Interview with Jared Broad, Founder and CEO of QuantConnect

QuantConnect combines cloud computing and open data access, and has one of the largest quantitative trading communities in the world constantly building, sharing and discussing strategies. QuantConnect provides software to design and test trading strategies on free data in multiple programming languages. Jared Broad, the founder and CEO of this innovative fintech firm shares insight about QuantConnect and the quant trading sphere as a whole.

Quant News: Can you give us an introduction to how QuantConnect formed and where the idea came from?

Jared Broad: The idea for QuantConnect came from my own trading. I had ideas that I wanted to apply to the markets so I started gathering data, building a platform and backtesting them. It was a full time task for about two years before I had something resembling a reliable system. After going through that process I saw there was a need to make it easier for others and QuantConnect was born.

QN: Could you give us a rundown of the quant tools that your website offers?

JB: The core of QuantConnect are three services: 1) A research CLI environment for free form data exploration and manipulation, 2) a complete backtesting environment for realistic strategy testing, and 3) a seamless live trading environment which can deploy the same algorithms from backtested code. Beyond this we offer the ability to quickly download pre-formatted Forex data ready for backtesting, tutorials to help you learn quant concepts and a large quant community to learn from and interact with.

QN: Which programming languages can be used to build a trading strategy?

JB: Through QuantConnect you can build a strategy in Python, C# or F#. We are fully cross platform and have users in markets around the world.

QN: With the recent explosion of quant trading, what do you think is the best way to get to started with QuantConnect?

JB:  We’ve recently launched a new interactive tutorial system called “BootCamp”. This guides you step by step through creating your first algorithms. Once you get through boot camp check out our YouTube channel; if you’d like to jump in and code you can use our documentation. We also provide about 100 example algorithms to get started so there is plenty of information to learn from.

QN: What is the process like when going from backtesting an algorithm at QuantConnect to implementing it to a live trading environment?

JB: Our aim is to make the transition from backtesting to live seamless and instant. We have put a lot of work into standardizing the platform to achieve that. Today you can backtest an algorithm and live trade it in seconds.

QN: I noticed that your website has a community section, where the users can communicate with each other. What do you think sets your community apart from other online quant trading communities?

JB: Our community includes engineers, scientists, and data scientists all with a passion for the financial markets and interest in the QuantConnect platform. We are one of the biggest communities in the world in the quantitative trading space.

QN: Why would a trader go to a place like QuantConnect instead of going the traditional route and developing their own algorithmic trading framework?

JB: People use QuantConnect to focus on the imporant part of the strategy — the alpha. When people start building their own framework they often spend 99% of their time managing data or fixing bugs. We’ve invested years of engineering building a powerful open-source platform to fast-track the development process.

QN: As of now, approximately how many ‘unique’ strategies have been made fully available to the quant community via QuantConnect?

JB: There are thousands of algorithms shared in the forums by users eager to help others learn. In addition we’ve provided hundreds of examples for people to get started on their own. The vast majority of users keep their algorithms private and trade on their personal accounts.

QN: How does QuantConnect help people who are interested in the research side of strategy development?

JB: We provide a research environment which allows traders to directly manipulate data and experiment with ideas in Python. This gives you full access to the data, down to individual ticks, in a batch format so you can draw charts and apply array-based math on your algorithms.

QN: So that we can give our readers something to be excited about, what possible new features are you looking at on the horizon?

JB: We’ve got a lot of exciting stealth projects coming in the near future. One we can share is called the Market Place — it will allow you to build and share algorithm modules so you can create robust algorithms quickly.

To learn more about QuantConnect, watch our exclusive webinar with Jared here.


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