Master of Science in Finance Hero Photo

Curriculum and Program Requirements

The Master of Science in Finance (MSF) is a broad and flexible graduate program in finance. The MSF program is designed to be a 3-semester residential program. The curriculum consists of preparatory courses, required courses and elective courses. Students need to complete a minimum of 40 graduate level credits, at least 28 of which, including preparatory and required classes, are in Finance

Preparatory Courses*:0-10 hours
Required Courses*:8 hours
Professional Development:2 hours
Finance Electives:10+ hours
Other Electives (may also be in Finance):12+ hours
ESL Courses (if required):0 hours
Total:40+ hours

*Most preparatory and required courses would be completed in the first fall semester; however, dependent upon a student’s background and career goals, some preparatory courses may be waived, substituted, or taken in the spring semester.

Preparatory Courses

MSF students are from a variety of backgrounds, not necessary in business or finance. Some students may need to work on their fundamental knowledge in important areas during their first semester. We offer three preparatory classes in the fall semester:

  • FIN 580 Corporate Finance (4 credit hours)
    This course will cover a broad range of corporate finance topics providing a comprehensive overview of the material. At the conclusion of the course, students will understand the broad fundamental concepts of corporate finance in a unifying model. The text we will be using provides an excellent introduction to the concepts. Topics can be explored in more detail based on class interest and experience. Required but may be waived if the student has the appropriate training at undergraduate level.
  • FIN 504 Accounting for Financial Analysis (2 credit hours)
    Introduces the fundamentals of reading and understanding financial statements. The basics financial statements will be introduced and there will be in-depth examples and cases demonstrating how the statements are constructed and how to carry out basic analysis. At the end of the class students should feel comfortable understanding a typical annual report. Required but may be waived if the student has the appropriate training at undergraduate level.
  • FIN 502 Quantitative Finance (2 credit hours)
    This course provides an introduction to quantitative methods that are applicable in several areas of finance; presents concepts and methodologies from probability theory, statistical inference, and regression analysis; emphasis is placed on software applications of real data on stock returns, CAPM and Fama-French models, and cross-section firm data. Required but may be waived if the student has the appropriate training at undergraduate level.
  • FIN 580 GP Data Science and Python for Finance (2 credit hours)
    The financial industry is increasingly adopting Python. Libraries such as NumPy and pandas provide extraordinary insights into data analysis. This course focuses specifically on introducing Python for financial analysis. The first part of the course provides a detailed understanding of Python basics. Data structures, numerical computing with NumPy, and data analysis with pandas will be explained. The second part applies Python in solving problems in corporate finance and performing investment analysis. Topics include capital budgeting decisions, equity valuation, risk and return, portfolio optimization, and technical trading strategies.

Required Courses

The program is focused on providing a flexible set of classes for students to tailor to their own specific career aims. There are only three required courses in the program:

  • FIN 501 Economics of Stock Market Fundamentals (4 credit hours)
    Firms’ long-run value ultimately depend on their business fundamentals. This course covers micro- and macro-economic drivers of such fundamentals, such as consumer demand, market competitiveness, government regulation, interest rates, business cycles, and monetary policy. Also includes topics in risk and intertemporal decision-making.
  • FIN 511 Investments (4 credit hours)
    Introduction to investment analysis, including the theory and implementation of portfolio theory, empirical evidence on the performance of financial assets, evaluation of portfolio investment strategies, and the extension of diversification to international markets.
  • FIN 581 Professional Development (2 credit hours)
    Effective communication skills are one of the most sought-after traits of business leaders across industries and throughout the world. Understanding the world around you, as well as communicating clearly and persuasively is critical to your success as a student, as an employee, and as a leader in the business world. These skills will help establish your own credibility and lead you to become an effective leader among your peers and colleagues. This course will introduce successful strategies for structuring both written and verbal communication in the business world, with an eye toward the specific outcomes listed below.

Specializations

The MSF program offers courses in the following areas of finance: asset management, corporate finance, data analytics and fintech, quantitative finance, real estate, and finance research. Students can specialize in one of these areas by following a specialization track. By specializing in a specific area of finance, students become more marketable to employers in that area. A minimum of 16 credits of courses in any chosen area is needed to be awarded a specialization. Please click on the links below to see the extensive offerings in each specialization.


Asset Management Specialization

Prerequisite Elective: FIN 511 Investments (Fall/Spring)

Capstone Elective: FIN 589 Applied Portfolio Management (Fall/Spring)

Other Electives:

  • FIN 512 Financial Derivatives
  • FIN 515 Fixed Income Portfolios
  • FIN 518 Financial Modeling
  • FIN 526 Investment Banking
  • FIN 528 Cases in Financial Derivatives
  • FIN 529 Applied Financial Analysis
  • FIN 535 Wealth Management (2 credit hours)
  • FIN 545 Real Estate Investment
  • FIN 550 Big Data Analytics in Finance
  • FIN 551 International Finance
  • FIN 552 Applied Financial Econometrics
  • FIN 580 Social Impact of Investing (2credit hours)
  • FIN 580 Quantamental Investment
Corporate Finance Specialization

Prerequisite Elective: FIN 521 Advanced Corporate Finance (Spring/Fall)

Capstone Elective: FIN 522 Cases in Financial Strategy (Fall)

Other Electives:

  • FIN 518 Financial Modeling
  • FIN 527 Mergers & Acquisitions (2 or 4 credit hours)
  • FIN 526 Investment Banking
  • FIN 529 Applied Financial Analysis
  • FIN 536 Banking and Financial Regulation
  • FIN 538 Enterprise Risk Management
  • FIN 550 Big Data Analytics in Finance
  • FIN 551 International Finance
  • FIN 580 Growth Corp Capital Funding
  • FIN 580 Entrepreneurship thru’ Acquisition
  • ACCY 502 Accounting Analysis II
  • ACCY 517 Financial Statement Analysis
Finance Research (PhD Specialization)

Prerequisite Elective: FIN 591 Theory of Finance (Fall)

Capstone Elective:

  • FIN 552 Applied Financial Econometrics or FIN 592 Empirical Analysis in Finance Econometrics (Fall)

Other Electives:

  • FIN 580 Financial Data Mgt. & Analysis
  • FIN 580 Microeconomic Theory I
  • FIN 594 Seminar in Corporate Finance (Spring)
  • FIN 594 Seminar in Corporate Finance (Fall)
Quantitative Finance Specialization

Prerequisite Elective: FIN 512 Financial Derivatives (Spring/Fall)

Capstone Elective: FIN 514 Valuation of Complex Derivative Securities (Spring/Fall)

Other Electives:

  • FIN 503 Quantitative Finance II (2 credit hours)
  • FIN 513 Applications of Financial Engineering
  • FIN 515 Fixed Income Portfolios
  • FIN 516 Term Structure Models (2 credit hours)
  • FIN 517 Adv. Term Structure Models (2 credit hours)
  • FIN 528 Cases in Financial Derivatives
  • FIN 537 Financial Risk Management
  • FIN 544 Algorithmic Trading Systems Design & Testing
  • FIN 552 Applied Financial Econometrics
  • FIN 553 Machine Learning in Finance
  • FIN 556 Algorithmic Market Microstructure 
  • FIN 580 Options Trading & Market Making
  • FIN 580 Quantamental Investment
  • FIN 580 Advanced Python for Finance (2 credit hours)
Data Analytics and Fintech Specialization

Prerequisite Elective:

  • FIN 503 Quantitative Finance II (2 credit hours) (Spring/Fall)
  • FIN 580 Advanced Python for Finance (2 credit hours) (Spring/Fall)

Capstone Elective: FIN 550 Big Data Analytics in Finance (Fall/Spring)

Other Electives:

  • FIN 537 Financial Risk Management
  • FIN 552 Applied Financial Econometrics
  • FIN 553 Machine Learning in Finance
  • FIN 555 Financial Innovation
  • FIN 580 Quantamental Investment
  • FIN 580 Financial Data Mgt. & Analysis

Concentrations

A concentration is an extension of a graduate major comprised of a coherent set of courses some or all of which count toward the major. Students must take a minimum of 12 credits of the required courses in order to earn a concentration.

The MSF offers two concentrations. Unlike the specialization, the concentration will appear on your final transcript:

Electives available for students

All of our extensive elective offerings are included in at least one of the MSF Specializations listed above. Here is a list of the electives that have been offered in the MSF program in previous semesters. Please visit the Finance Course Catalog to view course descriptions.

  • ACCY 501: Accounting Analysis I
  • ACCY 517: Financial Statement Analysis and Valuation
  • FIN 447: Real Estate Development
  • FIN 503: Quantitative Finance II
  • FIN 512: Financial Derivatives
  • FIN 513: Applications of Financial Engineering
  • FIN 514 Valuation of Complex Derivative Securities
  • FIN 515: Fixed Income Portfolios
  • FIN 516 Term Structure Models
  • FIN 517: Advanced Term Structure Models
  • FIN 518: Financial Modeling
  • FIN 521: Advanced Corporate Finance
  • FIN 522: Cases in Financial Strategy
  • FIN 526: Investment Banking
  • FIN 527: Mergers and Acquisitions Topics
  • FIN 528: Cases in Financial Derivatives
  • FIN 529: Applied Financial Analysis
  • FIN 535: Wealth Management
  • FIN 536: Banking and Financial Regulation
  • FIN 537: Financial Risk Management
  • FIN 538: Enterprise Risk Management
  • FIN 541: Real Estate Fundamentals
  • FIN 543: Legal Issues in Real Estate
  • FIN 544: Urban Real Estate Valuation
  • FIN 545: Real Estate Investment
  • FIN 546: Real Estate Financial Markets
  • FIN 547: Real Estate Development 
  • FIN 550: Big Data Analytics in Finance for Predictive and Causal Analysis
  • FIN 551: International Finance
  • FIN 552: Applied Financial Econometrics
  • FIN 553: Machine Learning in Finance
  • FIN 554 Algorithmic Trading Systems Design and Testing
  • FIN 555: Financial Innovation
  • FIN 556: Algorithmic Market Microstructures
  • FIN 580: Financial Data Management & Analysis
  • FIN 580: Adv. Data Sci & Python for Finance
  • FIN 580: Computer Science for Quants
  • FIN 580: Social Impact Investing
  • FIN 580: Entrepreneurship Thru Acquisition
  • FIN 580: Option Trading Market Making
  • FIN 580: Practical Asset Allocation
  • FIN 580: Special Topics in Wealth Management
  • FIN 580: Growth Corporate Capital Funding
  • FIN 580 Adv. Topics in Wealth Management
  • FIN 580: General Microeconomic Theory
  • FIN 580: Appl of Derivative Strategies
  • FIN 580: Adv. Real Estate Investment Cases
  • FIN 580: MSF Mentoring
  • FIN 580: Quantamental Investment
  • FIN 580: Pvt Banking & Ins Wealth Mgt
  • FIN 582: Project Management
  • FIN 583: Practicum
  • FIN 589: Applied Portfolio Management
  • FIN 591: Theory of Finance
  • FIN 592: Empirical Analysis in Finance
  • FIN 594: Seminar in Corporate Finance

Gies News and Events