Electives: Master of Quantitative Finance

Master of Quantitative Finance students must complete 32 units of offered elective courses, including coursework in Professional Development.

Among Potential Electives:

MGTF 401 - Financial Accounting (4)

Overview of financial accounting reporting, with a primary focus on the analysis of economic events and their effect on the major financial statements (balance sheet, income statement, and statement of cash flows). Learn the nature and purpose of accounting methods. Letter grades only. Students may not receive credit for both MGTF 401 and MGT 404. Prerequisites: Restricted to master of quantitative finance program or by consent of instructor.

MGTF 405 - Business Forecasting (4)

Introduction to state-of-the-art forecasting methods in finance. Students will learn to estimate forecasting models based on past values of the predicted variable(s), surveys, market information, and other economic data. Participants will become critical consumers of forecasts reported in the media. Letter grades only. Prerequisites: Restricted to master of quantitative finance program, MBA program, or by consent of instructor.

MGTF 406 - Behavioral Finance (4)

Develop theories of behavior motivated by psychology to describe various features of financial markets. Examine how the insights from behavioral finance complement the traditional paradigm and shed light on investors’ trading patterns, the behavior of asset prices, and corporate finance. Letter grades only. Prerequisites: MGTF 402; restricted to master of quantitative finance program, MBA program, or by consent of instructor.

MGTF 407 - Valuation in Corporate Finance (4)

Covering the fundamentals of corporate finance and their application to valuation (including the WACC approach, APV approach, multiples, and real option valuation). We focus on important areas of corporate finance, including capital structure, real options, and financial distress and bankruptcy. Letter grades only. Prerequisites: MGTF 402; restricted to master of quantitative finance program, MBA program, or by consent of instructor.

MGTF 408 - Real Estate Finance (4)

Examination of real estate capital markets, both debt and equity. Covered topics include real estate valuation, real options applied to real estate, real estate equity markets, and the place of real estate within a diversified investor’s portfolio. Letter grades only. Prerequisites: MGTF 402; restricted to master of quantitative finance program, MBA program, or by consent of instructor.

MGTF 410 - New Venture Finance (4)

Focuses on the financing of new ventures and technological innovation. Includes perspectives of both the entrepreneur and the investor, investigating the venture capital process, and methods of financial valuation useful in the venture capital industry and for other technology investments. Letter grades only. Students may not receive credit for both MGTF 410 and MGT 280. They are course equivalents. Prerequisites: Restricted to master of quantitative finance program, MBA program, or by consent of instructor.

MGTF 409 - M&A and Corporate Restructurings

In this course we study corporate transformations: acquisitions, divestitures, and restructurings. Firms make these strategic decisions in the face of major challenges. We are going to delve into the motivations why companies acquire other firms, divest business units, and reorganize their capital structures. We will also explore how managers can sometimes exploit corporate change to obtain private benefits at the expense of shareholders and stakeholders. On several subjects, we will develop spreadsheet models to analyze how decisions are expected to affect profitability, cash flows and shareholder value. By the end of the course you will have gained powerful insights into how firms adapt to technological, economic, and regulatory shocks, as well as the roles economic institutions play in promoting competition and mandating disclosures.

MGTF 411 - Stochastic Calculus and Continuous Time Finance (4)

Many closed-form analytic results in finance are obtained in the continuous-time setting. This course covers portfolio choice, derivative pricing, and term structure modeling in continuous time setting. The objective is to understand important topics and master techniques of continuous-time models. Letter grades only. Students may not receive credit for both MGTF411 and MGT286. These are course duplicates. Prerequisites: Restricted to master of quantitative finance program or by consent of instructor.

MGTF 412 - Financial Statement Analysis (4)

Develop a deeper familiarity with financial accounting and assumptions underlying measurements reported in financial statements. Understanding of economic and regulatory forces underlying corporate disclosure of financial statements. Knowledge of data sources and analytical tools to extract and evaluate this data. Letter grades only. Prerequisites: Restricted to master of quantitative finance program, MBA program, or by consent of instructor.

MGTF 413 - Computational Finance Methods (4)

This course introduces students to a variety of mathematical methods as applied in finance, including Monte Carlo simulation, optimization methods, and numerical solutions to PDEs. Letter grades only. Prerequisites: Restricted to master of quantitative finance program or by consent of instructor.

MGTF 418 - Preparing for the CFA Exam

The Chartered Financial Analyst (CFA) designation is the industry-accepted gold standard for financial analysts. To earn the CFA charter you must pass three very challenging exams. Exam material draws from surveys of practicing analysts and covers 10 major topics. We will look at each of the 10 major topic areas (one per class) and explore the level of understanding that is required to pass the first level exam. We will do applied valuation work as tested on the actual CFA exams as well as highlight study habits of successful past candidates. We will pay special attention to sub-topics that aren’t part of the core RADY MQF program but that are covered on the CFA exams.

MGTF 419- CFA Level II Exam Preparation

This course prepares the student for taking the CFA Level II exam. Course material will include review material on all areas of the test and will also include practice tests.

MGTF 420 - Financial Markets and Institutions

This course examines the economics of financial markets and financial institutions. The course will focus primarily on US financial markets with a lesser focus on international financial markets. Topics include the functions and structure of financial markets; interest rate fundamentals including the term structure of interest rates; central banking including the conduct and impact of monetary policy; capital markets, equity and debt markets, foreign exchange markets; major financial institutions and their roles in these markets. The course will also monitor current events in the area of finance, financial markets and business during the semester through links to various websites and to the financial press.

MGTF 421 - Corporate Finance

This course covers the foundations of finance with an emphasis on corporate finance applications. We will discuss many of the major financial decisions made by managers both within the firm and in their interactions with investors. Essential in most of these decisions is the process of valuation, which will be an important emphasis of the course. Topics include criteria for making investment decisions, valuation of financial assets and liabilities, relationships between risk and return, capital structure choice, and the effective use and valuation of derivative securities.

MGTF 422- Derivatives & Structured Finance

Derivatives are securities whose prices depend on other fundamental variables or securities. Derivative securities have seen a massive amount of growth in the last many years; growth in volume, applicability, usage and importance. In terms of volume, the outstanding notional of derivatives in the over-the-counter market is around $700 trillion, with a market value of $20 trillion. In terms of the latter three aspects, it is estimated that over 90 percent of the world’s 500 largest companies use derivatives to manage risk. In this course, we will be gaining a deep understanding of these derivative securities, including futures, forwards, options, swaps and credit derivatives.

MGTF 423 - Data Science for Finance I

Data science is an emerging field that brings together vast amounts of data with techniques in a range of areas including data management, statistical analysis and machine learning. This course will introduce you to a collection of powerful, open-source, tools needed to manage and analyze financial data, and to conduct data science in finance applications. This class will give an overview of the basic process of data science and dive into the data management and natural language processing NLP techniques useful for financial data analysis. The ability of learning patterns from data and making accurate predictions on new instances makes NLP a powerful tool for Business Intelligence and Financial Forecasting since it helps us transform the raw data into better decisions. This course will not dive into the technical details of algorithms but rather focus on how to use these algorithms in Financial applications. Popular Python based tools will be used in analytical components of the class. Data management lectures will utilize PostgreSQL in practical exercises.

MGTF 424 - Data Science for Finance II– Machine Learning

This course covers machine learning techniques useful for financial data analysis. The class will introduce a collection of powerful open-source tools, including but not limited to, Python and PostgreSQL. Not only will the students learn the theory of data science but also apply this theory to real world applications in class and in homework and a project.

MGTF 430 - Asset Management

Under one view, Asset Management is a relatively trivial exercise — an investor, based on her risk preferences, should passively invest in a linear combination of an efficient frontier portfolio and cash, in essence earning a fair return for her beta. This implication is belied by the large amount of resources expended in Asset Management in the real world. In this course, we will investigate the reasons behind such resource expenditure. And we shall examine ways in which an investor can aim to outperform the predictions of MPT, either by reducing risk without impacting return negatively, or increasing returns without increasing risk.

MFTF 495 - Data Science for Finance using Python (4)

This course will introduce you to a collection of powerful, open-source tools needed to manage and analyze finance data, and to conduct data science in finance applications. This class will overview the basic process of data science and dive in to the data management and machine learning techniques useful for financial data analysis.

The ability of learning patterns from data and making accurate predictions on new instances makes Machine Learning a powerful tool for Business Intelligence and Financial Forecasting since it helps us transform the raw data to inform better decision-making. Popular Python based tools will be used in analytical components of the class. Prerequisites: Restricted to master of quantitative finance program or by consent of instructor.

Program FAQs

How is the Master of Quantitative Finance program different from an MBA with an emphasis in Finance?

The Master of Quantitative Finance program provides deeper and more technically focused coursework in a program that, overall, has a more quantitative concentration than the MBA. As a focused, one-year program, the Master of Finance may be an excellent choice if you have clear career goals in data-driven areas of finance.

The Master of Quantitative Finance does not provide the broader perspective on business, management and leadership that the MBA offers: No courses in management, leadership, marketing or operations are included in the Master of Quantitative Finance.