Man vs. machine: the next frontier for ETFs? (via kirstenchang16 for ETFEdgeCNBC)
Artificial intelligence and machine learning could be the next frontier for ETFs to outperform the market.
A veteran in the business, Tull has been involved in the ETF industry for decades, creating more than 400 ETFs across 18 different countries. Now, he's looking at new ways to beat the market by using big data as raw material, combined with machine learning, to build ETF portfolios that could potentially outperform active management — even actively managed ETFs.
"Active management has been out there for a long time, underperforming," he said on CNBC's"ETF Edge.""They haven't found a solution yet, and I think the technology that I've run into is going to help the marketplace today."
The key to this new technology is ensemble analytics, a type of methodology that uses multiple learning algorithms to better predict performance."The technology's been around for years," Tull said. "It's just never moved into the asset management space, so [it's about] getting data collected, running permutations against it and then really focusing on the best of the best selection that's diversified." headtopics.com
In other words, instead of picking individual stocks, Tull aims to make smart beta even smarter by extracting data from other ETFs and attempting to build the smartest of them all.Smart beta involves the use of a rules-basedsystem, or a series of factors, for selecting investments to include in a fund's portfolio. These funds are governed by a specific set of rules and are typically weighted differently from the traditional market cap-based weighting scheme.
Goldman Sachs has done just this with its(GSLC), which looks at four different factors — value, momentum, high quality and low volatility — and weights them accordingly. Read more: CNBC »
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kirstenchang16 ETFEdgeCNBC An exchangeTradedFund (ETF) is an investmentFund trade-d on stockExchange's, much like stocks. An ETF holds assets such as stocks, commodities, or bonds. I had to look it up. The author/editor assumes everyone knows what it is. -- kirstenchang16 ETFEdgeCNBC Don’t need to many of these
kirstenchang16 ETFEdgeCNBC Do we understand what we mean - by the 'I' in AI?
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