Who it is for
Serious career students and practitioners who already have foundations.
Advanced
Quantitative Finance
Advanced financial-market education designed for deeper understanding of markets and finance, with practical application.
Modules
- Market microstructure deepening
- Corporate finance for markets
- Python for research calculations
- Machine learning as a research tool, not a signal service
- Algorithmic implementation: a written rule before code
- Research process
- Risk and capital
Course structure
Python, machine learning and algorithmic trading sit in every program as methods. Depth follows the subject. They are not a return.
Python
Work that needs a calculation is done in Python. Load a table, state the assumption, and compute the result with NumPy and pandas. A notebook is a worksheet. It is not a signal.
Machine learning
A model is a function fit to past data. The class covers features, a split between the data you fit and the data you score, and why a fit on history is not something you can spend. It is a method, not a tip.
Algorithmic trading
A strategy is a rule a computer can follow: data, entry, size, exit, and a hard risk stop. A test includes costs. The execution lab is the Algo Trading program. Every other program uses the same standard: write the rule before any code.
You leave with
- A research notebook, not a screenshot folder
- Application of valuation and risk in one case each week
- Desk-style write-ups: thesis, risk, invalidation