(TND) — Artificial intelligence is becoming a part of everyone’s life, and that goes for Wall Street stock traders as well.
As with any AI application, it has potential benefits and potential risks.
One expert said that the more traders rely on computers to make decisions, the more likely everyone is to buy and sell based on the same analysis from the same underlying programs.
Pawan Jain, assistant professor of finance at West Virginia University, said there is a danger of too much homogeneity within the market.
“If everyone is on the buy side and no one wants to sell, the market will crash,” Jain said.
Jain, who has studied algorithmic trading for years, said the shift to purely computerized forms of trading was “inevitable.”
The reason, he said, is that these tech tools, including AI, are useful and profitable for stock traders.
AI could rob the market of analytical diversity, but Jain said the dangers don’t stop there.
Traders took advantage of technology to execute trades at lightning speed.
Trading is now done in nanoseconds.
“The speed definitely increases the size of the loss,” he says.
AI-powered tools create market volatility, and more market volatility increases the risk of a crash, Jain said.
He argues that investors are no longer looking at the true price because computer-driven trading happens so fast that stocks can’t keep up.
The potential impact of AI on financial markets is enormous, with over $1 trillion of assets being replaced every day.
Institutional investors began using computer programs in the early 1980s to execute large trades quickly and efficiently.
Jain said “programmed trading” became more sophisticated and popular before sparking the 1987 Black Monday stock market crash.
Jain said regulators have taken steps to limit the use of program trading, including circuit breakers that stop trading in the event of significant market volatility.
However, the popularity of program trading continued to grow. High-frequency trading, which began in the early 2000s, was the next big technological evolution.
Jain said it has reached a stage where stock traders can use AI algorithms to analyze large amounts of data in a way humans cannot.
Jain said traders who use these tools typically buy and sell assets at very close to market prices, so they don’t charge high fees to investors.
That’s one of the advantages.
And that helps ensure that there are always buyers and sellers in the market, Jain said.
He said the technology could mitigate the effects of market inefficiencies.
But Jain cautioned that such AI-powered tools can react so quickly to market signals, even small ones, that they can cause sudden spikes or falls in asset prices.
He said the 2010 “flash crash” was a cautionary tale. Nearly $1 trillion in market value was erased and restored in minutes.
Herd mentality in stock trading can be dangerous, Jain said, and trading algorithms powered by ChatGPT and similar programs could “make things even worse.”
In general, there are concerns about bias and factual error in AI systems. Jain said financial markets are not invincible either.
Computer traders may even be motivated to sabotage their competitors’ systems with inaccurate information or fake orders to gain some speed advantage, Jain said.
Also, publicly traded companies trying to cater to high-frequency traders have a trick of releasing bad news to make it harder for AI-powered computers to read, he said.
