COMM 476 - Advanced Topics in Investment Management
The area of investments covers a broad range of topics related to how individuals and institutions allocate capital across asset classes and individual risky securities. The topics in the course will vary according to the interests of the students and the instructor and with new developments in the field of investment management.
Learning objectives
The main goal of the course is to study current topics and research findings, at the frontiers of investment management, that have not been fully covered elsewhere in the finance curriculum. Primary resources and methods will be the study of working papers, industry papers and journal articles that develop new ideas, consideration of real-world examples and practitioner experience, and student-led implementation of potential investment and trading strategies. During this course we will also introduce the programming language Python (which is a powerful and increasingly important, as well as free and open-source, tool used in the finance industry), and will develop skills in acquiring current market data and carrying out empirical analyses using Python and Excel. Example course outcomes are that students can:
- Analyse and understand properties of stock returns including:
- Individual stock returns versus portfolios
- Factor decomposition of stocks and portfolios (stock characteristics and risk exposures)
- Attribution properties of stock and portfolio returns
- Understand how to construct portfolios
- Factor portfolio construction
- Optimization, regressions, and other construction methods
- Compare and contrast various industry standard methods
- Opportunity to build and recommend portfolios through implementation of trading strategies (existing or novel student-led design)
- Understand and build Asset Allocation methods
- Implementation of traditional mean-variance analysis using broad asset classes
- Limitations and extensions including VaR (Value at Risk)
- Risk budgeting
- Introduce and review cryptocurrencies in portfolios and asset allocation
- Investigate new frontiers in investment management such as:
- Applications of Artificial Intelligence (AI) and machine learning (ML) methods for factor construction
- Applications of Natural Language Processing (NLP) methods for analysing various information sources like newspapers, magazines, corporate filings and social media like Twitter, Reddit, etc.
- Transaction cost modeling, including the importance of trading costs in the context of investment strategy turnover, investment size and market volatility
- Monte Carlo simulations and their practical uses in investment modelling
- ESG (Environment, Social, Governance), currently an important topic for all investors, including investigating ESG as factors (stock characteristics and risk exposures), impacts on portfolio construction, and carbon pricing methods to improve factors in modern investment management
Note: Formerly numbered COMM 486H. If you've completed the course as COMM 486H, you are not permitted to take it again as COMM 476 (you cannot receive credit for the same course twice).