Teaching
Quantitative Finance
A course in portfolio construction (graduate)
The graduate edition of the portfolio-construction course: the same arc from return and risk measurement to full strategy backtesting, taken at master's depth. The graduate textbook carries the MSc main text plus PhD appendices, adding rigor on estimation, factor structure, and pricing tests.
Topics
- Mean-variance optimization, rebalancing, and estimation error
- Covariance and factor models
- Momentum, reversals, and the investment horizon
- CAPM, multifactor models, APT, and pricing tests
- Characteristics versus covariances; finding alpha
- The Black-Litterman model
- Event studies and strategy examples (betting against beta, quality minus junk, macro momentum)
- Backtesting and evaluation
Audience
Master's students comfortable with statistics and linear algebra; PhD appendices for research-bound students.
Materials
A complete graduate textbook (~375 pp., 23 chapters: MSc main text plus PhD appendices), lecture decks, team projects plus the Fund Project.
The graduate textbook extends the undergraduate course chapter by chapter, with starred advanced sections and PhD appendices for research-bound students. Worked Python examples run throughout, and graded work is built around team projects and the semester-long Fund Project with its own rules and deadline calendar.