Core Curriculum

The Lazaridis Master of Finance program is designed to give you an advantage in launching or accelerating your finance career.

Whether you want to prepare for the CFA exams, expand your understanding of the latest finance theories, or learn how to apply those theories to solve real-world financial problems, the Lazaridis MFin program has something for you.

The ten required courses listed below are taught by world-class instructors who will equip you with the foundational and advanced knowledge need to join the next generation of finance leaders in Canada.

You will have the option to take various elective courses and gain exposure to broader finance topics or dive deeper into a specific specialization. Check out the course descriptions of our elective courses.

In addition to the 10 required courses and optional elective courses, you will receive training in:

• Bloomberg terminals;
• Financial databases;
• Excel and VBA for financial modelling; and
• Python for financial modelling.

Required Courses

Financial Modeling 

This course will introduce students to Excel functions, VBA, and Python to build financial models for financial analysis, valuation of bond and equity, portfolio optimization, and portfolio performance analysis. Students will also be introduced to various databases for financial research and analysis.

Financial Statement Analysis

This course focuses on the concepts, methods and uses of financial accounting information primarily from a security valuation perspective. The course is designed to improve your familiarity with and comfort level with financial statements. While our main focus is on understanding and using financial information for valuation purposes, we will be considering how financial statements are prepared and the rules that govern such preparation. It is by understanding the basis for preparation that you can understand how to use and interpret the information and any limitations that may be inherent in the information provided.

Financial Econometrics

The course covers Quantitative Methods and Econometric theories and techniques required for financial analysis, including data management, sampling and estimation, hypothesis testing, Monte Carlo simulations, regression analysis and time series. The course will have a practical orientation and will require the use of computer software as Excel, Stata or Python. 

Derivatives and Financial Risk Management

This course provides an overview of the derivatives markets and how these contracts are employed by market participants to control their market risk exposures. Students learn different aspects of derivatives, as well as the know-how to implement hedging strategies using these financial instruments. The course also discusses different option trading strategies and covers different methods for pricing derivatives, including the Black-Scholes option pricing model and the quantification of option’s risk based on the “Greeks.”

Economics for Financial Analysis

The course covers the microeconomic and macroeconomic theory and methods required for financial analysis. Topics include consumer and producer theory, market structure, economic growth, monetary and fiscal policy, and international finance.

Advanced Corporate Finance

This course discusses three main decisions (investment, financing, and payout) made by managers at a level deeper than the introductory course. First, you will learn various corporate valuation models and use them to assess investments. Second, all firms must compete in a marketplace for scarce capital, and thus the theories of capital structure are introduced to help us understand corporate financing behavior. Third, you will learn payout policies and the tradeoff between dividends and share repurchases. Finally, this course discusses special topics such as agency costs and asymmetric information.

Investment Management

This course is designed to equip you with deep understandings of financial markets and various financial products. Topics covered include security analysis, portfolio theories, bond pricing, and derivatives.

Fixed Income Analysis

This course has a three-fold purpose viz.:

• To understand the risks and returns implicit in the fixed income market and its instruments.
• To develop an analytical framework to understand how various fixed income instruments are priced.
• To acquire problem solving skills with applications to fixed income markets.

The course will feature cases in Fixed Income spanning diverse topics such as corporate debt issuances, structured finance, MBS/CDO markets, green bonds, interest rate hedging, credit risk, credit default swaps, and arbitrage trading. Bloomberg training will be part of the course. The students will be required to use data and analytical tools from Bloomberg to conduct regression and statistical analysis using Python.

Advanced Investment Management

The course covers advanced topics in investment analysis, portfolio management and alternative assets. It extends (and differs from) the introductory investments course (BU673) by emphasizing:

1. Active as well as passive investment strategies;
2. Modern alternative models to classical asset pricing models;
3. Complexities encountered while managing portfolios on behalf of clients; and
4. Alternative investment vehicles augmented to primary securities (equity and debt).

Selected Optional Electives

Advanced Security Analysis (Waterloo and Toronto)

This covers all aspects of security analysis. Students take on the role of either equity analyst or portfolio manager. Their work will be reviewed and overseen by industry professionals and faculty members. Analysts will learn:

1. How to conduct in-depth research on an equity security;
2. How to develop, defend and present an investment thesis; and
3. How to prepare detailed financial forecasts and valuation models.

The course allows students to manage real money for the Laurier Graduate Students Investment Fund (LGSIF).

Behavioral Finance (Waterloo)

The course compares traditional finance to the expanding influence of behavioral finance. It examines both proof and anomalies of efficient markets. The evolution of various behavioral finance theories; types of investor biases; methods for identifying and correcting biases will be studied. Investor psychology relating to age; culture; and other factors will be discussed.

CFA Level I Review (Waterloo and Toronto)

This course helps you prepare for the CFA level I exam in May. All topics covered in the level I exam will be reviewed.

Entrepreneurial Finance (Waterloo)

This course focuses on the financial challenges confronting private businesses and in particular, early and mid-stage companies that are growing rapidly or aspire to rapid growth. We will concentrate on:

1. Becoming familiar with the many sources of funds for these firms with particular emphasis on angel investments, venture capital, franchising, bank loans, mezzanine financing and early public sources of equity;
2. Becoming familiar with laws and regulations relevant to such financing; and, most importantly,
3. Learning the key elements that enter into the structuring of the “deal” between private companies and their financiers.

A secondary focus of the course is on the special financing concerns related to management and ownership succession within family firms.

International Financial Management (Waterloo and Toronto)

This course discusses several issues in the field of International finance. Five key topics will be discussed:

• Economics of the forex markets;
• International capital (debt and equity) markets;
• International corporate finance;
• Financing International trade; and
• Forex derivatives.

The course will feature several cases in International capital markets and risk management. Bloomberg training will be part of the course. The students will be required to use data and analytical tools from Bloomberg to conduct regression and statistical analysis using Python.

Investment Strategies (Waterloo)

This course provides an overview of the main investment strategies and tools used by hedge funds and proprietary traders. There are three specific objectives in this course:

• To understand the risks and returns associated with different investment strategies.
• To develop an analytical framework to study investment strategies.
• To acquire data analyst skills required in the study and implementation of investment strategies.

The lectures present central concepts of investment strategies with special emphasis on the financial intuition underlying them. These concepts are illustrated in each class with exercises in which students conduct analyses and implement different methodologies.

Laurier Start-up Fund (Waterloo)

The Laurier Start-up Fund course is a practicum that gives senior students a hands-on education in early stage investing. The course allows students to work with early stage technology companies that are growing rapidly or aspiring to rapid growth. In particular, students will learn how to assess the company’s:

1. Product development and testing;
2. Commercialization potential including size of addressable market and competitive position;
3. Sales strategy and planned steps to take market share;
4. Founders and key employees and their ability to plan and execute;
5. Financial prospects; and
6. Financing choices.

On the basis of this analysis, students will learn how “funding deals” are screened and structured between early stage companies and angel investors

Machine Learning in Finance (Waterloo and Toronto)

This course introduces students to diverse methods of machine learning (ML) and their practical implementation in Finance. The aim of this course is to provide students with an understanding of how some common problems in the financial industry can be tackled with machine learning tools.

The course is composed of different modules that take the student through the end-to-end process associated with the deployment of ML solutions. By overviewing key concepts in applied mathematics underlying ML and implementing ML solutions for selected financial problems, students will acquire the skills required to conduct financial analyses using machine learning. Throughout the lectures, illustrative exercises are carried out using a programming language like Python.

Management of Financial Institutions (Waterloo and Toronto)

This course introduces students to the structure and the role of major bank and non-bank financial institutions in Canada and U.S., and the management of their operations and risk. The course is structured into three modules:

1. Introduction to financial institutions, their operations, performance, and regulations;
2. Measurement of various financial and non-financial risks faced by these institutions; and
3. Tools and instruments to manage and hedge of these risks.

Research Paper (Waterloo and Toronto)

Pair up with a faculty member and conduct research on a specific topic. You will learn how to use research techniques and tools to conduct empirical tests of a finance problem using finance databases. The Research Paper is not a thesis but requires more detailed and analytical work than an independent study.

Seminar in Corporate Finance (Waterloo)

This course provides detailed conceptual and practical knowledge of finance from a corporate perspective. The objective is to understand how corporate structure and corporate value are interrelated, and how they are dependent on two sets of factors:

1. Dynamic relationships between corporate management and stakeholders; and
2. Strategies and decisions undertaken by corporate managers (executives).