Course Information

A two-week review session is offered to help fill in some of the 'gaps' in educational background across students (i.e. provide BSc students with an introduction to intermediate economics concepts, provide Econ/BA students with a refresher in quantitative methods). Content includes:

• Mathematics
• Econometrics
• Intermediate Macroeconomics
• Intermediate Microeconomics
• Financial Reporting
• Introduction to Python
• Professional Development

This course covers the most important topics and results in modern microeconomics, with emphasis on those that apply most directly to financial economics. These include decision making under uncertainty, including portfolio choice; asset pricing; market failure; market incompleteness; theory of incentives, including moral hazard; and imperfect information, including adverse selection.

This course is an introduction to financial economics. Its objective is to introduce students to the principles of financial asset pricing and investment decisions under uncertainty. Topics include financial institutions, time value of money, risk-return trade-offs, market efficency, portfolio choice, the Capital Asset Pricing Model (CAPM), Arbitrage Pricing Theory (APT), fixed income securities and, if time permits, selected topics on derivative securities.

This course begins with an examination of individual choices under uncertainty, including expected utility theory, risk aversion, stochastic dominance, and two-period consumption-portfolio problems. These frameworks are used as a foundation to explore more advanced models in this course and in subsequent courses in the Master of Financial Economics (MFE) program. 

This course deals with the necessary and appropriate econometric techniques used in the analysis of financial data. The first focus of the course is on time series methods, like autoregressive (AR), moving average (MA), integrated processes (unit root), and in combination (ARMA and ARIMA). The second focus is on models that estimate stock returns volatility, including ARCH, GARCH, SV and RV models. Other topics of the course include: forecasting, forecast evaluation, factor models, and the capital asset pricing model. Econometric software packages (i.e. R, Matlab, or STATA) are a large component of empirical applications that use current Bloomberg data.

This course is on modern financial mathematics -- the study of making financial decisions under uncertainty. Such decisions are shaped by three main drivers – the balance between future and present, quantified by the interest rate; the role of uncertainty, often quantified in terms of the volatility, and investors attitudes toward risk. Several products are available to trade and manage risk: stocks and bonds at a basic level; forwards, futures, and options at a more advanced level. This course will develop theories for pricing and hedging individual derivative securities using both the simple binomial tree model for options prices and at least the intution behind some continuous time models. Material covered includes the Black- Scholes-Merton theory of options pricing, how to price and hedge a variety of stock options and a briefly discussion of the challenges involved in extending this pricing technology to options on other underlying assets. Mathematics used includes multivariate calculus, basic stochastic calculus and linear difference and differential equations. However, the mathematics will always be taught as a means to a goal and not as the goal itself – explanations will be in simple, financially motivated terms as much as possible.

Examples of electives include Financial Risk Management, Applied Financial Econometrics, and Investment Portfolio Management. See Recommended Electives below.

Professional Development Courses

This series is designed to teach MFE students internship search skills and techniques that they will use to secure an internship. These same skills and techniques will transfer to full-time job search approaches as students graduate and alumni.

This course is a theoretical, empirical, and policy-oriented treatment of the determination of output, employment, interest rates, and the rate of inflation. The course builds on the stochastic neoclassical growth model, and introduces dynamic optimization tools required to characterize solutions. The growth model is used as an organizing framework to examine the empirical properties of long term economic growth and business cycles. Another core topic is an introduction to monetary economics, with a discussion of money-in-the utility function and cash-in-advance models. This is used to provide an introduction to the role of nominal rigidities in business cycles. The course also provides an introduction to asset pricing and the equity premium puzzle.

The goal of the course is to provide the most important and updated knowledge in all the areas in corporate finance. Topics to be covered include capital structure decisions, agency conflicts in the firm, dividend policy, security design, optimal financial contracting, the theory of the firm, the market for corporate control, and banking and financial intermediation, among others. The course also trains you to be a qualified financial analyst, as well as an efficient financial database user and SAS programmer. These skills are extremely important in finance industry. We then apply these skills in generating useful information from financial data and solving specific problems in corporate finance.

Examples of electives include Financial Risk Management, Applied Financial Econometrics, and Investment Portfolio Management. See Recommended Electives below.

Professional Development Courses

This series is designed to teach MFE students internship search skills and techniques that they will use to secure an internship. These same skills and techniques will transfer to full-time job search approaches as students graduate and alumni.

During the summer term (May-August), students are required to complete a summer internship. Students receive support from the MFE Program Director, the MFE Program Coordinator, and the MFE Career Counselor as they conduct their job search.  Credit for the summer internship is earned for 10-16 weeks of paid employment with a relevant employer.

Financial industry regulation is extensive, affects business decision-making and can even spur financial product and process innovation. Finance professionals need an intelligent understanding of financial regulation to avoid pitfalls and help identify issues requiring expert advice from counsel. This course will canvass the theoretical foundations of securities regulation and many fundamental doctrinal securities law issues, focusing primarily on Ontario. Topics may include: foundational securities law concepts; Canadian securities regulators and regulatory instruments; registration and prospectus requirements; the exempt market; insider trading; continuous disclosure; take-over bids; and enforcement. Comparisons may be drawn to securities regulation in other jurisdictions, such as federal U.S. securities regulation. The evolution of recent proposals to create a national regulator (or Common Cooperative Capital Markets Regulator) in Canada will also be surveyed.

This course presents a study of some of the most significant empirical (and theoretical) work in the field of asset pricing. We examine topics such as: the Capital Asset Pricing Model (CAPM), multi-factor asset pricing models, conditional and unconditional asset pricing models, international asset pricing models, and asset pricing in a behavioural finance context.  We discuss how research can be used in practice, how to develop interesting research questions, and how to develop practical applications for existing research.

Examples of electives include Financial Risk Management, Applied Financial Econometrics, and Investment Portfolio Management. Note, FM9578 Financial Options is required in Term IV if not completed in Term I. See Recommended Electives below.

This is an intermediate course on derivatives securities with a focus on practical applications. It is intended for graduate students who want to pursue careers in research, industry or government that focus on securities trading, risk management or asset pricing. The course will begin with a review of asset pricing theory, arbitrage models, and pricing of plain vanilla derivatives such as futures, forwards, options and swaps, then it will focus on practical applications in trading, corporate finance, financial engineering and risk management. While reviewing each topic the course will emphasize the effects of externalities, frictions, and modeling assumptions on valuations and trading strategies. The course will also highlight the role that financial institutions, market infrastructures and regulation play in enhancing welfare.

This course covers the theoretical and empirical methods necessary to undertake empirical analysis of financial data. Commonly used econometric techniques for analyzing cross sectional and time series data are examined. Topics include methods for testing asset pricing theories, parametric and non-parametric volatility models, and models that use high-frequency data. Empirical applications of the techniques will be done using Canadian and/or international financial markets data with econometric packages such as Matlab, R, Stata or SAS.

Investors, regulators and more generally stakeholders depend on the accuracy of company financial statements.  Using a series of case studies, this course explores how GAAP corporate accounts can systematically result in inaccurate decision making.  By challenging accounting labels and financial conventions and by understanding corporate performance as a series of cash flows, class participants will be better equipped to monitor, control and reward how scarce capital resources are allocated.  

This course examines the historical evolution of the financial and monetary system as well as several important financial crises episodes (e.g., banking panics, sovereign defaults). Economic theory is employed to analyze financial crises and the economic forces driving financial innovation. Insights from historical experiences and economic theory are used to evaluate the trade-offs associated with policies to mitigate the economic impact of crises and manage systemic risk.

This course examines Risk Management concepts and quantitative applications in the financial industry. Commonly used quantitative measures of key risks (e.g., credit, liquidity, operational risk) are examined, as well as their practical advantages and disadvantages as risk management tools.  Key elements of the regulatory (e.g., Basel capital and liquidity regulation, stress testing) and organizational environment which constrain the practice of risk management are discussed.

Options Pricing in continuous time. A gentle introduction to stochastic processes including what is meant by information filtrations, the Ito integral, Ito’s lemma, and the Ito isometry. Continuous time delta hedging and the Black Scholes PDE. Equivalent Martingale Measures. Options Pricing and Hedging. Hedging one option with another option and the market price of risk. An introduction to interest rate models – affine term structure models of the yield curve. (Prereq – SS3521b or AM9578b or equivalent/permission of the instructor)

This case based financial modeling course will develop the conceptual and practical framework for building a securities portfolio of stocks, bonds and derivatives. The process will start with the client (individual or institution), then develop an investment policy identifying the specific risk and return characteristics of the client. Building on the clients needs, we will develop risk return forecasts for various classes of securities.

Students are welcome to enroll in courses offered by other faculties including the Department of Statistical and Actuarial Sciences and Ivey Business School. Enrollment is on special permission basis subject to students having the required background and course availability. 

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