RSM6301H – Topics in Financial Risk
This course will deal with the various ways that risk is relevant in the banking industry. It will cover both traditional and emerging risks.
For traditional risk, the course will be spent on how the capital markets as a whole interacts – from an investment banking point of view to trading and sales. It will look at the way in which market risk is quantified and managed from a practitioner point of view.
For emerging risk, the course will focus on climate risk. Climate change has a profound impact on planet earth and human society. This course introduces the concept of climate change and its impact across multiple areas, ranging from climate policy to technology innovation and finance. It will discuss the implications for the financial industry, with a focus on climate analytics for both transition and physical risks.
RSM6302H – Financial Markets, Risk, and Institutions
This course provides a qualitative description of commercial banks, investment banks, insurance companies, mutual funds, and central banking. Cases and current examples are used throughout the course to provide illustrations of the challenges facing financial institutions, requiring both qualitative and quantitative analysis. Students will participate in a banking simulation where students are asked to make quarterly decisions on loans, deposits, securities, etc. with the objective of managing bank risk while maintaining bank profitability.
RSM6303H – Regulation of Financial Institutions
Regulation drives much of risk management in financial institutions. This course explains why this is the case. It explains the history of the regulation of banks and insurance companies focusing particularly on regulatory changes that have been implemented since the 2008 credit crisis and those that will be implemented in the next few years. An important part of the course is a group project where students will evaluate a regulatory directive and present their findings to their peers.
RSM6304H – Operational Risk
It is now widely recognized that Operational Risk is as important, if not more important, than credit risk or market risk for a financial institution. This course will provide a detailed analysis of key areas of operational risk including legal risk (client, employee and shareholder claims), compliance risk (regulatory fines and sanctions), damage to assets, external events, cyber risk, internal and external fraud. Students will be exposed to the challenges of a category of risk that often results from complex interactions across people process and systems and across departments of a financial organization.
RSM6305H – Credit Risk
This course focuses on the pricing, measurement and management of interest rate and credit risks. It provides a broad overview of the issues in fixed income and credit risks, applies state-of-the-art credit risk pricing, measurement and management techniques.
The emphasis of this course will be on both qualitative and quantitative aspects of credit risk management as well as the implementation of models to capture credit risk in traded assets. Key focus will be given on derivative pricing with respect to interest rate and credit derivatives, credit risk scorecard modelling, structural models for credit risk and credit risk model validation.
RSM6306H – Probabilistic Modeling for Risk-Informed Decisions
We will use probabilistic modeling and stochastic simulation as tools for guiding risk-informed decisions in complex environments with material uncertainty about the future. The first part of the course will focus on quantifying various measures of equity return risk using historical data. We then focus on forecasting distributions of returns using both parametric and nonparametric approaches. Forecasting requires a ‘model’ so we assess parameter and model risk. This part of the course emphasizes developing models linked to financial data and assessing model performance.
The second part of the course uses stochastic simulation cases to practice deriving robust strategies for the decisions that risk managers must make in real time, including managing liquidity risk, market risk, crash risk, and real economy risks. We use the RIT market simulator platform (analogous to using a flight simulator); decision models for each RIT case are linked to data from the simulated market, that is, data generated by the class participants. The markets aggregate participants’ decisions and provide immediate feedback, allowing you to adapt strategies given the range of potential outcomes experienced in the multiple replications of the case.
RSM6307H – Macroeconomics for Financial Risk Management Professionals
This course is intended to prepare MFRM students to be able to understand and monitor risks forthcoming from global and national macroeconomies. We will review a number of different sources of macroeconomic risk, both short-term and longer-term, and consider the likely greatest areas of risk over the next 5-10 years and beyond. We will examine how ongoing and ‘real-world’ macroeconomic analysis and forecasting are carried out, and by whom, and consider the best sources for keeping aware of key macroeconomic issues in a busy professional life.
RSM6308H – Advanced Investments
This quantitative course presents advanced material on a broad range of topics relevant for investment professionals. Topics include the investor behaviour and preference, money management industry (mutual funds, pension funds, hedge funds, ETFs), properties of asset returns, asset pricing models, investment strategies designed to exploit market inefficiency, modern techniques for optimal portfolio selection, portfolio performance attribution and factor approach to investing. The course interprets asset management as a problem in understanding and exploiting factor risk premiums.
RSM6310H – Derivative Models for Risk Management
This course looks at the range of derivative products and the pricing models used to value and manage the risk of these products. The course starts with simple equity options and then moves on to exotic options and options on other types of assets. It also covers credit and interest rate derivatives.
RSM6311H – Risk Management Project
A distinctive feature of the MFRM program is the integrated Risk Management Project undertaken from January to March, where students tackle a real risk issue that is relevant and important to financial institutions. Project placements take students out of the classroom and into the industry, allowing students to work in-house with practicing risk management professionals. Presentations of project findings will be given to practitioners, fellow students and faculty in mid-March.
Samples of project topics include:
- Present the pros and cons of hedging FX exposure for a pension plan
- Estimate trading book loss due to global market shocks for CCAR
- Compare the reliability and relevance of different liquidity metrics
- Propose a technology solution for non-cleared OTC derivatives
- Assess the impact of IRRBB regulation on Canadian banks
RSM6313H – Innovations in Financial Technology
This course provides an overview of the basic tools in machine learning, with emphases on applications in finance. Machine learning plays an important role in FinTech. Individual investors and financial institutions who are able to leverage these new tools and technology will have a significant advantage. This course discusses these new opportunities and challenges. It seeks to equip students with these highly coveted skills in the market.
In addition to machine learning, blockchain is a significant component of FinTech. It is the technology behind cryptocurrencies and allows to create, record, trade, and transfer any digital assets. The last three lectures (delivered by Professor Andreas Park) cover the main ideas that are essential for the functioning of a blockchain, and it then takes a deep dive into some of the most notable innovations in the nascent field of decentralized finance (DeFi).
RSM6601H – Self Development lab
More than 80% of human work in organizations is carried out in groups and teams, and around 80% of an executive’s time is spent on communicating. Generative AI tools (and, in particular, Large Language Models and Large Symbol Models capable of interacting with people in textual or symbolic forms) will likely be a complement or substitute for significant components of the individual work people still do in organizations within five years. We are aiming to help each participant to become more skilled at those skills that are uniquely human in an executive setting – by becoming an astute and informed observer, evaluator and designer of her/his own social, relational and communicative interactions, and by becoming informed users of Large Language Models to generate useful prototypes, blueprints for communications in the specific genres of business, which include emails, memoranda, presentations and pitches.