ORLANDO, Florida, Oct 17 (Reuters) - Technology has been

the main driving force behind the evolution of financial markets

in recent decades, with the explosion of automated and

algorithmic trading fostering the eye-popping speed, efficiency,

and liquidity that traders and investors enjoy today.

Artificial intelligence is likely to accelerate these

positive changes and revolutionize financial markets along the

way.

But with the benefits come potential dangers, including the

risk that markets will become more vulnerable to frequent bursts

of short-term turbulence and volatility.

Generative AI technologies like ChatGPT may be in their

infancy, but their use across society is mushrooming at an

alarming rate. Generative AI's adoption rate since its mass

launch nearly two years ago is 39.4%, according to a blog post

last month by St. Louis Fed economist Alexander Bick, Vanderbilt

University's Adam Blandin and Harvard's David Deming. That's

twice the adoption rate for the personal computer three years

after its mass introduction, and the internet after two years.

And St. Louis Fed economists and researchers Aakash Kalyani,

Serdar Ozkan, Mickenzie Bass and Mick Dueholm noted in a

separate blog last month that AI-related chatter in company

earnings calls has increased over fivefold since the launch of

ChatGPT in late 2022.

The financial industry is taking part in this trend. The

International Monetary Fund notes that when Large Language

Models first appeared in 2017, only 19% of patent applications

related to algorithmic trading featured AI content. That figure

jumped to more than 50% in 2020 and has remained above that

level ever since. This suggests a "wave of innovation" in

financial markets could be coming.

This could be very good news for the financial industry, as

AI has the potential to take the efficiency of trading,

investment and asset allocation to new heights.

Generative AI's ability to instantaneously analyze vast

quantities of information could enhance market performance by

generating more accurate trading signals, improving risk

management, strengthening trading models, and spotting trends.

AI also has the potential to improve liquidity and help iron

out price distortions in markets with a wide range of

instruments that don't lend themselves to automated trading,

like corporate bonds.

It may even enhance returns. A working paper published in

May by University of Chicago researchers Alex G. Kim, Maximilian

Muhn and Valeri V. Nikolaev found evidence that investors may be

able to deliver higher cumulative returns over time by following

investment signals from simple ChatGPT-based analysis. The

technology's apparent ability to "uncover value in smaller

stocks" is a notable feature.

True, if everyone is using the same technology, any trading

benefit could wane over time, but this would likely only fuel

the drive for greater innovation as investors seek to remain one

step ahead.

CASCADING AND HERDING

Of course, there are serious risks as well.

The IMF highlighted a few of them in its latest Global

Financial Stability Report, following discussions with an

extensive range of stakeholders, including banks, dealers, AI

vendors, asset managers, academics, and market infrastructure

firms.

One of the most pertinent concerns is the potential for a

sudden evaporation of liquidity, and even the cessation of

trading, during periods of high volatility as market

participants scramble to minimize losses. Algorithmic trading

strategies, enhanced by AI, could create a "cascading" effect

triggering negative feedback loops.

The risk of "potential herding and market concentration" is

particularly acute, the IMF notes, if only a handful of

providers are designing the AI programs and Large Language

Models that are enhancing these algos. This is likely the case

right now.

The IMF notes that there is already evidence the U.S. stock

market has seen algo-driven liquidity dry up - albeit only

briefly - during times of high stress. This reflects that fact

that many participants are essentially on the same side of

trades and their models are designed to respond to many

situations in the same way.

In addition, AI is likely to accelerate the shift of

market-making activities to less regulated corners of the

financial universe like hedge funds, proprietary trading firms,

and other non-bank financial intermediaries.

Increased opacity will make it harder for regulators and

authorities to monitor these activities, which, in turn, could

create more opportunities for cyberattacks, market manipulation,

fraud, and online dissemination of disinformation.

But there is no going back to the pre-AI world. Markets have

little option but to accept and embrace technology. This means

investors - and financial regulators - have to accept the

potential risk, disruption and danger AI could bring along with

its many benefits.

(The opinions expressed here are those of the author, a

columnist for Reuters.)