An open API service indexing awesome lists of open source software.

https://github.com/Auquan/Tutorials

Ipython notebooks for math and finance tutorials
https://github.com/Auquan/Tutorials

math trading tutorials

Last synced: 7 months ago
JSON representation

Ipython notebooks for math and finance tutorials

Awesome Lists containing this project

README

          

# Tutorials
IPython notebooks for trading and math tutorials.
You can view these here in github, or you can download and run locally on your computer.
You will need to have the auquanToolbox installed to be able to run them.

For instructions on how to install the toolbox, visit [here](https://github.com/Auquan/auquan-toolbox-python)

## Contents:
### Trading Strategies:
1. [Mean Reversion Basics](https://github.com/Auquan/Tutorials/blob/master/Mean%20reversion.ipynb)
2. [Momentum Strategy Basics](https://github.com/Auquan/Tutorials/blob/master/Momentum%20Strategies.ipynb)
3. [How to measure momentum](https://github.com/Auquan/Tutorials/blob/master/Measuring%20Momentum.ipynb)
4. [Model Selection Pitfalls](https://github.com/Auquan/Tutorials/blob/master/Trading%20Strategy%20Model%20Selection%20Pitfalls.ipynb)
5. [Avoid Overfitting](https://github.com/Auquan/Tutorials/blob/master/Overfitting.ipynb)
6. [Pairs Trading](https://github.com/Auquan/Tutorials/blob/master/Pairs%20Trading.ipynb)
7. [Long-Short Strategies using Ranking](https://github.com/Auquan/Tutorials/blob/master/Long-Short%20Strategies%20using%20Ranking.ipynb)

### Math
1. [Random Variables](https://github.com/Auquan/Tutorials/blob/master/Random%20Variables.ipynb)
2. [Expected Value and Standard Deviation](https://github.com/Auquan/Tutorials/blob/master/Expected%20Value%20and%20Standard%20Deviation.ipynb)
3. [Covariance, Correlation and Confidence Intervals](https://github.com/Auquan/Tutorials/blob/master/Covariance%2C%20Correlation%20and%20Confidence%20Intervals.ipynb)
4. [Stationarity, Integration and CoIntegration](https://github.com/Auquan/Tutorials/blob/master/Integration%2C%20Cointegration%2C%20and%20Stationarity.ipynb)

### Time Series Analysis
1. [ Part 1 - Stationarity, Auto Correlation, White Noise and Random Walks ](https://github.com/Auquan/Tutorials/blob/master/Time%20Series%20Analysis%20-%201.ipynb)
2. [ Part 2 - AR and MA models ](https://github.com/Auquan/Tutorials/blob/master/Time%20Series%20Analysis%20-%202.ipynb)
3. [ Part 3 - ARMA and ARIMA models ](https://github.com/Auquan/Tutorials/blob/master/Time%20Series%20Analysis%20-%203.ipynb)
4. [ Part 4 - ARCH and GARCH models ](https://github.com/Auquan/Tutorials/blob/master/Time%20Series%20Analysis%20-%204.ipynb)