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:
These two courses introduces you to quantitative methods and economic theories for financial analysis. The Quantitative methods section starts with the study of basic statistical methods for data analysis, sampling, estimation and hypothesis testing. It is completed with the study of Multiple Regression and Time Series Models including ARMA and ARCH models for forecasting. The Economics section is focused in the study of micro, macro and international economics models for financial decision making. All topics are covered with a practical orientation, through real-world case studies and using Excel and other statistical software.
This course equips you with the fundamentals in corporate finance, investment, and portfolio management. Students will be introduced to advanced financial modeling in Excel and Python to apply theories to solve real world problems.
These two courses focus on the concepts, methods and uses of financial accounting information primarily from a security valuation perspective. The course is designed to help you understand the basic structure of financial statements and exposes you to financial statement preparation and financial statement analysis. In this course, you will be exposed to both routine and non-routine accounting transactions and the rules, IFRS and US GAAP, that govern the preparation of financial statements.
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.”
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.
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.
This course has a three-fold purpose viz.:
The content in this course will be roughly equivalent to the CFA Levels I, II and III. 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.
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:
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:
The course allows students to manage real money for the Laurier Graduate Students Investment Fund (LGSIF).
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.
This course helps you prepare for the CFA level I exam in May. All topics covered in the level I exam will be reviewed.
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:
A secondary focus of the course is on the special financing concerns related to management and ownership succession within family firms.
This course discusses several issues in the field of International finance. Five key topics will be discussed:
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.
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:
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.
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:
On the basis of this analysis, students will learn how “funding deals” are screened and structured between early stage companies and angel investors
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.
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:
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.
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:
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