On May 6, 2010, at 2:32 pm, stocks and stomachs dropped.
An unexpected sell-order of 75,000 contracts (worth $4.1 billion, according to an SEC report filed a few months later) led to a chain reaction of buys, sells, buybacks, sellbacks, and panicked exits.
In the span of about 10 minutes, in what became known as the “flash crash,” the Dow Jones Industrial Average (which today includes companies like Microsoft, Amazon, and Apple) fell by about 9%.
Normally that kind of drastic downfall would mean a tough day for then floor governor of the New York Stock Exchange Jay Woods. But he’d had the day off.
“I’ll never forget: My Motorola flip phone lit up with text messages saying, ‘What is going on?!’ It was my brother. And I’m like, ‘I have no idea what you’re talking about,” Woods told us, recalling the stock market slide, an event that occurred while he was cleaning a park during a Goldman Sachs-led community service project.
According to the SEC’s study, the large sale was an automated transaction, which triggered other computer programs known as high-frequency traders to rapidly buy and resell contracts, creating price drops and fear of “a cataclysmic event.”
Prices recovered by around 3 pm, and the market, in the end, closed only 3% down from the previous day. One example that sums up the up-and-down afternoon: Accenture fell from nearly $40 to one cent and recovered all of its value within a matter of seconds.
In other words, it was a volatile time for financial pros and probably not a bad day to be picking up litter in the park.
The speed of the crash, largely driven by an algorithm, led agencies like the SEC to enact new “circuit breakers” and mechanisms to halt a runaway market crash.
“On that day, we learned why,” Woods said. “because an algorithm went crazy, and sell programs continued to beget sell programs, and there was nothing to say, ‘Stop.’”
Finance and IT pros spoke with IT Brew about the possibilities of another flash crash and how technologies like AI, which also allow transactions at high frequencies, will test those brakes.
Flashback.
According to the SEC’s findings:
- At 2:32 pm, a “large fundamental trader,” unnamed in the 2010 SEC report, used an automated execution algorithm to sell 75,000 electronic futures contracts called E-minis, at 9% of its trading volume.
- Computer programs called high-frequency traders (HFTs), known for exchanging a large number of contracts but capping their inventory, quickly bought and then resold contracts to each other—generating a “hot potato” volume effect, the SEC said. In 14 seconds, HFTs traded over 27,000 contracts, which accounted for about 49% of the total trading volume, “while buying only about 200 additional contracts net.”
- From 2:41 pm through a little after 2:45 pm, prices of the E-mini had fallen by more than 5%.
- As volatility increased, many feared the occurrence of a cataclysmic event, leading some to withdraw completely from the markets. Even as prices recovered, stop losses—automatic exits triggered by price declines—led to additional drops in securities values.
- E-mini trading automatically paused at 2:45 pm, as prices moved beyond predefined thresholds. In that short period of time, “sell-side pressure in the E-mini was partly alleviated and buy-side interest increased.”
- By approximately 3:00 pm, “as market participants had time to react and verify the integrity of their data and systems,” most securities had reverted back to trading at prices reflecting true consensus values. “These same algorithms reversed and started repurchasing the assets because it was abnormally low pricing,” Irene Aldridge, CEO and founder of AbleBlox and AbleMarkets and a Cornell University visiting professor in finance and markets, told us.
Woods, a Goldman Sachs market-maker at the time, had to balance volatile stocks with strategic buying and selling. He wondered: Was it an error? Are these trades going to stand?
“It was just chaos that I got second-hand from people on the floor,” he said.
Over 20,000 trades representing 5.5 million shares were executed at prices more than 60% away from their 2:40 pm value, according to the report, and these trades were subsequently canceled by the exchanges.
Flash forward. In response to the crash, SEC staff worked with the exchanges and the Financial Industry Regulatory Authority (FINRA) to implement a circuit-breaker pilot program.
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Much like the shutdown mechanisms that keep your toaster from burning down your house, current circuit breakers for the New York Stock Exchange, updated officially in 2012, stop trading for 15 minutes when there’s a Level 1 (an S&P 500 index drop of 7%) or Level 2 (an S&P drop of 13%) event. A level 3 (an S&P drop of 20%) halts trading for the day.
The circuit breakers were implemented four times in March 2020 as the Covid-19 pandemic triggered selloffs. (Silicon Valley Bank’s failure in 2023 also resulted in a break, and trading briefly halted on some investment options abroad as countries responded to President Trump’s recent announcement of tariffs.)
“Pausing a market can be an effective way of providing time for market participants to reassess their strategies, for algorithms to reset their parameters, and for an orderly market to be reestablished,” the SEC wrote in its 2010 report.
In 1987, on a day known as “Black Monday,” the Dow Jones Industrial Average dropped by more than 22%—the biggest one-day decline in history.)
“We will never have another October 1987, down 22% in a day,” Woods said. “It can’t happen because once we go down 20% a day in the S&P 500, we shut down.”
Another mechanism known as Limit Up-Limit Down (LULD), implemented in 2012, prevents trades in National Market System (NMS) securities from occurring outside of specified price bands. Trading pauses for five minutes when a threshold is reached. (Think: GameStop.)
“The exchange technology has improved considerably, and exchanges are now able to catch these events as they go along,” Aldridge said.
Enter the agents. While financial industries may have a better handle on market volatility than they did in the past, the idea of catching unexpected aberrations from automated decision-making tech has emerged lately as many industries consider using AI agents.
Agentic AI—a tech that 36% of business managers expect to manage in the next two to five years, according to a recent Microsoft workforce study—automates processes on your behalf. Even agents’ biggest supporters want to place brakes on the tools, to prevent decisions based on hallucination or bias.
While the circuit breakers help a regulated field like finance, Peter Atanasoff, managing director of Scratch Marketing and Media (and a former consultant and corporate finance pro) sees ways that agents can set off hot potatoes in less regulated markets. Atanasoff referenced President Trump’s tariff announcements and the resulting uncertainty among industry leaders.
Imagine a world where, say, a retailer has decisions automated by AI agents, Atanasoff wondered. What if there’s a rule in the AI algorithm to order 12 months of inventory from China, and the script is trained to search a marketplace of vendors for the best price, he said. That could impact pricing as demand surges. “There are no mechanisms in those types of marketplaces for circuit breakers,” Atanasoff said.
Financial markets have seen extensive use of algorithmic trading systems over the past two decades, according to the Pacific-Basin Finance Journal Report from December 2023, “whereby computer programs generate orders and submit them to the stock exchanges without real-time human intervention.”
And that human intervention is an important check on algorithms that can go rogue. In a research paper posted in April 2025, AI startup Anthropic’s Alignment Science team demonstrated that simulated reasoning models frequently fail to disclose when they’ve used external help or taken shortcuts, even with features designed to show such actions.
And some market disruptions feature a more old-fashioned hack than algorithms gone awry. Just this April, regulators in Japan published an urgent warning about hundreds of millions of dollars worth of unauthorized trades being conducted on hacked brokerage accounts in the country.
When you add up all the possibility for error, and a crash lasting far longer than a flash, it’s enough to make a pro in any industry want to stop everything for much longer than a circuit break-sized 15 minutes, and take the day off.
Woods, however, sees the exchange industry as a resilient and responsive one.
“When you have an outlier event happen, and I don’t even want to think of what the next one could be, the rules will change to make sure that you can’t have that happen again,” Woods said.
This is one of the stories of our Quarter Century Project, which highlights the various ways industry has changed over the last 25 years. Check back each month for new pieces in this series and explore our timeline featuring the ongoing series.
