Lecture materials for Quant Juniors (Spring 2024)
This semester we will use Codespaces to work with code. If you have experience, you can do everything locally. Codespaces simplifies our setup process and allows us to make the most of our meeting time.
- If you are not familiar with Git, please refer to this repository and/or other online resources to set up Git.
- Fork this repository (qj-s24), so you can have a copy on your own GitHub (remote).
- In your forked repository, you can open up codespaces under
<> Code>Codespaces. - Edit and commit and push as needed. It works just like VSCode.
- Intro to numpy, pandas, matplotlib and other Python data science libraries
- Random walks/geometric brownian motions
- Basic probability and computational statistics
- Monte Carlo methods for simulations
- Algorithmic trading: backtesting, ML strategies
- Statistical arbitrage
- Various interested topics in ML, stats, math and finance