Artificial intelligence: use worries trading companies – 07/24/2023 – Market

Hedge funds and other computer-operated trading firms are increasingly concerned about the threat artificial intelligence poses to their profits after a false image of an explosion near the Pentagon sparked a brief sell-off in US stocks.

The S&P 500 index fell 0.3% in 30 minutes late last month after a viral tweet from a blue-sealed (confirmed) Twitter account showed an image of an explosion that never happened. The image, which quickly spread on social media and was soon revealed to be a fake, was likely AI-generated, according to investigative websites such as Bellingcat.

However, the incident underscores how AI-generated news and images can pose a huge problem for ultra-fast hedge funds and proprietary brokerages, which use complex algorithms to sift through vast amounts of news and social media for signals of market movement that they can quickly trade.

While their computers have become better able to filter out fake news and social media posts, executives at quantitative trading firms warn that machine-generated misinformation is a new frontier.

“AI certainly opens the door to all sorts of scams in the information environment, and that’s getting harder and harder to manage,” said Doug Greenig, founder of hedge fund Florin Court Capital, which bets on long-term trends in alternative markets rather than very short-term market movements.

Traders’ main concern is the rapidly advancing ability of AI to produce highly compelling images and stories in large numbers.

This could pose a host of pitfalls for proprietary trading firms and hedge funds that for years have invested heavily in algorithms to analyze critical information, assess a source’s language and sentiment, and use that data as a signal to trigger an automatic trade.

“We see quants facing two hurdles: false images that can mislead a journalist and false image reports that can mislead the algorithm itself,” said Peter Hafez, chief data scientist at software company RavenPack, which uses AI to read massive amounts of data for banks, hedge funds and other companies.

Powerful algorithms learn to recognize patterns and natural language in ways that mimic the human brain, but they might still struggle with genuine news about fake news — for example, a credible news provider reporting the fake Pentagon explosion — “so they could treat it as real facts and produce corresponding analysis,” added Hafez.

Yin Luo, head of quantitative research at data group Wolfe Research in New York, predicts “a cat-and-mouse game” between parties spreading false market-moving news and traders wanting to stay one step ahead.

For now, investors are likely to trust more reputable news and data sources, he said, adding that algorithms are already being developed to check various news sources to ensure information integrity.

A London-based quant fund executive said the rise of AI is likely to drive traders to use data companies that aggregate a wide range of sources into sentiment notes.

The sharp drop in the S&P may also have been exacerbated by investor concerns about issues looming over the market at the time, such as the US debt ceiling impasse and the effect of higher interest rates.

These factors have led to an increase in the popularity of strict stop-loss orders in trades, said Charles-Henry Monchau, chief investment officer at Syz Bank. These orders determine that in-demand positions are sold when prices reach a certain level, protecting investors from further losses.

“There’s a big tug of war going on between bulls and bears on an intraday basis, there’s a lot of uncertainty right now,” Monchau said. “Any unexplained sudden movement of macro numbers that [algoritmos] recognize, they will react to it and force some sales, accelerating the movement.”

Not all quantitative companies tend to face this problem, however. A quant strategist at a leading investment group said companies have checks and balances designed to ensure that “dangerous” data points don’t trigger forced selling by quants that push prices even lower, leading to further selling. Many quants trade market patterns rather than news or social media, and often look at trends over longer time periods, which causes them to ignore very short-term price movements.

Most computer-powered traders also place large numbers of small bets, minimizing possible losses from price movements caused by unreliable sources. “Bad data of any kind is generally a big concern, but it always has been,” said the strategist.

“In a way, we’re back in the past, when we didn’t have accurate and fast news,” said Kit Juckes, macrostrategist at Société Générale. “This is another step on the road to easy misinformation, made possible by technology and perhaps to some extent regulation and laziness. But yes, an important step.”

But those who have built their businesses by marrying technology and trading realize it’s going to be a long haul and that they’re in the firing line.

“Whether the false story was exploited by its creators for profit remains to be seen, but there will be more of these stories for a long time to come, and the perpetrators will try to extract value from the markets as a result,” said Mike Zigmont, head of trading at US-based Harvest Volatility Management.