12 Months, 31 Credits
The Saunders Master of Science in Finance program at RIT is designed to prepare students for managerial careers in corporate finance, investment analysis and portfolio management, financial consulting and financial institutions.
The analytical, deductive nature of the program creates financial professionals who can adapt to dynamic changes in the deregulated financial industry and its dramatic growth in investment options. Its courses prepare students to sit for the Chartered Financial Analyst (CFA) exam.
Students may complete the program on a full-time or part-time basis, with the full-time program beginning exclusively in the fall semester.
The program of study consists of 10 courses and a comprehensive exam based on the finance courses completed by the student. The exam will be administered at the end of the student’s last term. Students must pass the exam to earn their degree.
The latest curricula for incoming students is provided below. Current students and alumni – please visit the Office of the Registrar for a History of Course Catalogs to view and download official degree requirements pertaining to the academic year you began your degree.
Finance, MS degree, typical course sequence
|Course||Sem. Cr. Hrs.|
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.
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.
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.
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.
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)
|Total Semester Credit Hours||
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.
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.
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.
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)
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.
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.).
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.
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.
General electives (in addition to Finance electives listed above)
Corporate Financial Reporting I
A comprehensive exposure at an intermediate level to financial accounting theory and practice under U.S. Generally Accepted Accounting Principles. Emphasis is placed on applying underlying accounting theory to complex accounting and reporting problems. The effects of alternative accounting methods are considered. International Financial Reporting Standards are introduced as they relate to course subject matter.
Corporate Financial Reporting II
Continuation of Corporate Continuation of Corporate Financial Reporting I with emphasis on equity and special measurement and reporting problems. Topics include liabilities and contingencies, stockholders’ equity, earnings per share, pensions, leases, revenue recognition, income tax accounting, and the statement of cash flows. International Financial Reporting Standards are introduced as they relate to course subject matter.
The development and use of cost data for external reporting and internal cost management (planning and control). Topics include job costing, process costing, joint product costing, cost reassignments, standard costs, activity-based costing, decentralization and transfer pricing, and cost variances. Consideration is given to manufacturing, service and retail organizations.
A basic introductory course in federal income taxation. Emphasis is on taxation of individuals and sole proprietorships. Topics include income measurement and deductibility of personal and business expenses.
Statistical Analysis for Decision Making
This is a course in applied statistics emphasizing an understanding of variation and inference (estimation and testing). Topics to be covered include: review of descriptive statistics, normal distribution, sampling distributions, estimation, test of hypothesis for single and two populations, analysis of variance (ANOVA), linear regression, multiple regression and model building. Students will apply these concepts using mini-cases and problem sets that involve both structured and unstructured data sets. The application of appropriate tools will be required.
Economics and Decision Modeling
The course focuses on the fundamental economic theories most useful for the management of a firm in a global environment. Microeconomic theories and current events are used to explain the performance of the market system and help managers formulate effective pricing and business decisions. Macroeconomic theories and current events are used to explain the direction of the domestic and global economy to help managers understand the implications, including foreign direct investment, for their companies. Students will learn to explain and predict changes in economic growth, inflation, interest rates, international trade and foreign exchange rates.
Financing New Ventures
A focus on financial issues affecting an entrepreneur. The course emphasizes, identifies, and follows the wealth creation cycle. The wealth creation cycle begins with an idea for a good, product or service, progresses to an initial company startup, passes through successive stages of growth, considers alternative approaches to resource financing, and ends with harvesting the wealth created through an initial public offering, merger or sale. Identification and valuation of business opportunities, how and from whom entrepreneurs raise funds, how financial contracts are structured to both manage risk and align incentives, and alternative approaches by which entrepreneurs identify exit strategies are reviewed.
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.
Information Systems Concepts
This course is an introduction to the conceptual and theoretical foundations of management information systems and their role in modern organizations. The course will provide students with the concepts, tools and techniques needed to understand and to interpret information management issues, such as how to best incorporate information technology into an organization, from a managerial perspective.
This course provides an overview of marketing analytics in the context of marketing research, product portfolios, social media monitoring, sentiment analysis, customer retention, clustering techniques, and customer lifetime value calculation. Students will be introduced to, mathematical and statistical models used in these applications and their implementation using statistical tools and programming languages such as SAS, SPSS, Python and R. Multiple data sources will be used ranging from structured data from company databases, scanner data, social media data, text data in the form of customer reviews, and research databases. Students will complete guided projects using real time data and make effective use of visualization to add impact to their reports. There are no listed 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.