## Computational Finance (MGT412)

Syllabus [here]

Software needed: Anaconda Python Distribution (Mac, Windows, Linux): open source

Literature: Textbook on Amazon.fr

Literature: Textbook on Amazon.fr

## Schedule

**Introduction to Python. Operators. Control flows. Data types and structures.****Algorithms: Solving problems in Python.****Data analysis and management: The***pandas*library**High-frequency trading data. Plotting in***matplotlib*.**Optimization and maximum likelihood: GARCH model of volatility.****Stochastic processes: Simulating stock price paths.****Portfolio theory and plotting the efficient frontier.****Empirical asset pricing: Testing factor models.****Option pricing: Programming a binomial tree.****Option pricing: Monte Carlo simulations and American options.****Discussion of Large Data Assignment and Recap.****Discussion of Take-Home Final Test**

**Assessment:**- 20% from a five-problem algorithm solving assignment (general programming)
- 25% from a short code adaptation assignment (portfolio formation)
- 30% from a Large Data Assignment (more complex project, in teams of 2 or 3)
- 25% from the final Term Test