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Course Description

Number of Modules: 8  |  Credit Hours: 20

UEC Credits: 2 

Final exam passing grade: 60%

Price: 495 CAD

This introductory course on quantitative methods presents statistical concepts and techniques that are essential in the financial industry. The first part of the course focuses on tools for describing and estimating risk, including calculating the time value of money and descriptive statistics. Probability theory and distributions are then introduced as techniques to describe the behaviour of random variables, and this leads to estimation techniques, hypothesis testing, and technical analysis as methods used to help make investment decisions.

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Modules

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NOTE: The modular nature of this program allows different learners to tailor their courses to their needs. You may choose to take one course (for interest, or for a personal need), a series of courses (for career advancement, for example), or a series of modules (for professional certification preparedness in a particular field).

View course objectives

Credit Hours: 2 

In this module, we will cover the fundamental concepts used in time value of money applications such as simple interest and compound interest, cover the use of timelines in analyzing and understanding cash‐flows, and introduce the concepts of intra‐year compounding, annuities due, and perpetuities.

Credit Hours: 2 

In this module, you will learn how to apply discounted cash flow (DCF) to estimate project performance, including Net Present Value (NPV) and the Internal Rate of Return (IRR). You will also learn how DCF can help financial analysis value stocks, bonds or other investments that generate cash flows.

Credit Hours: 2 

In this module, you will learn the basic tools and terminology associated with descriptive statistics. This will include calculating and interpreting measures of central tendency, variability, and position. You will also be introduced to the basic notions for displaying data via distributions including kurtosis and skewness.

Credit Hours: 3 

This module focuses on the fundamental concepts underlying probability calculations, as well as their basic practical interpretations as a prerequisite for the later modules. The goal of this module is, therefore, to provide you with the basic tools you will need to identify unique scenarios and select or create the appropriate technique to carry out an effective probability calculation.

Credit Hours: 4 

This module expands on the fundamental concepts of probability theory by placing you in practical situations to make informed investment decisions. In particular, you will learn how probability distributions, such as the normal distribution, are used in financial decision making. You will also be introduced to specific calculations and associated baselines devised by experts in the field to apply to authentic scenarios.

Credit Hours: 2

Statistics is not an exact science. After all, the whole point of statistics is to make generalizations about the population under study using a portion of the population’s data. Therefore the notions of sampling error, bias, estimators, degrees of freedom, and the central limit theorem become essential to understand if you are to design, develop, and carry out any study that involves the collection of data. This module introduces you to these concepts, along with their practical use in confidence intervals and with the t‐distribution.

Credit Hours: 3 

The backbone of inferential statistics is the hypothesis test. In this module, you will learn how to properly initiate, carry out, and interpret the results of hypothesis tests. Throughout this module you will be introduced to various types of hypothesis tests such a sample being compared to its population, determining if a difference exists between two independent samples, the treatment effect on a given sample, and the difference in the variation of two samples.

Credit Hours: 2 

Some analysts believe that the truth lies not in calculations, but rather in patterns. In this module, you will learn how technical analysts study charts in order to identify patterns that signify an impending shift in stock prices, and an opportunity to take advantage of it! You will be introduced to common chart patterns, technical analysis indicators, and the importance of understanding the underlying notion of cycles in stock market prices.

Instructor

Dr. Patrick Devey is the Dean of the Centre for Continuing and Online Learning at Algonquin College (Ottawa, Ontario). He has over 15 years of professional experience in the leadership and management of quality learning and training experiences for students and clients in higher education, corporations, government agencies, health care, and professional associations. He has extensive knowledge in the areas of curriculum and pedagogical development, instructional design, integration of educational technologies in the learning environment, and the deployment of digital learning strategies.

Patrick has held a number of positions in the postsecondary sector as well as the private sector including Chief Learning Officer at KnowledgeOne Inc. (formerly eConcordia), lecturer in the Faculty of Education at McGill University, adjunct faculty in the Department of Education at Concordia University, and President and Founder of Devey eLearning Solutions. He earned his Ph.D. in Educational Technology from Concordia University where he studied the retention patterns of undergraduate students in online courses. His more recent research interests focus on the gamification of learning and the use of learning analytics in instructional design.

Instructor

Reena Atanasiadis obtained her MBA (with Honours) from the John Molson School of Business in 1995 and brings over 2 decades of experience in wealth management to her lectures.

She has held multi-provincial licenses as Investment Counsel/Portfolio Manager and handled on a discretionary basis global assets valued at several hundred million dollars.

Her thorough understanding of investment management and market intermediary activities led her to start up the Wealth Management division of the largest independent accounting firm in Canada. She designed and implemented asset allocation plans consistent with the investment objectives, risk profile and constraints of high net worth clients and corporations.

Reena has taught Finance at the John Molson School of Business and the Goodman Institute of Investment Management (an MBA program specializing in investment management) since 2004 with evaluations paying tribute to her applied knowledge and engaging style. In 2009, she was nominated to receive the Dean’s Award for Teaching Excellence and she received the award in 2012 for her teaching at the graduate level.

Her areas of interest include Behavioural Finance, Corporate Finance, Portfolio Management and Financial Institutions Management.

Course instructors and the program director are available to you at all times via email to answer your questions about course contents and how to organize your study time wisely to get the best out of the study materials.

Email: fac@knowledgeone.ca

“I loved having the possibility to study whenever and wherever I could; topics were very well explained by the instructor; plus I had the possibility to take the tests many times.”

John H.

“Very easy to use – Very good instructor – Notes easy to use and follow.

Margaret N.

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