra 3 credits, MTH 9831 Real Analysis and Probability 3 credits, MTH 9852 Numerical Methods for PDEs in Finance 3 credits, MTH 9862 Stochastic Processes in

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Finance 3 credits, MTH 9871 Advanced Computational Methods in Finance 3 credits, MTH 9873 Interest Rate Models and Interest Rate Derivatives 3 credits, MTH 9903 Capstone Project and Presentation 3 credits. The elective courses (9 credits): choose three courses from: MTH 9841 Statistics for Finance 3 credits, MTH 9842 Linear and Quadratic Optimization Techniques 3 credits, MTH 9845 Market and Credit Risk Management 3 credits, MTH 9848 Elements of Structured Finance 3 credits, MTH 9849 Deal Theory and Structured Analysis 3 credits, MTH 9881 Current topics in Mathematical Finance 3 credits, ECO 82100 (Term I) Econometrics I 3 credits, ECO 82100 (Term II) Financial Econometrics 3 credits, FIN 9770 Financial Markets and Institutions 3 credits, FIN 9782 Futures and Forward Markets 3 credits, FIN 9783 Investment Analysis 3 credits, FIN 9786 International Financial Markets 3 credits, FIN 9790 Seminar in Finance 3 credits, FIN 9793 Advanced Investment Analysis 3 credits, FIN 9797 Options Markets 3 credits, STA 9700 Modern Regression Analysis 3 credits, STA 9701 Time Series: Forecasting and Statistical Modeling 3 credits.

Entry requirement for international students Students should possess a regionally accredited bachelor's degree or its recognized international equivalent (any major). Students must demonstrate their English proficiency; they should submit scores from either the Test of English as a Foreign Language (TOEFL) or the International English Language Testing System (IELTS) Academic format/level test. TOEFL score of 105 out of 120 or an IELTS score of 7 is required. There is no minimum SAT/ACT score or GPA. For reference, the average SAT score is a 1220 (Math & Verbal), the average ACT score is a 26 and the average GPA is an 87%.

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7. Cornell University, USA Master of Engineering in Operations Research and Information Engineering - Financial Engineering Concentration Venue / office name College of Engineering, School of Operations Research and Information Engineering

Address 206 Rhodes Hall Cornell University ITHACA New York 14853

Venue description Cornell Financial Engineering Manhattan fosters close working relationships between Cornell University's School of Operations Research and Information Engineering and the financial services industry by building on the highly successful financial engineering program on the Ithaca campus.

Cornell Operations Research is dedicated to advancing the field of Operations Research through the talented students, scientific discovery, collaborative work with business and industry, and academic outreach. Operations Research (OR) emphasizes optimizing organizational and system performance using advanced analytical methods to help make better decisions. The OR is used in many different industry segments, from health care to logistics to financial services. It is also applied in different business functions from finance to manufacturing and marketing. It helps solve diverse business problems such as identifying best product placements in retail establishments to ensuring appropriate inventory levels in spare parts manufacturing. There is a close connection between Operations Research (OR) and commercial software. A wide array of software products, from Excel Solver to high performance parallel processing simulation tools, are based on OR-developed abstract ideas and concrete algorithms (several of these packages, notably CPLEX and AMPL for optimization, were developed by Cornell alumni). Such software products are used to solve OR models that are routinely used in manufacturing, distribution, marketing and other business functions.

Website http://www.orie.cornell.edu/academics/master/cfem/

Study mode Duration Department/Faculty

Full time Variable College of Engineering, School of Operations Research and Information Engineering

Telephone +1 607 255 4856 +1 607 255 5820

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Course summary This program is a professional degree. Its objectives are to provide: each student greater breadth and depth of technical knowledge; an environment in which to synthesize and apply material studied in the coursework. The program's emphasis is on mathematical modeling and on the application of quantitative techniques associated with optimization, probability, stochastic processes, and statistics to the design and operation of systems. This program prepares students for careers that involve the quantitative analysis and management of financial instruments and risk. Such jobs frequently involve: (1) mathematical modeling and analysis of stocks, bonds, options, currency exchange rates, and other structured products, (2) developing quantitative models to help corporations understand and manage their exposure to risk, and/or (3) implementing algorithms to monitor, price, and/or trade financial instruments. Unlike other concentrations, FE is specifically designed to be a three-semester program (Fall-Spring-Fall), with the third (i.e., second fall) semester taking place at Cornell Financial Engineering Manhattan in New York City.

Entry requirement for international students Students seeking admission must have completed a bachelors’ degree. International students must take the GRE exam. Students whose native language is not English must take the TOEFL and have the official score reported to Cornell from the Educational Testing Service (ETS). Educational Testing Service provided a new Internet-based Test (iBT) version of the TOEFL. This new version will test all four language skills important for effective communication: writing, listening, reading, and speaking. Each section has its own score, and the Graduate School has set the following minimum scores for admissions: Writing: 20; Listening: 15; Reading: 20; Speaking: 22. Students will continue to accept scores for computer based (cBT) (213 minimum) and paper based (550 minimum) versions of the TOEFL that were taken within two years of the date.

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8. University of Manchester, UK Quantitative Finance (Financial Engineering) MSc

Venue / office name UNIVERSITY OF MANCHESTER

Address Oxford Road Manchester Greater Manchester M13 9PL

UK Provider Reference Number (UKPRN) 10007798

Website http://www.mbs.ac.uk/programmes/masters/courses/quant-fin-financial-eng/

Study mode Duration Department/Faculty

Full time 1 year Manchester Business School and the School of Mathematics

Course summary The course provides an advanced knowledge and understanding of the main theoretical and applied concepts in quantitative finance and financial engineering, delivered from a genuinely international and multicultural perspective, and with a current issues approach to teaching; the course is particularly useful for careers that involve designing new financial instruments and managing trading in them.

Program modules Typical compulsory and optional course units will include: Foundations of finance theory; stochastic calculus; VBA/C++ with financial applications; derivative securities; financial econometrics; interest rate derivatives; computational finance; mathematical modeling of finance; real options in corporate finance; and credit risk management. The course teaching is shared by Manchester Business School and the School of Mathematics, and delivered through lectures, case studies, seminars and group project-based work. Assessment varies depending on course units taken. It may include a combination of course work and examination. The dissertation normally ranges between 12,000 and 25,000 words.

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Semester 1

Foundations of Finance Theory This course provides a foundation in the most important models in finance: general no-arbitrage relationships (forward parity, put-call parity, MM theorem, the law of one price), stock valuation models (APT, CAPM, TSP) and option pricing models.

Stochastic Calculus The course content includes: Wiener process; continuous local martingales; the quadratic variation process; Ito’s integral with respect to a continuous semi-martingale; the Levy characterization theorem; the martingale representation theorem; optimal prediction of the maximum process; Bassel process; the Ornstein-Uhlenbeck process; branching diffusion; Brownian bridge; the Shiryaev process; the sequential testing equation; the quickest detection equation; the existence and uniqueness of solutions in the case of Lipschitz coefficients.

Scientific Computing This course teaches the syntax and logical structure of C++ programming and object-oriented development with no assumed prior knowledge. Emphasis is placed on the implementation of common mathematical tasks/algorithms in C++. students must complete two mini-projects applying C++ to problems related to finance. The projects are assessed by a written report and a demonstration/oral description of the code.

Derivative Securities This course covers the valuation and application of financial derivatives instruments, and the use of no-arbitrage arguments and risk neutral valuation for the relative pricing of financial derivatives.

Semester 2

Financial Econometrics This course covers OLS, ML and GMM estimation methods, univariate time series analysis and various topical issues such as ARCH, Vector Autoregressive Models, unit roots, error correction, co-integration and non-linear time series models.

Interest Rate Derivatives This course unit provides students with foundations of interest rate models and the conceptual framework for valuing interest rate derivatives. The unit covers interest rates and bond prices, single period and multi period interest rates instruments, interest rate derivatives, interest rate models, spot rate models and forward models.

Computational Finance This course covers computational methods, including Monte Carlo and Lattice methods for option pricing, finite difference methods for parabolic PDEs with emphasis on Crank Nicolson methods for parabolic systems, point and line relaxation and PSOR methods, and quadrature methods.

One course unit from:

Mathematical Modeling of Finance The course content includes: no-arbitrage valuation of options and futures; models for the movements of stock prices, Brownian motion and geometric Brownian motion; stochastic and deterministic processes; basics of stochastic calculus and Ito's lemma;

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derivation of the Black–Scholes PDE and the assumptions behind it; formulating the mathematical problem, determining boundary conditions and deriving the solution of the heat conduction equation using the Dirac delta function; extension to assets paying dividends, early exercise and free boundary problems.

Real Options in Corporate Finance This course evaluates strategy and management value in property, power, resources, R&D, football, dot.coms, telcos, banking and consulting. The course surveys the real options that practitioners have identified in these industries.

Credit Risk Management This course unit provides students with advanced approaches to quantitative credit risk modelling and management in the context of the Basel II and Solvency II regulatory framework.

Summer research period Research dissertation (60 credits)

For the dissertation, Students will carry out an original piece of research on a subject relating to the course. Our MSc dissertation topics are aligned with the research interests of leading financial institutions from the City of London and internationally. A number of the dissertation topics are proposed by these organisations and supervised by academic staff. Students who want to work on the industry linked topics for their dissertations are subject to certain strict selection criteria (for example, strong CV and first semester exam performance). Other dissertation topics are proposed by academic staff focusing on cutting edge research issues in these industries

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9. Imperial College London, UK Risk Management and Financial Engineering MSc Venue / office name IMPERIAL COLLEGE LONDON

Address South Kensington Campus Kensington and Chelsea London SW7 2AZ

UK Provider Reference Number (UKPRN) 10003270

Website http://www3.imperial.ac.uk/business-school/programmes/msc-risk-management

Study mode Duration Department/Faculty

Full time 1 year Imperial College Business School

Course summary The course equips students with the cutting-edge risk management tools and strategies utilized by leading financial firms in the world.

Program modules Core modules: Pre-study courses; financial statistics; corporate valuation; investments and portfolio management; elective modules; hedge funds; credit risk; advanced credit derivatives and structured products; introduction to numerical finance with C++; advanced numerical finance with C++; fixed-income securities; advanced options theory; advanced corporate finance; private equity and entrepreneurship; venture capital finance and innovation.

Telephone +44 (0)20 7594 9100

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10. Princeton University, USA Master of Science in Engineering in Operations Research and Financial Engineering Venue / office name School of Engineering and Applied Science, Department of Operations Research and Financial Engineering

Address Contact address for international enquiries Princeton University Sherrerd Hall Charlton Street PRINCETON New Jersey 08544

Website http://orfe.princeton.edu/

Study mode Duration Department/Faculty

Full time 1 year School of operation and applied science, Department of Operations Research and Financial Engineering

Venue description The Department was formed in 1999 and traces a distinguished history to activities at Princeton between 1930 and 1960.Though the Department is relatively new, Operations Research & Financial Engineering has had a distinguished history at Princeton. In fact, a significant portion of modern ORFE is an outgrowth of activities at Princeton between 1930 and 1960.

Telephone +1 609 258 0876 +1 609 258 3030

Course summary This program has a strong research focus reflected in the requirement of a thesis. The course requirements are fulfilled by successfully completing ten one-semester courses, two of which are required research courses (509 and 510). The M.S.E. degree is usually completed within two academic years of full-time study.

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Program modules The ORFE is the intersection of five core disciplines: financial mathematics, operations research, optimization, probability theory, and statistics. The research in the department ranges from the mathematical foundations of these fields to the development of state-of-the-art methodology for solving complex problems that arise in important real-world applications in engineering and the sciences. Students obtain a strong quantitative and interdisciplinary training, and acquire the skills to become leaders in academia and industry. The modules include ORF 504/FIN 504 Financial Econometrics; ORF 505/FIN 505 Modern Regression and Time Series; ORF 507 Master's Project I; ORF 508 Master's Project II; ORF 509 Directed Research I; ORF 510 Directed Research II; ORF 511 Extramural Summer Project; ORF 514/FIN 501 Asset Pricing I: Pricing Models and Derivatives; ORF 515/FIN 503 Asset Pricing II: Stochastic Calculus and Advanced Derivatives; ORF 517/APC 513 Empirical Processes & Bootstrap Method; ORF 522 Linear Optimization; ORF 523 Nonlinear Optimization; ORF 524 Statistical Theory and Methods; ORF 525 Generalized Regression Models; ORF 526 Stochastic Modeling; ORF 527 Stochastic Calculus and Finance; ORF 530 Financial Data Mining; ORF 531/FIN 531 Computational Finance in C++; ORF 533 Convex Analysis for Mathematical Finance; ORF 534 Investment Science; ORF 538 Analytical and Computational Methods of Financial Engineering; ORF 542 Controlled Markov Processes; ORF 547 Dynamic Programming; ORF 548 Large-scale Optimization; ORF 549 Stochastic Programming; ORF 551/APC 551 Probability Theory; ORF 553 Stochastic Differential Equations; ORF 554 Markov Processes; ORF 555/FIN 555 Fixed Income Models; ORF 557 Stochastic Analysis Seminar; ORF 558 Stochastic Analysis Seminar; ORF 562 Transportation and Logistics Planning; ORF 563/WWS 527A Topics in Domestic Policy Analysis; ORF 569 Special Topics in Statistics and Operations Research; ORF 570 Special Topics in Statistics and Operations Research; ORF 572 Risk Management Seminar; ORF 574/FIN 574 Special Topics in Investment Science; ORF 575 Financial Engineering Seminar.

Entry requirement for international students A bachelor's degree in engineering, sciences, or mathematics is normally required for admission to the graduate program from an accredited undergraduate institution. GRE scores within the past five years. Applicants to the Masters in Finance may submit GMAT scores in place of the GRE General Test. The Graduate School has set a 7.0 on the academic version of IELTS as the minimum to be considered for admission to Princeton doctoral programs. The Graduate Schools tentative recommended minimum score on the iBT TOEFL is 71, but this is currently under review. Over the last two admission seasons the average iBT TOEFL combined score for admitted students was 108, with the following average sub-scores: Listening 28, Reading 29, Speaking 24, and Writing 27.

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11. University of Twente, Netherlands MSc in Industrial Engineering and Management - Specialization in Financial Engineering and Management Venue / office name School of Management and Governance ENSCHEDE Overijssel 7521 PL

Website http://www.utwente.nl/master/international/iem/tracks/fem/

Study mode Duration Department/Faculty

Full time 2 year School of Management and Governance

Venue description School of Management and Governance is one of the six faculties of the University of Twente. It provides educational programmes and undertakes research in the areas of (International) business administration, public administration, health sciences, business information technology and industrial engineering and management.

Telephone +31 (0)53 489 54 24

Course summary In this programme, students will be trained to identify and quantify risk. Moreover, they should be able to determine the extent to which risk should be dealt with using financial engineering instruments or other types of solutions, such as reengineering business processes, adapting the firm's strategy, switching customers/suppliers or taking different investment decisions. Students will also benefit from comprehensive management training, learning to apply strategic skills to manage the firm's innovation and technology. Financial engineering graduates enjoy a wide array of career opportunities where they can apply the tools they have learned. Working for an investment bank or an insurance company is one career option, but by no means the only one. Skills necessary to price and manage complex risks are also highly valued by non-financial corporations. Finally, financial engineering graduates may also pursue other avenues of professional development, including consultancies, software companies and regulatory institutions.

Entry requirement for international students Students must have a bachelor's degree in a related field. They must have obtained an academic overall band score of at least 6.5 on IELTS; score of at least 90 internet based TOEFL; Cambridge CAE-C (CPE);

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Legenda:

C = Common courses (obligatory)

F = FEM obligatory cluster specialization courses

I = ITM obligatory cluster specialization courses

P = PLM obligatory cluster specialization courses

H = HCTM obligatory cluster specialization courses

generation 2011 first year Obligatory

Quartile/ (cluster)

Code Coursename EC courses

equalization course 1 F/I/P/H

Introduction to Investment Theory 5 F

Statistics and probability 5 F

Foundations of Information Systems 5 I

E-strategizing 5

Purchasing 5 P

Discrete Optimization of Business Processes (1) 2,5 P/H

Simulation (1) 2,5 P/H

Clinical efficacy & MTA 5

equalization course 2 F/I/P/H

Introduction to Industrial Engineering and Management

5 C

Mathematical Finance 5 F

Information Services 5 I

Simulation (2) 2,5 P/H

Discrete Optimization of Business Processes (2) 2,5 P/H

Health & Health Systems 5 H

Financial Econometrics 5 F

Risk management 5 F

M & O of Technological Innovation 5 C

Implementation of IT in organizations 5

ICT Management 5

Supply Chain - & Transport Management 5 P

Reliability engineering & Maintenance management 5

Clinical Safety and Quality Assurance 5 H

Financial accounting 5

Management Control for Financial Institutions 5

Structured Products 5 F

Global Project Management 5

Business Case Development for IT Projects 5 I

Information System Research Methods 5 I

Advanced Production Planning 5 P

Warehousing 5 P

New Production Concepts 5

The Nature of Hospital Work Heathcare Workers 5

E-health strategies 5 H

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Legenda:

C = Common courses (obligatory)

F = FEM obligatory cluster specialization courses

I = ITM obligatory cluster specialization courses

P = PLM obligatory cluster specialization courses

H = HCTM obligatory cluster specialization courses

generation 2011 first year Obligatory

Quartile/ (cluster)

Code Coursename EC courses

second year

Management of Technology for FEM * 5 C for all clusters *

Management of Technology for PLM * 5

Management of Technology for Health Care * 5

Micro Economics 5

Special topics in Financial Engineering 2,5

Simulation (1) 2,5

Business Process Integration Lab 5 I

Production & Logistic IS 5 I

Optimization of Healthcare Processes 5 H

Medical decision making 5

Organization & Strategy 5 C

Empirical Research & Data Analysis 5 C

Special topics in Financial Engineering 2,5

Simulation (2) 2,5

Reverse Logistics & re-manufacturing 5

Quality and Safety in Health Care 5

Master thesis 30 F/I/P/H

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PART III

Here you can find a list of universities and scientific institutions which offer FE programs for the

name of university, name of college, and name of program.

North America

University Name of program Department/Faculty

1. Carnegie Mellon University, USA

Master of Business Management - Financial Engineering

Tepper School of Business

2. University of California, Berkeley, USA

Master's in Financial Engineering

Hass School of Business

3. University of California, Los Angeles, USA

Master of Financial Engineering

Anderson School of Management

4. Bernard M. Baruch College of the City University of New York, USA

Master of Science in Financial Engineering

Weissman School of Arts and Sciences, Department of Mathematics

5. Claremont Graduate University, USA

Ph.D. in Financial Engineering

Peter F. Drucker and Masatoshi Ito Graduate School of Management

6. Cornell University, USA

Master of Engineering in Operations Research and Information Engineering - Financial Engineering Concentration

College of Engineering, School of Operations Research and Information Engineering

7. Princeton University, USA

Master of Science in Engineering in Operations Research and Financial Engineering

School of operation and applied science, Department of Operations Research and Financial Engineering

8. State University of Newyork at Binghamton, USA

BS in Management - Financial Engineering

School of Management

9. Temple University, USA

Masters of Science in Financial Engineering (MSFE)

Fox School of Business and Management, Department of Finance

10. Temple University, USA

Master of Science in Financial Engineering

Fox School of Business and Management

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11. Columbia University, USA

M.S./M.B.A. Degree in Financial Engineering

Fu Foundation School of Engineering and Applied Science, Department of Industrial Engineering and Operations Research

12. Columbia University, USA

M.S. in Financial Engineering

Fu Foundation School of Engineering and Applied Science, Department of Industrial Engineering and Operations Research

13. Kent State University, USA

Master of Science in Financial Engineering

College of Business Administration, Department of Finance

14. University of Texas At Dallas, USA

Master of Science in Finance - Financial Engineering and Risk Management

School of Management

15. University At Buffalo, The State University of New York, USA

MS in Finance - Financial Engineering Track

School of Management, Accounting and Law Department

16. Stevens Institute of Technology, USA

Masters of Business Administration (MBA) in Technology Management - Engineering Management and Financial Engineering

School of Systems and Enterprises

17. Stevens Institute of Technology, USA

Master of Science in Financial Engineering

School of Systems and Enterprises

18. Stevens Institute of Technology, USA

MBA - Master of Business Administration in Financial Engineering

Howe School of Technology Management

19. New Jersey Institute of Technology, USA

MS in Financial Engineering

School of Management

20. Princeton University, USA Doctor of Philosophy (Ph.D.) in Operations Research and Financial Engineering

School of Engineering and Applied Science, Department of Operations Research and Financial Engineering

21. Princeton University, USA Master of Science in Engineering in Operations Research and Financial Engineering

School of Engineering and Applied Science, Department of Operations Research and Financial Engineering

22. Polytechnic Institute of Nyu, USA Master of Science in Brooklyn Campus

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Financial Engineering - Financial Markets and Corporate Finance Track

23. Polytechnic Institute of Nyu, USA Master of Science in Financial Engineering - Financial Information Services and Technology Track

Brooklyn Campus

24. Polytechnic Institute of Nyu, USA Master of Science in Financial Engineering - Computational Finance Track

Brooklyn Campus

25. Polytechnic Institute of Nyu, USA Master of Science in Financial Engineering - Actuarial Science Track

Brooklyn Campus

26. Rensselaer Polytechnic Institute, USA

M.S. in Information Technology - Financial Engineering

Information Technology Program

27. Polytechnic University, Brooklyn Campus, USA

Master of Science in Financial Engineering - Financial Markets and Corporate Finance Track

Department of Finance and Risk Engineering

28. Polytechnic University, Brooklyn Campus, USA

Master of Science in Financial Engineering - Computational Finance Track

Department of Finance and Risk Engineering

29. Polytechnic University, Brooklyn Campus, USA

Master of Science in Financial Engineering - Financial Information Service and Technology Track

Department of Finance and Risk Engineering

30. Polytechnic University, Brooklyn Campus, USA

Master of Science in Financial Engineering - Actuarial Sciences Track

Department of Finance and Risk Engineering

31. University of Illinois at Urbana Champaign, USA

Bachelor of Science in Finance - Financial Engineering

College of Business, Department of Finance

32. Columbia University, USA B.S. in Operations Research - Financial Engineering

Fu Foundation School of Engineering and Applied Science, Department of Industrial Engineering and Operations Research

33. California State University Long Beach, USA

Bachelor of Science in Business Administration in Finance - Financial Engineering

College of Business Administration, Department of Finance

34. Princeton University, USA Bachelor of Science in School of Engineering and

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Engineering in Operations Research and Financial Engineering

Applied Science, Department of Operations Research and Financial Engineering

35. Virginia Commonwealth University, USA

Bachelor of Science in Financial Technology - Financial Engineering Track

School of Business, Department of Finance, Insurance and Real Estate

36. Thunderbird School of Global Management, USA

Master of Science in Global Finance

Thunderbird School of Global Management

37. University of Toronto, Canada Master of Mathematical Finance(MMF)

Graduate Business school, Mathematical Finance Program

38. DePaul University, USA

Master of Science in Computational Finance (M.S.C.F.)

Loop Campus

39. DePaul University, USA Master of Science in Computational Finance

Loop Campus

40. Carnegie Mellon University, USA

Master of Science in Computational Finance

Tepper School of Business

41. Purdue University, USA M.S. Statistics - Computational Finance

College of Science, Department of Statistics

42. Purdue University, USA Master of Science in Mathematics - Computational Finance

College of Science, Department of Mathematics

43. Rice University, USA

Ph.D in Statistics - Computational Finance

George R Brown School of Engineering, Department of Statistics

44. Université Laval, Canada M.Sc. Financial Engineering

Institut de Finance Mathématique de Montréal

45. University of San Francisco, USA M.S. in Financial Analysis

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UK and Europe

University Name of program Department/Faculty

1. University of York, UK

Financial Engineering MSc

department of mathematics & department of economics

2. University of Manchester, UK

Quantitative Finance (Financial Engineering) MSc

Manchester Business School and the School of Mathematics

3. Imperial College London, UK

Risk Management and Financial Engineering MSc

Imperial College Business School

4. University of Essex, UK

Financial Engineering and Risk Management MSc

UNIVERSITY OF ESSEX

5. University of Birmingham, UK Financial Engineering MSc

UNIVERSITY OF BIRMINGHAM

6. Birkbeck, University of London, UK Financial Engineering MSc

BIRKBECK, UNIVERSITY OF LONDON

7. University of Reading, UK Financial Engineering MSc

UNIVERSITY OF READING

8. University of Bradford, UK Financial Engineering and Knowledge Management PgDip

UNIVERSITY OF BRADFORD

9. University of Bradford, UK Financial Engineering and Knowledge Management MSc

UNIVERSITY OF BRADFORD

10. University of Twente, Netherlands MSc in Industrial Engineering and Management - Specialization in Financial Engineering and Management

School of Management and Governance

11. University of Twente, Netherlands MSc in Applied Mathematics - Specialization in Financial Engineering

Faculty of Electrical Engineering, Mathematics and Computer Science

12. Mälardalen University, Sweden Master Program in Financial Engineering

School of Education, Culture and Communication

13. ICMA Centre (University of Reading), UK

Financial Engineering MSc

ICMA CENTRE (UNIVERSITY OF READING)

14. University of Ulster, UK Financial Engineering UNIVERSITY OF ULSTER

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BSc (Hons)

15. International University of Monaco, France

Master of financial engineering

International Business School

16. University of St.Gallen, Switzerland

Master of Business Engineering

Institute for Media and Communications Management, Business Engineering

17. Athens University of Economics and Business, Greece

Finance & Financial Engineering

AUEB's international business school

18. TiasNimbas Business School,Netherlands

Financial Management TiasNimbas Business School

19. Università della Svizzera italiana, Switzerland

M.Sc. - Finance Department of finance

20. University of Tartu, Estonia Financial and Actuarial Mathematics

Department of finance and banking

21. South Bank University, UK

M.Sc. - Accounting and Finance

Faculty of Business

22. South Bank University, UK

Accounting and Finance; Pg.Dip

Faculty of Business

23. University of Malta, Malta

M.A. - Financial Services

European Documentation and Research Centre

24. ESSEC Business School, France M.S. -Financial Engineering

Essec Business School

25. University of Oxford, UK

Mathematical and Computational Finance MSc

UNIVERSITY OF OXFORD

26. University of Limerick, Ireland

Master of Science in Computational Finance

Department of Accounting and Finance

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Latin America

University Name of program Department/Faculty

1. Universidad de Belgrano, Argentina Master of financial engineering

School of Economics and International Business

Asia pacific

University Name of program Department/Faculty

1. Nanyang Technological University, Singapore

Master of Science in Financial Engineering - Computing

Nanyang Business School

2. Nanyang Technological University, Singapore

Master of Science in Financial Engineering - Finance

Nanyang Business School

3. Nanyang Technological University, Singapore

Master of Science in Financial Engineering - Financial Mathematics and Statistics

Nanyang Business School

4. ESSEC Asian Center, Singapore Advanced Master's Degree in Financial Techniques - Financial Engineering Asia

ESSEC Asian Center

5. Multimedia University (MMU), Malaysia

Bachelor of Financial Engineering (Hons)

Cyberjaya Campus

6. Multimedia University (MMU), Malaysia

Bachelor of Financial Engineering

Cyberjaya Campus

7. Chinese University of Management, Hong Kong

MSc.-Financial Engineering

School of Economics and Finance

8. Victoria University of Wellington, New Zealand

Master of Financial Mathematics [M.Fin.Math.]

Faculty of Commerce and Administration

9. University of Melbourne, Australia

Master of Banking and Financial Services Law

University of Melbourne, Faculty of Business and Economics

10. Macquarie University, Australia

Master of applied finance

Faculty of Business and Economics