Course Descriptions

By Semester

First Semester - Fall - 17 hours

Course title and description Core/Elective Credit Hours

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

IE 517 Machine Learning in Finance lab (first half of semester): Machine learning is an increasingly important tool in every financial engineer’s toolbox. Machine Learning includes the design and the study of algorithms that can learn from experience, improve their performance and make predictions. In this introductory course students will explore the main concepts behind several different machine learning algorithms and gain practical experience implementing them using Python and several of the most frequ5ently used packages; pandas, NumPy, scikit-learn, etc.. Students will also learn how to construct and interpret their own machine learning models in Python.

Core

2

FIN 553 Machine Learning: (second half of semester): 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

2

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

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

FIN 581 Professional Development: This course is designed to enrich student coursework experience through a series of invited speaker lectures (MSFE Practitioner Series) field trips and conversation courses aimed at bridging the gap between academic work and industry. Students are expected to meet standards of professional conduct during MSFE related activities -see handbook for more details.

Elective - highly suggesteda

1

Total hours 17a
aSixteen hours are required for the first semester but students are strongly encouraged to enroll for FIN 581 Professional Development for 1 credit hour.


Semester 1 Registration is static and will look like the following:

Semester 1 Required/Core Hrs
FIN 500 4
FIN 517 (1st 8 weeks) 2
FIN 553 (2nd 8 weeks) 2
IE 522 4
IE 523 4
Total Required Core 16
FIN 581 (strongly suggested) 1
Semester Total 17



 

Second Semester - Spring - 16 hours

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

IE 597/FIN583 Financial Engineering Project/Practicum: 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 timingb

4

  Total hours 16
bIE 597/FIN583 Financial Engineering Project/Practicum is a required component of the MSFE program and students may request to enroll early in the second semester of the program. See more information about the practicum project here.




Semester 2 Registration Examples:

Example 1 Hrs
FIN 512 4
FIN 525 4
IE597/FIN 583 Practicum 4
Elective/Concentration #1 4
Semester Total 16
Example 2 Hrs
FIN 512 4
FIN 525 4
Elective/Concentration #1 4
Elective/Concentration #2 4
Semester Total 16

 





 

Summer Semester (Internship)

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

Course title and description Core/Elective Credit Hours

FIN 516 Term Structure Models:(1st 8 weeks required). The LIBOR market model (LMM), its calibration, implementation, and use in valuing interest rate derivatives, including interest rate exotics and Americanstyle 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 c

2

IE 524 Optimization in Finance: (1st 8 weeks required). 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-atrisk, and other risk measures. c

Core c 2

IE 597/FIN583 Financial Engineering Project/Practicum: : 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 timingb 4


And /or

 
And/or
Approved Elective(s)/Concentration Course Elective 4-8
Total hours 16
bIE 597/FIN583 Financial Engineering Project/Practicum is a required component of the MSFE program. It must be taken in the third semester if not taken in the second semester. See more information about the project here.
c
FIN 516 and IE 524 are both required for 1st 8 weeks of the semester with the 2nd 8 weeks considered elective for each course



Semester 3 Registration Examples:

The third semester allows for considerable variablity 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
IE597/FIN 583 Practicum 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
IE597/FIN 583 Practicum 4
Elective/Concentration #1 4
   
Semester Total 16



 

Course Overloads

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). .