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

Name		Name	Last commit message	Last commit date
Latest commit History 78 Commits
.gitattributes		.gitattributes
.gitignore		.gitignore
ARIMA + GARCH to model SPX returns.ipynb		ARIMA + GARCH to model SPX returns.ipynb
Covariance, Correlation and Confidence Intervals.ipynb		Covariance, Correlation and Confidence Intervals.ipynb
Expected Value and Standard Deviation.ipynb		Expected Value and Standard Deviation.ipynb
Integration, Cointegration, and Stationarity.ipynb		Integration, Cointegration, and Stationarity.ipynb
Long-Short Strategies using Ranking.ipynb		Long-Short Strategies using Ranking.ipynb
Mean reversion.ipynb		Mean reversion.ipynb
Measuring Momentum.ipynb		Measuring Momentum.ipynb
Momentum Strategies.ipynb		Momentum Strategies.ipynb
Overfitting.ipynb		Overfitting.ipynb
Pairs Trading.ipynb		Pairs Trading.ipynb
README.md		README.md
Random Variables.ipynb		Random Variables.ipynb
Simple ML Strategies to generate Trading Signal.ipynb		Simple ML Strategies to generate Trading Signal.ipynb
Time Series Analysis - 1.ipynb		Time Series Analysis - 1.ipynb
Time Series Analysis - 2.ipynb		Time Series Analysis - 2.ipynb
Time Series Analysis - 3.ipynb		Time Series Analysis - 3.ipynb
Time Series Analysis - 4.ipynb		Time Series Analysis - 4.ipynb
Trading Strategy Model Selection Pitfalls.ipynb		Trading Strategy Model Selection Pitfalls.ipynb
download.png		download.png

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Tutorials

Contents:

Trading Strategies:

Math

Time Series Analysis

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