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Co-Terminal Bachelor of Science in Applied Mathematics / Master of Mathematical Finance

Illinois Tech offers a five-year, co-terminal Bachelor of Science in Applied Mathematics/Master of Mathematical Finance degree program for students who wish to combine a bachelor's degree in applied mathematics with a professional master's degree in mathematical finance, leading to a career in financial risk management as a quantitative financial analyst (also known as quant).

The Master of Mathematical Finance (MMF) program at Illinois Tech is a professional (non-thesis) interdisciplinary program offered jointly by the Department of Applied Mathematics in the College of Science and the Stuart School of Business. The MMF program provides individuals interested in pursuing careers in financial risk management with advanced education in theoretical, computational, and business aspects of quantitative methodologies relevant to the financial industry.

Our alumni are employed by such companies as CME Group, Citigroup, Discover Financial Services, Envestnet, Goldman Sachs, Intercontinental Exchange (ICE), JPMorgan Chase & Co., Morgan Stanley, OCC, PrivateMetrics Group, and Quantitative Risk Management, Inc. (QRM).

Students are immersed in the quantitative principles of valuation and hedging of financial securities. The quantitative core of the program is based on the theory of stochastic process and stochastic calculus, mathematical and computational finance, as well as advanced numerical and simulation methods. Based in the heart of Chicago, the program offers an ideal balance of theoretical knowledge and practical application.

The advantages of the co-terminal degree program are:

  1. Provide high-quality students opportunities to obtain both B.S. and master’s degrees within five years, cutting the length of a master’s degree by up to one year.
  2. Share up to nine credit hours between the two degrees.
  3. Offer students chances to link the advanced undergraduate course work with graduate course work.
  4. Offer an enhanced academic environment with accelerated learning.
  5. Simplify the graduate admission procedure.

Admission 

Students in the Bachelor of Science (B.S.) program in Applied Mathematics may apply for admission to the co-terminal Master of Data Science program after their second year (4 semesters or 80 credit hours including transfer credit) of undergraduate study. The student must have an overall GPA of at least 3.0 and a GPA of at least 3.25 in math and computer science.

See Graduate Admissions: Co-Terminal for information on how to apply.

FINANCIAL ASSISTANCE

Students in co-terminal degree programs are classified as undergraduates, and undergraduate scholarships continue to apply. See Graduate Admissions: Co-Terminal for important details.

Program Requirements 

Students must fulfill the requirements of both the B.S. in Applied Mathematics and the Master of Mathematical Finance. The B.S. in Applied Mathematics requires a minor, which in this case must be a minor in Business or Entrepreneurship. Nine credit hours may be shared by both programs by selecting three courses that count toward requirements in both degrees.

Course of Study 

 

Sample curriculum and program requirements Credits
Applied Mathematics requirements 42
MATH 100, 151, 152, 230, 251, 252, 332, 350, 380, 400, (410, 430, 431, or 454), 475  
Applied Mathematics electives 18

(including MATH 476 and MATH 478, and 3 shared graduate AM courses)

 
Humanities and Social Science requirements 21
Minor Subject requirements 15
(Business or Entrepreneurship)  
Interprofessional Projects  6
Computer Science requirement 4
(Two of CS 104, 115, 116) or (CS 105 and 201)  
Science requirement 4
(PHYS 123)   
Science electives  9
Free electives 9
Total 128

 

FIVE-YEAR SAMPLE PROGRAM

 

First semester (fall) Lect. Lab UG Credits Grad Credits
MATH 100 Introduction to the Profession 3 0 2 NA
MATH 151 Calculus I 4 1 5 NA
CS 115 Object Oriented Programming I 2 1 2 NA
HUM 2xx   3 0 3 NA
Science elective 3 0 3 NA
Totals 15 2 16 NA
Second semester (spring)        
MATH 152 Calculus II 4 1 5 NA
MATH 230 Introduction to Discrete Mathematics 3 0 3 NA
CS 116 Object Oriented Programming II 2 1 2 NA
PHYS 123 General Physics 3 3 4 NA
HUM/Social Sci. 3 0 3 NA
Totals 15 5 17 NA
Summer        
MATH 251 Multivariate & Vector Calculus 4 0 4 NA
Third Semester (fall)        
MATH 252 Introduction to Differential Equations 4 0 4 NA
MATH 332 Elementary Linear Algebra 3 0 3 NA
MATH 475 Probability 3 0 3 NA
Minor (Business or Entrepreneurship) 3 0 3 NA
Science elective 3 0 3 NA
Totals 16 0 16 NA
Fourth semester (spring)        
MATH 350 Introduction to Computational Mathematics 3 0 3 NA
MATH 476 Statistics (AM UG elective) 3 0 3 NA
MATH 380 Introduction to Mathematical Modeling 3 0 3 NA
Minor (Business or Entrepreneurship) 3 0 3 NA
HUM/Social Sci. 3 0 3 NA
HUM/Social Sci. 3 0 3 NA
Totals 18 0 18 NA
Fifth semester (fall)        
MATH 400 Real Analysis 3 0 3 NA
Math elective 3 0 3 NA
Minor (Business or Entrepreneurship) 3 0 3 NA
HUM/Social Sci. 3 0 3 NA
HUM/Social Sci. 3 0 3 NA
Free elective 3 0 3 NA
Totals 18 0 18 NA
Sixth semester (spring)        
MATH 454 Graph Theory & Applications 3 0 3 NA
MATH  478

Numerical Methods for Differential Equations
(AM UG elective)

3 0 3 NA
Minor (Business or Entrepreneurship) 3 0 3 NA
Science elective 3 0 3 NA
IPRO 397   3 0 3 NA
Totals 15 0 15 NA
Seventh semester (fall)        
MATH 542 Stochastic Processes (AM UG elective) 3 0 3 3
MATH 548 Mathematical Finance (AM UG elective) 3 0 3 3
MSF 505 Futures, Options, & OTC Derivatives 3 0 NA 3
Free elective 3 0 3 NA
Totals 12 0 9 9
Eighth semester (spring)        
Free elective 3 0 3 NA
MATH 582 Mathematical Finance II (AM UG elective) 3 0 3 3
MSF 575 C++ with Financial Applications 3 0 NA 3
IPRO 497   3 0 3 NA
Totals 12 0 9 6
Summer        
Internship (or electives)        
Ninth semester (fall)        
MATH 565 Monte Carlo Methods in Finance 3 0 NA 3
MSF 526 Computational Finance 3 0 NA 3
Graduate AM elective 3 0 NA 3
Minor (Business or Entrepreneurship) 3 0 3 NA
Totals 12 0 3 9
Tenth semester (spring)        
MSF 566 Financial Time Series Analysis 3 0 NA 3
MSF 576 OOP & Algorithmic Trading Systems 3 0 NA 3
MATH 586 Theory & Practice of Fixed Income Modeling 3 0 NA 3
HUM/Social Sci. 3 0 3 NA
Totals 14 2 3 9
Total UG credit hours     128  
Total Grad credit hours       33