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Course descriptions

MQIM 6601 Professional Development I (non-credit)

Students will go through sessions on but not limited to: Career development (career leader, mock interviews, professional designations), Certifications (Bloomberg, excel, etc), Ethics, seminars by invited speakers providing background on what to expect as a quantitative analyst and what are the frontiers of the industry. Students will be required to review a quantitative reading and present on it in one of the semesters following Toastmasters approach.

MQIM 6602 Financial Data Analysis (3 ch)

Time series analysis, such as ARIMA, GARCH, regression, co-integration, MCMC resampling, copula, PCA, Factor models.

MQIM 6603 Financial Derivatives (3 ch)

Basic theory of derivatives with an emphasis on computational implementation via R language.

MQIM 6604 Quantitative Portfolio Investment Management (3 ch)

The course will cover the theory, analytic methods, and computational techniques currently employed in the business of investment management. Intended to be highly quantitative, the content will include topics drawn from the fields of utility theory, asset pricing, portfolio optimization, active portfolio management, and risk modeling. The course is intended to be applied in nature, and will have a significant computational component using the R language for statistical computing and various financial industry add-on packages. A particular focus will be on the implementation and interpretation of models that are used throughout the investment industry in the management of large pools of institutional capital.

MQIM 6611 Professional Development II (non-credit)

The second semester students will be focused on the application of quantitative techniques in investment management. Students will go to the major Canadian financial centres to meet practitioners. They will then prepare for quantitative university competitions (i.e., algo. trading).

MQIM 6612 Fixed Income Securities and Interest Rate Derivatives (3 ch)

Topics to be covered: Yields & Discount Factors; Spot & Forward Rates; Curve fitting (Bootstrapping & Nelson Siegel); Bond pricing, pricing of certain cash flows; Duration, Convexity; Key Rate Duration; Hedging & immunization, Interest rate forwards, futures & swaps, Models of the short rate (Vasicek, Hull White introductions), Interest rate tree methods (Ho Lee, BDT), Pricing interest rate derivatives (swaptions), Credit risk understanding credit spreads, Black-Scholes-Merton/KMV style default risk models.

MQIM 6613 Financial and Portfolio Risk Management (3 ch)

Loss distributions, risk measures, and risk aggregation and allocation principles, credit risk, VaR.

MBA 6636 Algorithmic Trading (3 ch)

The case-based course intends to be applied in nature and covers the implementation, backtesting, evaluation, and interpretation of automated trading models and strategies employed by both retail and institutional traders via the R language. According to Wikipedia: As of 2014, more than 75 percent of the stock shares traded on United States exchanges (including the New York Stock Exchange and NASDAQ) originate from automated trading system orders. This course is a practical introduction to algorithmic trading (AT) in the financial market. We will consider both algorithmic order execution and automated trading (such as high frequency trading (HFT)).

In particular, we will cover such topics as financial market microstructure, order types, order-driven vs quote-driven markets, low-frequency, regularly spaced data vs high-frequency (or tick-by-tick) irregularly spaced data, limit order books, order execution algorithms and strategies, and high frequency trading. We will introduce models and techniques that are prevalent in modern institutional and retail investment management. The focus will be on applications and implementations of models in the R language as opposed to theoretical considerations and derivations. Quantitative analysis and computer programming will be emphasized.


The Quantitative Investment Management program allows you the flexibility to complete two approved electives. These may include the Student Investment Fund courses.

Student Investment Fund (6 ch): Presents experiential learning of the actual financial investment process and portfolio management. Students, under the guidance of faculty advisers, manage a fund worth over $8.0 million (CD).

The course requires detailed analysis of macroeconomic, industry, and company fundamentals and entails preparation, on a regular basis, of up-to-date reports and presentations of portfolio analysis, selection, and management. Eligible candidates must have specified prerequisite courses, are required to complete an application form, undergo an interview, and write an exam based on CFA Level I materials.