Providing Bond University 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.

At Bond University in Queensland, Australia, students in Rand Low’s and Bruce Vanstone’s Financial Trading Systems course are getting access to high-level data through QuantConnect. The course is for students studying data science and analytics but specifically caters to those interested in investment banking and quantitative finance. 

Centered around learning the tools and strategies used by hedge fund managers, the course teaches students how to develop strategies in Python using data pulled from various resources. 

Rand, an associate professor at Bond, previously worked on Wall Street as a quant for firms such as Bank of America, Merrill Lynch, and BlackRock. As a professor, he made the jump to the QuantConnect platform in late 2020, and has been using it in his classroom since. 

“QuantConnect allows [students] free access to data in a structured manner. That enables students to explore financial market anomalies and see if previous historical events of the 1970s and 1980s are still relevant in today’s market,” Low said. “They can understand that conditions are always different and that financial markets are a Level 2 chaotic system. Level 2 chaotic systems react to predictions about them, and therefore they are very difficult to predict accurately,” he said. “QuantConnect gives students a practical means to evaluate how trading strategies that may have worked in the past may not work in the future, due to the efficient market hypothesis.”

Another benefit students gain from QuantConnect is backtesting accuracy. Rand said his Ph.D. students use their own localized backtester, and he urges them to use QuantConnect’s online backtesting system after.  This ensures consistency between their localized backtesters that are implemented for speed and QuantConnect’s online backtester that is optimized for robustness and real-time trading accuracy. He also said the online programming interface is exceptionally beneficial in helping students get started.

With this level of data available to students at little to no cost from QuantConnect, his students are able to achieve their goal of learning how trading and investing works in both high and low-frequency environments. 

If you’re looking to give your students hands-on experience in algorithmic trading, get in touch with us at

Lexie Robinson

By: Lexie Robinson