Skip to content
Ipython notebooks for math and finance tutorials
Jupyter Notebook
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.
ARIMA + GARCH to model SPX returns.ipynb
Covariance, Correlation and Confidence Intervals.ipynb
Expected Value and Standard Deviation.ipynb
Integration, Cointegration, and Stationarity.ipynb
Long-Short Strategies using Ranking.ipynb
Mean reversion.ipynb
Measuring Momentum.ipynb
Momentum Strategies.ipynb
Overfitting.ipynb not needed/to be deleted Feb 27, 2017
Pairs Trading.ipynb
Random Variables.ipynb
Simple ML Strategies to generate Trading Signal.ipynb
Time Series Analysis - 1.ipynb
Time Series Analysis - 2.ipynb
Time Series Analysis - 3.ipynb
Time Series Analysis - 4.ipynb
Trading Strategy Model Selection Pitfalls.ipynb


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


Trading Strategies:

  1. Mean Reversion Basics
  2. Momentum Strategy Basics
  3. How to measure momentum
  4. Model Selection Pitfalls
  5. Avoid Overfitting
  6. Pairs Trading
  7. Long-Short Strategies using Ranking


  1. Random Variables
  2. Expected Value and Standard Deviation
  3. Covariance, Correlation and Confidence Intervals
  4. Stationarity, Integration and CoIntegration

Time Series Analysis

  1. Part 1 - Stationarity, Auto Correlation, White Noise and Random Walks
  2. Part 2 - AR and MA models
  3. Part 3 - ARMA and ARIMA models
  4. Part 4 - ARCH and GARCH models
You can’t perform that action at this time.