Some price series are mean reverting some of the time, but it is also possible to create portfolios which are specifically constructed to have mean-reverting properties. Series that can be combined to create stationary portfolios are called cointegrating, and there are a bunch of statistical tests for this property. We’ll return to these shortly. While …
This is the first post in a two-part series about the Hurst Exponent. Tom and I worked on this series together and I drew on some of his previously published work as well as other sources like Quantstart.com. UPDATE 03/01/16: Please note that the Python code below has been updated with a more accurate algorithm for …
In the first Mean Reversion and Cointegration post, I explored mean reversion of individual financial time series using techniques such as the Augmented Dickey-Fuller test, the Hurst exponent and the Ornstein-Uhlenbeck equation for a mean reverting stochastic process. I also presented a simple linear mean reversion strategy as a proof of concept. In this post, I’ll …
This series of posts is inspired by several chapters from Ernie Chan’s highly recommended book Algorithmic Trading. The book follows Ernie’s first contribution, Quantitative Trading, and focuses on testing and implementing a number of strategies that exploit measurable market inefficiencies. I’m a big fan of Ernie’s work and have used his material as inspiration for a great deal …
