Discussions about how artificial intelligence can be used in asset management have become fashionable if not overheated. AI and related technologies such as machine learning have demonstrated success in applications ranging from self-driving cars to chess to speech recognition, so it is natural to ask how they could be applied to asset management.
But the fact of the matter is that the question has been asked ― and answered ― for years at Capital Fund Management (CFM), a global asset manager founded in 1991 that uses quantitative and systematic techniques to implement trading strategies and manage client assets globally.
“This sudden interest is in many ways puzzling to us because we feel AI is merely a natural evolution of what we have been doing for 28 years,” said CFM's Laurent Laloux, chief product officer. “We've always tried to use the most up-to-date techniques to analyze ever-growing volumes of data and identify opportunities. These techniques have included statistical modelling in the 90s, which was normally the preserve of the academic lab, electronic trading in the early 2000s and AI techniques today.”
CFM's response to investor interest in AI ― and the current hype surrounding it ― is to strike a middle ground, providing a research and science-based answer.
“Don't expect AI to be a complete change of paradigm in finance right away,” Laloux said. Instead, he pointed out that it is one technique among many that CFM uses in data analytics and trading platforms, and requires hard work, commitment and deep experience in the science of machine learning. Also essential is a deep understanding of capital markets and the experience to know where AI could help and where it could hinder.
Artificial intelligence was first coined in the 1950s along with a rush of research to develop learning machines. With limited progress, the AI winters in the '70s & '90s saw a drop in funding and a slowdown in progress. But with a dramatic increase in computing power through the 2000s and greater availability of data and code through the open source community, AI has become one of the hottest topics this decade.
According to Laloux, while “AI is currently more an evolution than revolution” in asset management, it does bring with it new capabilities.
“We can create models using AI techniques that allow us to capture regularities in the data that humans would otherwise have a hard time noticing,” he said.
It has this ability, Laloux argued, because modern AI models are better at grasping patterns than traditional statistical tools. “That's why people are very excited by this new technology,” he said. “We also have the computing power and data we can leverage to make it successful, that is what is really new nowadays.”