Here’s How Elite Investors Gain An Edge With Artificial Intelligence And Machine Learning

Here’s How Elite Investors Gain An Edge With Artificial Intelligence And Machine Learning

Machine learning and artificial intelligence may seem like the substance of sci-fi movies. But private equity companies, major banks, and hedge funds are deploying technology to acquire an edge.

Citigroup (C) uses machine learning how to make portfolio recommendations to customers. High-frequency trading firms rely on machine learning programs to read and respond to markets. And stores like PanAgora Asset Management have developed complex algorithms to test investment ideas.

A lot of the technology that elite traders utilize is not really new. Financial firms are only better able to harness the power of AI and machine learning because the computers of today can process data. Then there did years ago and there exists vastly more information.

Emergence Of Machine Learning

Still, technology is disrupting the industry -- and will continue to do so.

The growth of machine learning is really going to make Industrial and financial sector unrecognizable in the future.

For example, Citi Private Bank has deployed machine learning how to help financial advisors answer a question they asked: What are investors doing with their money? The lender can anonymously share portfolio motions being made by customers all around Earth, by using technologies.

"Traditionally that type of data was sourced from the network. You might have had a few java or heard of it over a cocktail," Philip Watson, head of the global investment lab at Citi and chief innovation officer at Citi Private Bank, told CNN Business. "Now we could share insight that is very valuable."

A recommender engine was built by Citi, that leveraged ML tools to advise clients. The platform advocates even alert clients of events such as the maturity of a bond within their portfolio, solutions and tailored research reports.

Machines Help High-Speed Traders

Domeyard, a Boston hedge fund that concentrates on high-frequency trading, depends on machine learning how to decipher 300 million data points in the New York Stock Exchange hour of trading alone.

"We rely on the assistance of machines to create simpler and faster predictions of what's going to happen in the next second or minute," said Christine Qi, Domeyard's co-founder, and partner.

But Qi cautioned that machines are "just as smart as the information you are feeding it."

Earlier this season, PanAgora, the Boston quant store, enlarged its exposure to China by starting a "self-learning" algorithm that deciphers Chinese "cyber slang" utilized by investors on social websites to get around government censorship, Chen said. The findings give portfolio managers at PanAgora a valuable window to the sentiment among retail investors, who dominate the market in China.

Man Vs. Machine?

Technology executives warn to not believe all of the hype about machine learning and artificial intelligence --, especially about robots replacing us at workspaces.

However, some of the effects could be hugely exaggerated. It’s an individual plus machine world. It is not a version that is machine-only. Nor do I find it becoming a machine-only model for a long, long time.

Chen of panAgora said. "It's not man versus machine. It's a machine plus man."

At PanAgora, humans have the final say on investment choices and sometimes override what the computer models let them do.

"Machines aren't sentient. Terminators aren't likely to grow up and kill us in another 10 years," Chen said.

Most Jobs Will Be Impacted

But that does not mean humans won't be disrupted.

"We do believe that 100% of all roles and jobs could be affected," said Mark Foster, senior vice president of IBM (IBM) Global Business Services.

Foster said that the result is that businesses, governments and education systems get by re-skilling workers ahead of this disruption.

"Probably the world is moving more slowly than that. There's a risk that individuals will be left behind," Foster explained. "It's incumbent upon us in business that we are assisting our workforces to get ahead of the curve".

Rather than getting displaced that are outright, the Watson of Citi thinks employees doing menial tasks could be moved to positions that are more rewarding.

What Is Next?

In the future, the increase of technologies that are emerging will further disrupt the industry -- such as quantum computing.

"It will be able to solve problems we might never touch before," said Mark Jackson, a scientific guide at UK-based Cambridge Quantum Computing.

IBM (IBM), Google, Intel (INTC) and other major businesses have spent heavily to develop quantum technologies, but experts aren't exactly sure what these supercomputers will be utilized for.

"We actually don't understand yet," Jackson said when asked for particular use cases. "We're only starting to understand the power of this."

He said it appeared that quantum computers will excel in a number of areas: chemistry, security, encryption, and machine learning.

"It will fulfill the hype," Jackson stated.

There are still lots of things that computers can not do in the financial realm.

For example, investors use game theory to map other market players can react to a given position. Game theory enables firms to cash in by positioning before market swings that are sharp occurring.

PanAgora's Chen said that machines can't do this -- yet.

"I really hope to see it at the next five to 15 decades," he said.