Course Descriptions
First Semester - Fall - 16 hours |
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Course title and description |
Core/Elective |
Credit Hours |
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FIN 500 Introduction to Finance: Introduction to financial markets, some of the most common securities traded in financial markets, and theories of valuation, with a brief overview of some of the important ideas in corporate finance. Net present and future value; internal rate of return; Gordon dividend model; fixed-income analysis; random cash flow; Markovitz’ portfolio theory and diversification; Sharpe’s capital asset pricing model; capital market line; free cash flow for equity evaluation; forward markets, futures and options; binomial and Black-Scholes option pricing; capital structure and corporate restructuring. |
Core |
4 |
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FIN 553 Machine Learning: Machine Learning includes the design and the study of algorithms that can learn from experience, improve their performance and make predictions. In this continuation course students will explore advanced topics in machine learning including neural net architecture, Reinforcement Learning, recurrent neural nets (RNNs) and long short-term memory (LSTMs). Applications include option pricing, portfolio selection and time series modeling. Students will gain practical experience implementing these models in Python with frequently used packages such as TensorFlow. |
Core |
4 |
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IE 522 Statistical Methods in Finance: Methods of statistical modeling of signals and systems with an emphasis on finance applications. Review of linear algebra, probability theory, and spectral analysis. Linear Time Invariant (LTI) models, ARX models, Least-squares methods, Maximum likelihood methods, non-parametric and frequency-domain methods, convergence, consistency and identifiability of linear models and asymptotic distribution of parameter estimates, and techniques of model validation. Principal Component Analysis (PCA) for dimension reduction, ARCH and GARCH processes and their related models, implementation/application and case-studies of Recursive Identification, and Monte Carlo Simulation. |
Core |
4 |
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IE 523 Financial Computing: Review of C++ programming: structures, classes, I/O, C++ standard libraries, Recursion. Linear Algebra tools and MILP solvers in C++. Computational aspects of probability, statistics and simulation in C++. Methods: Root-finding, Taylor’s Expansion, FFTs, Dynamic Programming, Monte Carlo Methods. Financial computing case studies in C++ |
Core |
4 |
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Total hours | 16a |
Semester 1 Registration is static and will look like the following:
Semester 1 Required/Core | Hrs |
FIN 500 | 4 |
FIN 553 | 4 |
IE 522 | 4 |
IE 523 | 4 |
Total Required Core | 16 |
Second Semester - Spring - 16 hours |
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Course title and description | Core/Elective | Credit Hours |
FIN 512 Financial Derivatives: Introduction to options, futures, swaps and other derivative securities; examination of institutional aspects of the markets; theories of pricing; discussion of simple as well as complicated trading strategies (arbitrage, hedging, and spread); applications for asset and risk management. |
Core |
4 |
IE 525 Stochastic Calculus & Numerical Models in Finance: This course explores PDE and simulation methods for pricing derivatives. Specifically, we will derive the Black-Scholes PDE and develop finite-difference techniques for pricing vanilla, path-dependent and exotic options. Moreover, we will discuss Monte Carlo methods and variance reduction techniques, for pricing options as well as calculating their sensitivities |
Core | 4 |
Approved Elective(s)/Concentration Course(s) | Elective | 4-8 |
And /or |
And/or |
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IE 583 MSFE Practicum Project: Project-based course. Students work individually or in teams to develop solutions to problems in finance supplied by industry or by a faculty member associated with the MSFE program. A midterm and final report summarize the work of the term.b |
Core - optional timing |
4 |
Total hours | 16 |
Semester 2 Registration Examples:
Example 1 | Hrs |
FIN 512 | 4 |
IE 525 | 4 |
IE 583 MSFE Practicum Project | 4 |
Elective/Concentration #1 | 4 |
Semester Total | 16 |
Example 2 | Hrs |
FIN 512 | 4 |
IE 525 | 4 |
Elective/Concentration #1 | 4 |
Elective/Concentration #2 | 4 |
Semester Total | 16 |
Summer Semester (Internship) |
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Students are encouraged to seek summer internships. If successful in securing an internship, the student will register for a 0 credit hour course. Registering for this course will ensure that the internship is reflected on the academic transcript. |
Third Semester - Fall - 16 hours |
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Course title and description | Core/Elective | Credit Hours |
FIN 516 Term Structure Models: The LIBOR market model (LMM), its calibration, implementation, and use in valuing interest rate derivatives, including interest rate exotics and American style options with the LMM. Review of the simpler Hull-White, Black-Derman-Toy, and Black-Karasinski models that are still in widespread use. Applications of Monte Carlo methods (in the LMM) and finite-difference or “tree” methods (in the other models). c |
Core |
2 |
IE 524 Optimization in Finance: Basic optimization methods for financial engineering, optimization modeling languages such as AMPL and GAMS, and optimization software including the NEOS server. Linear, quadratic, nonlinear, dynamic, integer, and stochastic programming and their applications to portfolio and asset management. Optimization using values-at-risk, conditional values-at-risk, and other risk measures. c |
Core | 2 |
IE 583 MSFE Practicum Project: : Project-based course. Students work individually or in teams to develop solutions to problems in finance supplied by industry or by a faculty member associated with the MSFE program. A midterm and final report summarize the work of the term.b |
Core - optional timing | 4 |
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And/or |
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Approved Elective(s)/Concentration Course | Elective | 4-8 |
Total hours | 16 |
Semester 3 Registration Examples:
The third semester allows for considerable variability and selectivity within the curriculum. If the practicum project was not taken in the second semester, it must be taken in the third semester (see examples 1 & 4 below). Registration options for Semester 3 might be as follows:
Example 1 | Hrs |
FIN 516 (1st 8 weeks) | 2 |
FIN 524 (1st 8 weeks) | 2 |
IE 583 MSFE Practicum Project | 4 |
Elective/Concentration #1 | 4 |
Elective/Concentration #2 | 4 |
Semester Total | 16 |
Example 2 | Hrs |
FIN 516 (full semester) | 4 |
FIN 524 (full semester) | 4 |
Elective/Concentration #1 | 4 |
Elective/Concentration #2 | 4 |
Semester Total | 16 |
Example 3 | Hrs |
FIN 516 (1st 8 weeks) | 2 |
FIN 524 (1st 8 weeks) | 2 |
Elective/Concentration #1 | 4 |
Elective/Concentration #2 | 4 |
Elective/Concentration #3 | 4 |
Semester Total | 16 |
Example 4 | Hrs |
FIN 516 (full semester) | 4 |
FIN 524 (full semester) | 4 |
IE 583 MSFE Practicum Project | 4 |
Elective/Concentration #1 | 4 |
Semester Total | 16 |
Course Overloads |
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Students may request to take additional electives beyond the required 16 hours each semester with approval from the program director. University and Graduate College guidelines apply. Read more here about the policy (scroll down to "overload" section on page). . |