Finance Master of Science Degree
Finance
Master of Science Degree
A master of science in finance unlocks the world of finance and sets you on a path toward managerial success.
Overview
- Manage a real investment portfolio with the Finance Management Association.
- The curriculum in the MS in Finance is designed to prepare you to take the Chartered Financial Analyst® (CFA) exam.
Encompassing corporate finance, investment management, banking, insurance, consulting, and more, RIT’s master of science in finance unlocks the world of finance and prepares you for managerial careers in corporate finance, investment analysis, and portfolio management, financial consulting, and financial institutions.
RIT's Master of Science in Finance
Top finance master's programs, like RIT's master of science in finance, prepare you to take the Chartered Financial Analyst® (CFA) exam–the most respected and recognized investment management designation in the world. In this highly flexible program, you’ll complete courses in accounting for decision makers, financial analysis for managers, securities and investment analysis, options and futures, and more. In addition, you'll choose elective courses in a wide range of dynamic areas–portfolio management, financial analytics, equity analysis, stock market algorithmic trading, financial modeling and analysis, and more–that prepare you for today's dynamic careers in finance. enhance your marketability and expand your job prospects.
Finance Careers
Graduates of RIT's master of science in finance are prepared for outstanding career opportunities in a range of finance positions, including financial engineer, risk analyst, research associate, quantitative analyst, quantitative investment analyst, credit risk analyst, quantitative strategist, data analyst, and more.
Our alumni are employed at diverse financial firms such as AMG Technology, Invata Intralogistics, T3 Trading Group, LLC, TD Securities, MAI Capital Management, and more.
Students are also interested in: Accounting and Analytics MS, Computational Finance MS
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Discover how graduate study at RIT can help further your career objectives.
Join us virtually
Discover how graduate study at RIT can help further your career objectives.
Join us virtually
Discover how graduate study at RIT can help further your career objectives.
Careers and Experiential Learning
Typical Job Titles
| Financial Engineer | Risk Analyst |
| Research Associate | Quantitative Analyst |
| Quantitative Investment Analyst | Credit Risk Analyst |
| Quantitative Strategist | Data Analyst |
Salary and Career Information for Finance MS
Cooperative Education
Cooperative education, or co-op for short, is full-time, paid work experience in your field of study. And it sets RIT graduates apart from their competitors. It’s exposure–early and often–to a variety of professional work environments, career paths, and industries. RIT co-op is designed for your success.
Cooperative education is optional but strongly encouraged for graduate students in the finance program.
Curriculum for Finance MS
Finance, MS degree, typical course sequence
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| First Year | ||
| ACCT-603 | Accounting for Decision Makers A graduate-level introduction to the use of accounting information by decision makers. The focus of the course is on two subject areas: (1) financial reporting concepts/issues and the use of general-purpose financial statements by internal and external decision makers and (2) the development and use of special-purpose financial information intended to assist managers in planning and controlling an organization's activities. Generally accepted accounting principles and issues related to International Financial Reporting Standards are considered while studying the first subject area and ethical issues impacting accounting are considered throughout. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Fall, Spring, Summer). |
3 |
| FINC-721 | Financial Analysis for Managers An examination of basic financial theories, techniques, and practices. Topics include: time value of money, valuation, capital asset pricing, risk and diversification, cost of capital, capital budgeting techniques and spreadsheet analysis. (Prerequisites: ACCT-603 or equivalent course.) Lecture 3 (Fall, Spring). |
3 |
| FINC-725 | Securities and Investment Analysis A survey of topics in investment analysis, including the study of financial markets, features of various financial assets and security pricing. Focus is on individual security analysis (as distinct from portfolio analysis). Asset pricing theory is used in valuing securities. Practical issues in equity valuation are discussed including risk evaluation, macroeconomic/industry/competitive analysis, and the use of corporate SEC filings. (Prerequisites: FINC-721 or equivalent course.) Lecture 3 (Fall, Spring). |
3 |
| FINC-740 | Options and Futures This course focuses on financial derivative securities. Their role in financial management is becoming increasingly important, especially in portfolio management. This course covers valuation of various options and futures as well as their use in risk management. Specific topics include options and futures pricing models, options strategies, and contemporary topics such as index arbitraging. (Prerequisites: FINC-721 or equivalent course.) Lecture 3 (Fall, Spring). |
3 |
| FINC-790 | Field Exam Preparatory All MS-Finance students take a field exam at the end of their program. This course provides basic help to students taking this exam. (all required finance courses in the MS-finance program) (This course is restricted to FINC-MS Major students.) Comp Exam 1 (Fall, Spring, Summer). |
1 |
Finance Electives |
9 | |
STEM Electives |
9 | |
| Total Semester Credit Hours | 31 |
|
Finance electives
| FINC-722 | Financial Management II This advanced course in corporate finance focuses on financing policies, financial planning/control, and other advanced corporate topics. Specific topics include the financing process, alternative financing instruments, restructuring, cost of capital, corporate applications involving options, working capital management and the use of financial budgets/forecasts. (Prerequisites: FINC-721 or equivalent course.) Lecture 3 (Fall, Spring). |
| FINC-732 | Portfolio Management This course extends the knowledge of risk and return in a portfolio context to portfolio management. Topics include portfolio optimization, diversification strategies, hedging strategies and performance evaluation. A variety of investment tools (e.g., fixed income securities) and investment contexts (e.g., pensions) will be studied. (Prerequisites: FINC-725 or equivalent course.) Lecture 3 (Fall, Spring). |
| FINC-742 | Financial Modeling and Analysis Students apply computer technology to solve finance-related problems using a variety of analytical methods. Analytical methods include spreadsheet modeling, mathematical optimization, regression, decision tree analysis, and Monte Carlo Simulation. Typical topics covered are financial forecasting, pro-forma financial statements, equity valuation, cash budget forecasts, and portfolio analysis. This is a hands-on course that focuses on collecting, managing and analyzing financial data. (Prerequisites: FINC- 722 and FINC-725 or equivalent courses.) Lecture 3 (Fall, Spring). |
| FINC-758 | Seminar in Finance Special topics seminars offer an in-depth examination of current events, issues and problems unique to finance. Specific topics will vary depending upon student and faculty interests and on recent events in the business world. Seminar topics for a specific semester will be announced prior to the course offering. These seminars may be repeated for credit since topics will normally vary from semester to semester. (instructor-determined) Lecture 3 . |
| FINC-760 | Finance in a Global Environment This course has a specific focus on international business problems that are financial in nature. Topics include an examination of the international environment the firm operates in, international investment, exchange rates and the management of risks arising from shifting exchange rates, and the problems of short and long-term asset and liability management. (Pre or Corequisites: FINC-721 or equivalent course.) Lecture 3 (Fall, Spring). |
| FINC-761 | Stock Market Algorithmic Trading The course is a “hands-on” lab-based class designed to help students develop algorithmic trading strategies to invest in the stock market that can be implemented by retail and professional traders. What sets this course apart from many others is a strong emphasis on practical application with the purpose of building marketable skills for careers in finance. Concepts are not only taught, they are brought to life by learning how to design algorithmic trading models through the use of a computerized trading platform, that allows back-testing of data on thousands of different stocks. The software platform includes an automated wizard for building advanced technical trading models without programming knowledge; but also has an embedded programming language, similar to C-sharp, for those students that have those skills and elect to use them. (Knowledge of programming is not required; and there are no pre or co-requisites; but a lap-top is strongly recommended.). Lecture 3 (Spring). |
| FINC-772 | Equity Analysis Students learn about various equity markets, trading, and valuation. The focus of this course is on valuing equities using widely used methods and in forming and analyzing equity portfolios. Students also learn portfolio optimization methods. (Prerequisites: FINC-671 or equivalent course.) Lecture 3 (Fall). |
| FINC-773 | Debt Analysis Students learn about various debt markets, trading, and valuation. The focus of this course is on valuing debt instruments using widely used methods and in forming and analyzing debt portfolios. (Co-requisites: FINC-671 and FINC-721 or equivalent courses.) Lecture 3 (Spring). |
| FINC-780 | Financial Analytics This course provides a survey of financial analytics applications in contexts such as investment analysis, portfolio construction, risk management, and security valuation. Students are introduced to financial models used in these applications and their implementation using popular languages such as R, Matlab, and Python, and packages such as Quantlib. A variety of data sources are used: financial websites such as www.finance.yahoo.com, government sites such as www.sec.gov, finance research databases such as WRDS, and especially Bloomberg terminals. Students will complete projects using real-world data and make effective use of visualization methods in reporting results. There are no pre or co-requisites; however, instructor permission is required – student aptitude for quantitative work will be assessed; waived for students enrolled in quantitative programs such as the MS-Computational Finance which have pre-requisites in the areas of calculus, linear algebra, and programming. Lecture 3 (Fall). |
STEM electives
| ACCT-745 | Accounting Information and Analytics The objective for this course is helping students develop a data mindset which prepare them to interact with data scientists from an accountant perspective. This course enables students to develop analytics skills to conduct descriptive, diagnostic, predictive, and prescriptive analysis for accounting information. This course focuses on such topics as data modeling, relational databases, blockchain, visualization, unstructured data, web scraping, and data extraction. (Prerequisites: ACCT-110 or ACCT-603 or equivalent course.) Lecture 3 (Fall, Summer). |
| BANA-680 | Data Management for Business Analytics This course introduces students to data management and analytics in a business setting. Students learn how to formulate hypotheses, collect and manage relevant data, and use standard tools such as Python and R in their analyses. The course exposes students to structured data as well as semi-structured and unstructured data. There are no pre or co-requisites; however, instructor permission is required for students not belonging to the MS-Business Analytics or other quantitative programs such as the MS-Computational Finance which have program-level pre-requisites in the areas of calculus, linear algebra, and programming. Lecture 3 (Fall). |
| BANA-780 | Advanced Business Analytics This course provides foundational, advanced knowledge in the realm of business analytics. Advanced topics such as machine learning, analysis of structured data, text mining, and network analysis are covered. Industry standard tools such as R and Python are extensively used in completing student projects. (Prerequisite: BANA-680 or equivalent course.) Lecture 3 (Spring). |
| MGIS-650 | Introduction to Data Analytics and Business Intelligence This course serves as an introduction to data analysis including both descriptive and inferential statistical techniques. Contemporary data analytics and business intelligence tools will be explored through realistic problem assignments. Lecture 3 (Fall). |
| MGIS-725 | Data Management and Analytics This course discusses issues associated with data capture, organization, storage, extraction, and modeling for planned and ad hoc reporting. Enables student to model data by developing conceptual and semantic data models. Techniques taught for managing the design and development of large database systems including logical data models, concurrent processing, data distributions, database administration, data warehousing, data cleansing, and data mining. Lecture 3 (Spring). |
| FINC-761 | Stock Market Algorithmic Trading The course is a “hands-on” lab-based class designed to help students develop algorithmic trading strategies to invest in the stock market that can be implemented by retail and professional traders. What sets this course apart from many others is a strong emphasis on practical application with the purpose of building marketable skills for careers in finance. Concepts are not only taught, they are brought to life by learning how to design algorithmic trading models through the use of a computerized trading platform, that allows back-testing of data on thousands of different stocks. The software platform includes an automated wizard for building advanced technical trading models without programming knowledge; but also has an embedded programming language, similar to C-sharp, for those students that have those skills and elect to use them. (Knowledge of programming is not required; and there are no pre or co-requisites; but a lap-top is strongly recommended.). Lecture 3 (Spring). |
| FINC-773 | Debt Analysis Students learn about various debt markets, trading, and valuation. The focus of this course is on valuing debt instruments using widely used methods and in forming and analyzing debt portfolios. (Co-requisites: FINC-671 and FINC-721 or equivalent courses.) Lecture 3 (Spring). |
| FINC-780 | Financial Analytics This course provides a survey of financial analytics applications in contexts such as investment analysis, portfolio construction, risk management, and security valuation. Students are introduced to financial models used in these applications and their implementation using popular languages such as R, Matlab, and Python, and packages such as Quantlib. A variety of data sources are used: financial websites such as www.finance.yahoo.com, government sites such as www.sec.gov, finance research databases such as WRDS, and especially Bloomberg terminals. Students will complete projects using real-world data and make effective use of visualization methods in reporting results. There are no pre or co-requisites; however, instructor permission is required – student aptitude for quantitative work will be assessed; waived for students enrolled in quantitative programs such as the MS-Computational Finance which have pre-requisites in the areas of calculus, linear algebra, and programming. Lecture 3 (Fall). |
Admission Requirements
To be considered for admission to the MS program in finance, candidates must fulfill the following requirements:
- Complete an online graduate application. Refer to Graduate Admission Deadlines and Requirements for information on application deadlines, entry terms, and more.
- Submit copies of official transcript(s) (in English) of all previously completed undergraduate and graduate course work, including any transfer credit earned.
- Hold a baccalaureate degree (or US equivalent) from an accredited university or college.
- Recommended minimum cumulative GPA of 3.0 (or equivalent).
- Submit a current resume or curriculum vitae.
- Two letters of recommendation are required. Refer to Application Instructions and Requirements for additional information.
- Not all programs require the submission of scores from entrance exams (GMAT or GRE). Please refer to the Graduate Admission Deadlines and Requirements page for more information.
- Submit a personal statement of educational objectives. Refer to Application Instructions and Requirements for additional information.
- International applicants whose native language is not English must submit official test scores from the TOEFL, IELTS, or PTE. Students below the minimum requirement may be considered for conditional admission. Refer to Graduate Admission Deadlines and Requirements for additional information on English requirements. International applicants may be considered for an English test requirement waiver. Refer to Additional Requirements for International Applicants to review waiver eligibility.
For further information about tips on personal statements and additional guidance on how to submit a successful application, please visit Saunders College of Business Admissions Requirements.
Deferment
Accepted students may defer enrollment for up to one year. After one year, a new application must be submitted and will be re-evaluated based on the most current admission standards.
Learn about admissions, cost, and financial aid
Latest News
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September 3, 2021
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Technology Focused Graduate Programs Deliver Top Career Skills and STEM OPT Work Extensions
International graduate students may be eligible to work in the United States for up to three years after graduating from RIT.
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April 16, 2021
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Saunders Rears the Future of Finance
Traditional business practices work hand in hand with the latest industry innovations at Saunders College of Business. Here, master of science in finance students can explore traditional corporate finance and investment management as readily as the latest emerging fintech. The curriculum is embedded in understanding software and artificial intelligence and is taught by nationally-renowned faculty.
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April 1, 2020
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GMAT/GRE Waiver for Fall 2020
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