Robo-advisors have burst onto the trading scene in recent years, and some estimates suggest these automated trading algorithms will be responsible for nearly half a trillion dollars of assets under management (AUM) by 2020.
According to Aferiat, the first wave of robo-advisors has been mostly query-based. In other words, these robo-advisors ask a question and then sort through massive loads of data seeking an answer.
Aferiat believes the next wave of robo-advisors will have the artificial intelligence capabilities to generate market insights and actionable trading ideas.
"To secure true alpha, the machine trading needs to be able to generate ideas and be correlated to the second wave in robo advisement – artificial intelligence," Aferiat explains.
That's the primary objective of Trade Ideas' machine learning system, nicknamed "Holly." The system was given the name as a play off of the idea that it will be "The Holy Grail" of investing technology.
Every day, Trade Ideas takes a fresh batch of market data and feeds it to Holly to add to a historical database. The system then creates what's called a "quantitative combine."
"Holly then takes that information, measures the performance of the base strategies, optimizes them, and reduces it down to a few algorithms. Trade Ideas can then publish this trade regime of ideas to their customers," Aferiat explains.
Aferiat believes that Trade Ideas' cutting-edge machine learning technology has created a window of opportunity for investors to outperform while other robo-advisors still rely on first-wave technology.
© 2023 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.
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