Kris Longmore This article is adapted from one of the units of Advanced Algorithmic Trading. If you like what you see, check out the entire curriculum here. Find out what Robot Wealth is all about here. If you’re interested in using artificial neural networks (ANNs) for algorithmic trading, but don’t know where to start, then this article …
In keeping with our recent theme of providing useful tidbits of algo trading practicalities, here’s an elegant solution that resolves Yahoo’s unceremonious exit from the free financial data space. Regular readers would know that I use various tools in my algo trading stack, but the one I keep coming back to, particularly when I’m ready …
Earlier this year, I attended the Google Next conference in San Francisco and gained some first-hand perspective into what’s possible with Google’s cloud infrastructure. Since then, I’ve been leaning on Google Cloud Platform (GCP) to run my trading algorithms (and much more) and it has quickly become an important tool in my workflow! In this …
Recently, Yahoo Finance – a popular source of free end-of-day price data – made some changes to their server which wreaked a little havoc on anyone relying on it for their algos or simulations. Specifically, Yahoo Finance switched from HTTP to HTTPS and changed the data download URLs. No doubt this is a huge source of frustration, …
I recently read Gary Antonacci’s book Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk, and it was clear to me that this was an important book to share with the Robot Wealth community. It is important not only because it describes a simple approach to exploiting the “premier anomaly” (Fama and French, …
This is the final post in our 3-part Back to Basics series. You may be interested in checking out the other posts in this series: Part 1: An Introduction to Algorithmic Trading Part 2: How to Succeed at Algorithmic Trading We’ve also compiled this series into an eBook which you can download for free …
This is the second post in our 3-part Back to Basics series on successful algorithmic trading. You may be interested in checking out the other posts in this series: Part 1: An Introduction to Algorithmic Trading Part 3: Backtesting in Algorithmic Trading There is a lot of information about algorithmic and quantitative trading in the public …
This is the first post in our 3-part Back to Basics series which serve as an introduction to algorithmic trading. You may be interested in checking out the other posts in this series: Part 2: How to Succeed at Algorithmic Trading Part 3: Backtesting in Algorithmic Trading This is the first in a series of posts in …
What if you had a tool that could help you decide when to apply mean reversion strategies and when to apply momentum to a particular time series? That’s the promise of the Hurst exponent, which helps characterise a time series as mean reverting, trending, or a random walk. For a brief introduction to Hurst, including …
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 …
