How to Optimize the Trading Process in a Human-Centric Model

Angus Cameron is the Founder and CIO of Liminal Capital, a machine-learning focused investment manager.

But Angus does not come to markets with a computer science PhD. Rather, his career arc took him through the prop desks and buyside of Asia, trading global fixed income, FX, equity markets, and arbitrage strategies on a discretionary basis.

A machine-learning driven approach is a new endeavor, but one informed by the wisdom of experience. Angus would consider himself a quantitative trader, not a quantitative investor, and his approach reflects that. Like many systematic investors, Angus breaks the broad investment problem down into data ingestion, idea generation, position management, and risk management. Where he differs from many past guests is in the latter two pieces.

Informed by his trading experience, Angus places a strong emphasis on trade structuring and on-going position management. Liminal automates this philosophy by using swarms of systematic trading agents to place and manage different trades based upon the same underlying signals.

From market structure to machine learning: we cover the full range. I hope you enjoy my conversation with Angus Cameron.