Providing University College London Students With Real-Life Quantitative Trading Experience
At QuantConnect, we’re always interested in how our users are deploying our institutional-grade technology. With Organizations, QuantConnect is more flexible and customizable than ever before, allowing you to scale up and down your resource use as your team grows.
The University College London (UCL) Fintech Society is a student-run finance, technology, and entrepreneurship organization open to anyone from UCL, Imperial College, and King’s College London. The society, with over 2,500 members, offers networking and career-building opportunities to students studying computer science, economics, and engineering. The society also studies the newest industry innovations in tech and finance to ultimately prepare students for a career in Fintech after graduating. In the tech sector of the society, students from UCL started an internal quantitative trading competition using QuantConnect.
Adam Peace and Simon Fattal, the Director and Executive of the society’s Quant division respectively, are both completing their Master’s degrees in Computer Science with an emphasis in Machine Learning. Over the past year, they set up this competition following their keen interest in algorithmic trading. They say the internal trading competition they organized is the first long-term event the society has had, and to their knowledge they are the first society in the UK to create an algorithmic trading event of this kind, attracting over 100 graduate students from Computational Finance and Machine Learning programs.
The competition, using QuantConnect’s liquid ETF universe, is broken into two months. Students spent one month in December writing their strategies on QuantConnect, and their strategies are tested over the month of January. Winners are named in February based on the profitability of their strategies.
The trading competition is facilitated by QuantConnect’s Organizations layer, as 65 students were able to collaboratively work in their respective organizations with supervision. “You can create and administer different permissions to be able to backtest and monitor their usage to make sure they’re not going over the quota, and that was really useful,” Adam said.
For newcomers, Simon said the extensive documentation available on QuantConnect was a great learning tool. Simon says many of their members are new to the algorithmic trading world, and having solid documentation can make a world of difference. “Having good documentation really helps people, especially when you’re frustrated because something’s not working. I thought the documentation was really thorough, and some of the documentation pages even have a video walkthrough, which is helpful.”
If you’re looking to give your students hands-on experience in algorithmic trading, get in touch with us at email@example.com.