Curriculum

Whether we like it or not, as individuals and managers we evolve within various markets, and are subject to their rules. But how do world events shape our markets, decisions, and outcome predictions? This is the question we will address in our first theme, "Understanding Markets".

These markets are themselves part of the economy as a whole – Canadian and global. This economy goes through booms and busts over time – the business cycle – and these fluctuations have an important impact on prices, national output, unemployment, and indeed affect our daily lives. In our second theme, "Understanding the Economy", we will learn the tools necessary to understand business cycles and governments’ policy responses; and to form educated opinions about what we read on the subject in the news.

But beyond understanding markets and the economy, today’s managers face a myriad of economic issues when formulating strategies. Should we enter this market? Should we exit that one? What price should we charge? How much should we produce? Should we try and “deter” entry by a rival, or should we “accommodate”? In some markets – monopolistic markets – our ability to affect outcomes is strong. How can we use this market power to our advantage? Other markets are characterized by the fact that our actions affect, and are affected by, rivals’ actions and require a whole new set of tools – game theoretic tools. How can we use game theory to analyze these situations? These and other fundamental questions are addressed in our third theme, "Decision-Making in Market Environments".

The primary pedagogical objectives of the course are for students a) to familiarize themselves with important economic concepts, and b) to learn to use them as “tools” for efficient decision-making in business and other environments.

This course is an intensive, practice-oriented program focused on industry best practices in financial modeling. Participants develop the skills required to build well-designed, transparent, and dynamic financial models used in valuation, transactions, and strategic decision-making. The course covers model design, logical structure, construction techniques, core financial concepts, and appropriate accounting treatment. Key topics include building integrated financial statements, developing depreciation and tax schedules, forecasting and modeling working capital and capital structure, and performing discounted cash flow analysis. The course provides an essential foundation for students interested in corporate finance and investment banking.

MFIN 821 introduces students to the basics of corporate finance including: an overview of the financial system; a discussion of the importance of business ethics and corporate governance; a review of financial statement analysis; financial forecasting; bond and equity valuation; an introduction to risk management and portfolio theory; the Capital Asset Pricing Model (CAPM); how to determine a company’s overall cost of capital; and, a detailed discussion of capital budgeting decisions. The emphasis will be on applying the concepts to real-world situations using actual market and company data to examine company decisions and assess their future growth prospects and risks.

This course will provide students a comprehensive overview of the fixed income markets, the main debt instruments traded, types of issuers and investors, and practices in the industry. Our main focus is on the cash debt markets, with coverage of derivatives to enhance analytic tools in the subject, and on risk-management. Our goal is to bridge the gap between theory and practice by illustrating how models and theories inform best trading and risk management practices in the fixed-income space.

Course Goals:

1. Linking bond theory with practice – use of market simulations and ‘mini’ cases in class to demonstrate and apply theory to real market instruments
2. Building knowledge of current fixed income markets and issues
3. Building bond portfolios – ability to incorporate yield curve, credit, capital structure and other variables into a comprehensive approach to fixed income portfolio management
4. Understanding of bond mathematics, bond pricing and relative value of product across the credit spectrum

This course explores the theoretical and empirical evidence relevant for investing and portfolio management. We will focus on traditional assets (equity and fixed income) as well as alternative assets (e.g. commodities, real estate, private equity, venture capital) and investment style (carry, momentum, value). We will learn how to combine these assets and strategies into portfolios to achieve specific investment objectives. While the course is designed to meet the needs of students who might want to pursue a career in the investment field, the course will prove useful for personal investing as well.

This course provides a comprehensive overview of derivatives and the markets in which they are traded. We implement the manufacturing process underpinning linear as well as non-linear instruments and, in this process, uncover the key relationships employed by market participants to value them. Furthermore, we explore how derivatives are used by financial institutions, as well as by non-financial firms, to manage unwanted risk exposures and/or to enhance investment yields. The course covers plain-vanilla derivatives (e.g. futures, forwards, FRAs, swaps, and options) as well as more recent innovations, such as exotic options and credit derivatives. We also explore best practices in enterprise-wide market and credit risk management, as well as recent developments in the regulatory environment surrounding the derivatives marketplace.

This course provides a high-level quantitative examination of the strategies employed by modern hedge funds. Moving beyond qualitative surveys, the course “opens the black box” of alpha generation by focusing on mathematical frameworks, econometric modeling, and the algorithmic implementation of specific trading styles. Students will analyze the mechanics of risk premia, market neutral strategies, and arbitrage opportunities through the lens of institutional-grade execution, emphasizing the transition from theoretical pricing to active portfolio management. This course provides students with the tools to engineer complex structured products and manage multi-manager portfolios in a high-conviction environment.

This course prepares students with the concepts and programming tools required to analyze financial data encountered in professional finance practice. The course introduces the Python programming language and its ecosystem, including package management, numerical computing, data manipulation, and data visualization. All programming tasks are supported by an AI agent. The course also introduces key concepts in statistics and machine learning for the analysis of financial data. Students learn to implement and program in Python machine learning and time-series models that are commonly used in finance. The course features a highly interactive, project-based learning format using real-world cases, where statistical concepts are applied to specific financial use cases, including credit scores and default rates, stock prices and returns, and interest rate data.