MFIN8865 · Finance
Carroll School of Management
This course explores how the market is influenced by the behavior of investors, attributable to psychology or institutional constraints. We will survey recent research on possible mispricing in these markets, investor behavior, the predictability of security returns, and the practical limits to arbitrage. Possible topics include earnings and price momentum, market anomalies, tactical asset allocation, under-reaction to news, security complexity and obfuscation, and socially responsible investing. Practical implications for portfolio management are developed and emphasis will be placed on data-driven analysis of financial markets. The course has 3 major goals. The first will be to take the view of a professional money manager to utilize knowledge of investor behavior to understand market movements and (hopefully) profit from opportunities that are available. The second will be to understand how data is used to uncover such opportunities. The third is to understand how individuals make decisions in order to make better personal investment decisions and avoid commonly exhibited biases when making financial decisions. Achieving these goals will require learning some theories, facts and statistical tools. The theories will allow for a common language in the discussion of returns and will include risk-based asset pricing, present value relations and cognitive psychology. The facts relate to risk and return, value vs. growth, momentum, market frictions and trading costs. Support for both of these will come from the data for which we will need the tools of portfolio analysis, multifactor models and forecasting regressions. STEM-designated
Course experience
Averages use the original five-point historical evaluation scale.
Organization
4.2 / 5
How well the course was organized
Challenge
4.4 / 5
How intellectually challenging students found it
Attendance
4.2 / 5
How necessary attendance was
Assignments
4.2 / 5
How helpful assignments were
Weekly effort
~3
hours per week
Estimated from the original workload response buckets. Individual sections may differ.
Instructor options
Ratings below reflect the evaluations connected to this course.
Across time
Available section-level results across semesters.
Spring 2025
1 sectionSpring 2024
1 sectionSpring 2023
1 section