Helios Integrates Machine Learning Into Its Investment ModelsHelios Integrates Machine Learning Into Its Investment Models
While the technology will be used to identify patterns in large data sets, it will not be used to automatically initiate any trading on its own.
Helios, a quantitative asset management firm that provides outsourced chief investment officer services to advisors, announced this week that it started integrating machine learning into its custom investment models.
With it Helios expects to be able to quickly review hundreds of data series across its models and process thousands of trading and market signals monthly to find the highest predictive patterns.
While it is still early days, artificial intelligence is already reshaping modern wealth management. It is already fostering client engagement while driving efficiency across the advisor workflow, from client onboarding to financial planning to portfolio management.
William Trout, director of wealth management for Javelin Strategy and Research said there was vast potential to energize advisor decision-making with this type of development, and identifying investment opportunities was at the forefront.
Chris Shuba, Helios founder and CEO, said his firm developed this new machine learning capability in-house with assistance from a long-standing Amazon Web Services relationship and a more recent partnership with Microsoft Azure.
“It’s an optimization structure for us ... it’s the ability to take on vast amounts of data at one time and get near-instant calculations and answers out of it,” he said, and noted that the output of Helios’ machine learning structure does not automatically trigger trading activity.
“We’re not hooking it up to a trading platform,” he said.
Shuba said he saw this advancement as a “leap forward” because this would allow advisors to be less dependent on long-run data correlations.
Trout said from a competitive standpoint, the ability to harness market data and trading signals, along with the flourishing of alternative data sets, will give forward-thinking advisors “a critical advantage in the battle for client assets.” Enhanced compliance and reporting capabilities will be another benefit, he said.
Earlier this month, Helios rolled out a new feature that allows advisors to customize the frequency of their quantitative models rebalancing. Advisors are now able to schedule rebalances, within the parameters of their chosen models.
In July, Helios launched new sleeving capabilities, giving advisors the ability to customize the firm’s model portfolios to reflect their or their clients’ personal preferences.
Founded in 2016, Helios now works with around 800 advisors with a collective AUM of over $30 billion.
