Demystifying the Hurst Exponent – Part 2
What if you had a tool that could help you decide when to apply mean reversion strategies and when to
What if you had a tool that could help you decide when to apply mean reversion strategies and when to
This is the first post in a two-part series about the Hurst Exponent. Tom and I worked on this series
This post comes to you from Dr Tom Starke, a good friend of Robot Wealth. Tom is a physicist, quant
It would be great if machine learning were as simple as just feeding data to an out-of-the box implementation of
Last night it was my pleasure to present at the Tyro Fintech Hub in Sydney on the topic of using
If there’s one thing I’ve done a lot of over the last few years, reading would be it. I’ve devoted
Introduction My first post on using machine learning for financial prediction took an in-depth look at various feature selection methods
Disclaimer: I am not posting this at the behest of the developers of Zorro, nor do I receive any form
Updates: 2019: In this first Machine Learning for Trading post, we’ve added a section on feature selection using the Boruta
Recently, I wrote about using mean-reversion time series models to analyze financial data and build trading strategies based on their
In the first Mean Reversion and Cointegration post, I explored mean reversion of individual financial time series using techniques such
This series of posts is inspired by several chapters from Ernie Chan’s highly recommended book Algorithmic Trading. The book follows Ernie’s