Finance is learned at the keyboard, not just the blackboard. My courses pair the theory with data, code and tools students can actually run.
Every concept lands on a real problem. If it can't be applied, it isn't finished being taught.
Students explore models by changing them — the tools on this site were built for exactly that.
Intuition is tested against data, always. The number has the last word, not the slide.
Nine courses spanning computation, machine learning, risk and the plumbing of modern finance.
The computational backbone — turning equations into reliable numbers.
Where statistical learning meets markets, applied with discipline.
Measuring, pricing and controlling the risk a book carries.
Balancing what an institution owns against what it owes, over time.
The rules of the game — Basel, Solvency, and what they demand.
Pricing and hedging default risk, from CDS to structured credit.
Distributed ledgers, and what they actually change in finance.
Teaching machines to read the text that markets run on.
How to check that a pricing model is telling the truth.