Financial Engineering Curriculum
The interdisciplinary MSFE Program is designed for students with strong quantitative backgrounds who have career goals of becoming risk management officers, derivatives analysts or traders. The program is rigorous and requires the completion of 36 credit hours of coursework, including an industry-based project. The curriculum combines strong quantitative skills from mathematics with risk management and dynamic valuation skills from finance to address problems such as derivative securities valuation, portfolio structuring, risk management, and scenario simulation. The Master of Science in Financial Engineering curriculum meets the guidelines established by the International Association of Financial Engineers.
Derivatives I Financial Management I Topics in Probability Theory and Computational Finance Advanced Security and
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Derivatives II Fixed Income Markets Financial Mathematics Time Series Analysis
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Financial Engineering Legal Aspects of Financial Seminar: Modeling Projects |
Course |
Fall: 1st Semester
Derivatives I - FIN 66080:
An introduction to the theory and practice of pricing and hedging of derivative securities. Coverage of equity and index, foreign currency, commodity, and interest-rate derivatives. Basic mathematical concepts and the institutional structure of derivative markets are discussed.
Financial Management I - BAD 66061:
Study of financial decision-making processes within a firm. Emphasis on applications and strategic planning in investment, financing, dividend and working capital decisions. The course also covers market microstructure including participants, exchange structure, trading platforms and liquidity and volatility issues related to exchange and off-exchange trading.
Advanced Security and Investment Theory - BAD 6/76066:
The course provides an introduction to security analysis and portfolio management. The focus is placed on the financial theory and analytical tools for making investment decisions. The course covers a broad range of topics including the financial markets and instruments, portfolio theory and asset allocation, the capital asset pricing model, multifactor pricing model and their applications, market efficiency and behavioral finance, stock valuation techniques, performance evaluation and portfolio management. In addition, a section of this course also seeks to understand macroeconomic economic conditions, macroeconomic news announcements and their implications for trading along with different methods to forecast.
Topics in Probability Theory and Stochastic Processes - MATH 4/50051:
Topics from conditional expectations, Markov chains, Markov processes, Brownian motion and martingales, and their applications to stochastic calculus.
Computational Finance - MATH 6/72203:
Basic numerical methods (floating-point arithmetic, numerical linear algebra, solutions of non-linear equations, interpolation, curve fitting, splines, differentiation, integration, Monte-Carlo methods, ordinary differential equations) numerical solutions of PDEs (finite-difference methods for parabolic PDE's, stability, convergence, applications to Black-Scholes equations, free-boundary problems, applications to pricing American options) and probabilistic methods.
Spring: 2nd Semester
Derivatives II - FIN 6/76081:
Coverage of exotic options, discrete and continuous pricing models, and pricing techniques. Develops the economic foundation of the theory of derivatives and a mathematical toolkit to analyze standard instruments and 'dissect' exotic ones.
Fixed Income Markets - FIN 6/76085:
Provides a quantitative approach to fixed income instrument use. Covers the mathematics of bond pricing, term structure analysis, and pricing of credit risk. Trees and Monte Carlo methods of valuation are presented.
Financial Mathematics - MATH 6/70070:
Topics from replication of trading strategies, arbitrage, completeness, martingale representation theorem, fundamental theorem of finance, stochastic differential equations, Black-Scholes formula of option pricing.
Time Series Analysis - ECON 6/7/82056:
Covers various kinds of time series models, including ARIMA, GARCH, unit roots and co-integration, and vector autoregressive models. Students will gain hands-on experience with all models learned in this course.
Summer: 3rd Semester
Financial Engineering - FIN 6/76084:
Coverage of VaR, hedging techniques, synthetic assets, and volatility trading. Risk management and risk control models are covered. Surveys standard approaches to measuring and modeling financial risk from the risk manager perspective.
Legal Aspects of Financial Engineering - FIN 66075:
Coverage of the legal, regulatory and compliance aspects of derivative use and the current legal standing of derivatives and regulatory issues associated with derivatives. The issues of risk measurement, risk oversight, and transparency of derivatives markets and disclosure issues are covered.
INTERNSHIP: Seminar: Modeling Projects - MATH 4/52091:
Individual and small-group projects concerned with the formulation and analysis of mathematical models in a variety of areas with the focus on finance for the financial engineering students. Written and oral reports are required.
Quantitative |
Area |
Topics |
Courses* |
Calculus
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Differentials, infinite series, Taylor's formula, partial derivatives, multiple integrals
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Math12002 Analytic Geometry and Calculus I Math12003 Analytic Geometry and Calculus II Math 22005 Analytic Geometry and Calculus III |
Linear Algebra |
Matrices, vectors, determinants, linear systems of equations, linear independence, bases, eigenvalues, eigenvectors |
Math 21001 Linear Algebra with Applications |
Ordinary Differential Equations |
1st-order ODEs, solution techniques, initial value problems, exponential growth/decay, logistic model equilibrium, steady state 2nd-order linear constant-coefficient ODEs |
Math 32044 Introduction to |
Probability |
Continuous and discrete distributions, multivariate distributions and independence, ordinary and conditional expectations, Central Limit Theorem |
Math 40011 Introduction to Probability |
Statistics |
Regression analysis including detection of and solutions to various violations of classic regression assumptions (heteroskedasticity, autocorrelation, multicollinearity and simultaneity) |
Math 30011 Basic Probability and Statistics |
Computer Programming |
Programming ability in a high-level language such as C, C++, Fortran (77 or 90/95), Basic, Visual Basic, or Matlab |
CS 10051 Introduction to Computer Science CS 23021 Introduction to Object-Oriented |
Economics |
Basic Micro and Macro Economic topics including supply and demand functions, market structure, and the role of money |
ECON 22060 Principles of Microeconomics ECON 22061 Principles of Macroeconomics |
Accounting |
Basic financial statement analysis of balance sheet and income statement information. Fundamentals of taxation and the corporate form of organization. |
ACCT 23020 Introduction to Financial Accounting |
* These courses cover the necessary topics and more |
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