Answers to Questions I Often Get: Engineering and Interviewing at HRT
It’s been over a decade since I last wrote something about HRT. A lot has changed since then. HRT is much larger, and we trade in many more venues and in many different time horizons. But I still feel like the fundamental vibe is, thankfully, similar. We do now have a...
Building a Distributed Filesystem for Scalable Research
The ability to store and analyze vast amounts of data is table stakes for an algorithmic trading firm like HRT. Some of our storage requirements weren’t well met by existing solutions, so we decided to build and operate our own distributed filesystem, called Blobby....
Inside HRT’s Python Fork: Leveraging PEP 690 for Faster Imports
Python @ HRT At Hudson River Trading (HRT), we’ve found that centralizing our codebase facilitates cross-team collaboration and rapid deployment of new projects. Therefore, the majority of our software development takes place in a monorepo, and our Python ecosystem is...
Optimising Compiler Performance: A Case For Devirtualisation
In the realm of high frequency trading, speed is critical. Programmers working on production systems at firms such as HRT must write code that is highly performant without compromising correctness. To achieve that, we should be aware of how compilers work, the ways...
Building Robust Codebases with Python’s Type Annotations
Hudson River Trading’s Python codebase is large and constantly evolving. Millions of lines of Python reflect the work of hundreds of developers over the last decade. We trade in over 200 markets worldwide — including nearly all of the world’s electronic markets — so we need to regularly update our code to handle changing rules and regulations.