Hello everyone,

For the last month, Shile Wen and I, two Quantitative Developer Interns at QuantConnect, have been building trading strategies for a small in-house fund. We've spent the last several Friday afternoons working on this project and today we are excited to announce that we've deployed the fund's first two live trading strategies! In this post, we'd like to introduce ourselves, explain how users can emulate our workflow, and reveal the strategies we've deployed.

Introductions
Derek Melchin
I was first introduced to quantitative trading in the summer of 2018. Over the last two years, I've enjoyed spending my free time studying various quant finance topics and building personal projects. For the 2019-2020 school year, I accepted an executive position at the University of Lethbridge Finance Club. During my time there, I hosted several educational sessions and competed in the 2020 Rotman International Trading Competition as the algorithmic-focused team member. In the latter part of the academic year, I accepted an internship as a Quantitative Developer at QuantConnect. Now I utilize my background in software development and entrepreneurship to help the community and develop trading strategies.

Shile Wen
I was introduced to Quantitative Finance when I was browsing Quora, and came upon a post about the Medallion Fund, the legendary fund ran by Jim Simons and RenTec. I thought it was fascinating, and that’s what got me hooked. I currently attend the University of Washington, with a major in Computer Science. At UW, I partake in the Algorithmic Trading Club at my school. I hope to help the community with their issues and develop trading strategies (we have a Strategy Library for those that want to view strategies developed by interns) for the community.

Team Workflow
Shile and I both work in different countries, yet we've been able to remotely manage the InternFund together via the project collaboration feature. In short, we performed our research independently but merged our strategies together into one project after we validated their individual performance. The Algorithm Lab made deploying these strategies very simple. For an overview of the point-and-click process, check out this quick video.

InternFund Strategies
A concern some users have, and rightfully so, is that our staff may take their private strategies. Rest assured, we don't. Our terms of service and privacy policy explain this at great lengths. Shile and I don't even have access to users' private projects or the Alpha Streams algorithms. The strategies we researched and deployed for the InternFund can be found in public research papers.

The strategies we deployed are:

Algorithm
We merged the two strategies into one classic-style algorithm. A backtest of our live deployment is attached.

Future Updates
We hope to keep the community updated with the performance of the InternFund throughout the rest of the summer, so stay tuned!

Best,
Derek Melchin

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