These are notes written in Julia for the computational economics reading group. The notes can be found in the notebooks folder.

There are probably many errors, all of which are my own. It is safe to say that everything is a work in progress 🚧

1. Floating point arithmetic -- Complete
2. Autodifferentiation and linear algebra -- Complete
3. Solutions to systems of linear equations -- Incomplete
4. Optimisation (unconstrained and constrained) -- Complete
5. Function approximation -- Incomplete
6. Dynamic programming (deterministic) -- Incomplete
7. Endogenous grid method (deterministic) -- Empty
8. Stochastic processes -- Incomplete
9. Simulation and random numbers Incomplete
10. Numerical integration -- Empty
11. Dynamic programming (stochastic) -- Empty
12. Endogenous grid method (stochastic) -- Empty
13. Perturbation methods -- Empty
14. Reiter's method -- Empty
15. Linear time iteration -- Empty
16. BKM algorithm -- Empty
17. Sequence space Jacobian -- Empty
18. Neural networks -- Empty

We will probably not cover all topics during the year, but this is a first run. Future iterations will have more complete notes and include more topics.

Several resources were used in constructing these notes. I relied a lot on code from other people in setting up these notes. Below are links to some of the repositories, books and websites that I found helpful in trying to make sense of it all. These are not presented in any particular order.

1. Fedor Ishkakov -- Foundations of Computational Economics
2. Florian Oswald -- Computational Economics for PhDs
3. Ivan Rudik -- Dynamic Optimization
4. Toby Driscoll -- Fundamentals of Numerical Computaion
5. Chris Edmond -- Macroeconomics PhD course
6. Alisdair McKay -- Numerical Analysis
7. Stefano Pica -- Macroeconomics PhD Course
8. QuantEcon -- Quantitative Economics