Introducing Man AHL Technology
Technology is at the heart of everything we do at Man AHL. State-of-the-art quantitative trading strategies necessitate state-of-the-art technology at all stages; from market data acquisition and initial research through to model implementation and trade execution.
Who we are
We are a group of over 60 software technologists with varied backgrounds including computer science, mathematics, physics, engineering and classics.
Our team includes astrophysicists, musicians, and a Kendo champion. We speak over 10 languages. What unifies us is a passion for writing high-quality code.
Our developers are organised into small cross-functional teams. Our engineering roles cover a spectrum from developing our platform and core technology (“Core System Developers” or “Trading Systems Developers”) through to using the platform and working with our Quant Researchers to develop trading models (“Quant Developers”). People often rotate teams in order to learn more about our system, as well as find the role that best matches their interests.
Technologies we use
All of our production systems use Linux. We are heavy users of Python and its full scientific stack including numpy, scipy, pandas and scikit-learn.
While most of our codebase is written in pure Python, when we push the performance boundaries of Python we use Cython/C/C++ as required. We implement the systems that need the highest data throughput in Java.
Some other tools we use:
|Apr 2019||Instrument your infrastructure with Prometheus|
|Mar 2019||OpenStack VM balancing with Python|
|Nov 2018||Capturing System Core Dumps|
|May 2018||Core dumping, in Docker and beyond|
|Mar 2018||Logging in Large Mathematical Models|
|Jan 2018||Testing with pytest|
|Dec 2017||Man AHL: an intern’s perspective|
|Oct 2017||The Curious Case of the Longevity of C|
|Sep 2017||Why Python?|
|28 Jun 2018||ML Meetup: Deep Image Prior|
|20 Jun 2018||ML Meetup: Graphcore and Symbolic Representation Learning|
Working with others
At Man AHL we have benefited hugely from open-source technologies. We contribute back to the community whenever we can.
- We have open-sourced Arctic, the time series storage engine that powers all of our internal time series data; as well as PyBloqs, a project we use heavily for internal reporting
- As heavy users of Python and its scientific stack, we sponsor and host the Pydata meet up: London’s biggest monthly event for data scientists using Python
- We attend and sponsor major scientific and programming conferences, including ICML, NIPS, and PyData London
- Given that maths and code drive everything we do, we support maths and programming education and we sponsor the UK team at the European Girls’ Mathematical Olympiad
Join the conversation
Another successful machine learning meetup was hosted by @Man_AHL yesterday! This meetup welcomed Markus Wulfmeier, a postdoctoral research scientist at the Oxford Robotics Institute, who discussed ‘Saving Time - Increasing Human Efficiency for Robot Supervision’. We also had Andrew Davison, Professor of Robot Vision at Imperial College, who gave an overview of ‘Real-Time 3D Scene Perception Using Vision’. For all things technology at Man AHL, visit: www.ahl.com/technology . #MachineLearningMeetup #MachineLearning #AI #ArtificialIntelligence #science #data #bigdata #datascience #tech #analytics #algorithm #networks #meetup #techmeetup #technetworking #deeplearning #robotics #robots #OxfordRoboticsInstitute #digital #3D #stem #techeducation #technology #coding #computerscience
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