QuantStart News - July 2020

Find out what QuantStart has been working on in July 2020.

Last month we started a new series of posts designed to keep the QuantStart community informed of what the QuantStart team had been working on in the prior month. In this post we talk about what we've been up to in July 2020.

Articles and Tutorials

In July we reviewed our Content Survey for 2020 where it was shown that many in the community were interested in the Machine Learning & Deep Learning, as well as the Trading Infrastructure, content topics.

We researched and published two articles on the topic of Deep Learning—an area that is showing promise for certain types of systematic trading strategies. The first article discussed how to install an up to date version of the TensorFlow ML library against an Nvidia GPU:

The second article described the basics of the perceptron, which is a simple supervised linear classifier machine learning method. We outlined how the perceptron forms the building blocks of larger artificial neural networks:

We also began another new series of articles on how to connect to the Interactive Brokers Native Python API. In the first article we discussed how to test the connectivity with IB and how to interact with their API:


In addition to publishing new article content, QuantStart has been answering more insightful questions from the Quantcademy membership forum community recently.

Topics discussed in July include choosing the most appropriate modules at undergraduate and postgraduate level for targeting a quant researcher career as well as how to find and include fundamental data sources for use in systematic forex strategies.

What's Next?

We will be continuing to research and publish more content on both Deep Learning and Interactive Brokers connectivity, so expect to see some new posts in the following weeks.

As always if you have any questions about quant careers, systematic trading or mathematical finance please feel free to get in touch at support@quantstart.com and we'll do our best to get back to you.