Robot Wealth Part Two: Collaborative Research for Systematic Trading

Articles From: Interactive Brokers
Website: Interactive Brokers


Contributing Writer at Interactive Brokers

Power Couple: Prop Trading & Education. Robot Wealth Part 1″ is the first installment in this series. Click here to read it.

Kris Longmore, founder of prop trading and education hybrid Robot Wealth (RW), believes in collaboration. Over the past several years he and his partner, James Hodges, have developed a research platform in which members of their RWPro community exchange ideas using shared notebooks and a database of trading edges.

Longmore says the most important element of collaborative research is reproducibility.

“It’s a major issue. Imagine the tangle we’d get into if we published some research and someone else tried to extend it but couldn’t get the code to work because of a missing dependency. Or worse, got a different result?”

To prevent that, RWPro members do their collaborative research in hosted Jupyter Notebooks on Google Colab. Whenever a member opens a research item, they get the same clean Ubuntu instance.

“Of course, we recognize that when people first come to us, they often haven’t used Colab, Jupyter, GitHub, R, Ubuntu, or the other tools. So we offer optimized code that installs the necessary components. We also provide training material. That way, people can get going quickly, and we’re all starting from the same place in the process.”

Longmore and Hodges share each piece of research in a GitHub repository.

“When you start researching a potential edge, it’s all very iterative and messy. We want our community to understand that, so we let them look over our shoulders and see what we’re doing and how we’re doing it.”

To see a research notebook, a visitor just needs to enter RW’s GitHub library and click the “Open in Colab” button.

Attribution: GitHub

“We provide a library of clean, updated data and an R package for pulling that data into a research session. We also have a library of code snippets that work with our data sets and that people can reuse rather than writing analysis code from scratch.”

In Longmore’s view, productivity is the second key element.

“In pursuit of productivity, we maintain an Edge Database where we store all our ideas for future research and summaries of any work the group has previously done. Everyone shares their work so no one wastes time reinventing the wheel.”

Attribution: GitHub

Longmore says the third critical piece is feedback. Using the GitHub pull request framework, members can submit their research and have the RW team review it and provide personalized feedback.

“James and I are driven by the idea of helping people become truly independent by acquiring the necessary skills. The collaborative research framework directly supports that.”

Attribution: GitHub

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