The Flash Crash: When Robots Broke Wall Street

May 6, 2010 — The Dow Jones plunged 1,000 points in 36 minutes, erasing $1 trillion in market value. Then recovered. A glimpse into the terrifying future of algorithmic trading.

-998.5 pts Dow Drop
$1 Trillion Vanished

Key Takeaways

  • Dow Jones crashed 998.5 points in 36 minutes — biggest intraday drop ever
  • Blue-chip stocks like Procter & Gamble traded at 1 CENT
  • $1 trillion in market value evaporated in minutes
  • Caused by algorithmic trading algorithms feeding on each other
  • A single $4.1 billion trade triggered the cascade
01

2:32 PM — The Day the Market Went Insane

It was a Thursday afternoon. Traders were already nervous. Greece was melting down. European debt crisis headlines dominated the news. The Dow was down about 300 points — a bad day, but nothing unusual.

Then, at exactly 2:32 PM Eastern Time, something broke.

Traders across Wall Street stared at their screens in disbelief. The Dow Jones Industrial Average, the most watched stock market index in the world, began falling. Not just falling — plummeting like a stone thrown off a cliff.

"I've been trading for 25 years. I've never seen anything like it. We all thought the world was ending."

— NYSE Floor Trader

In the next 5 minutes, the Dow dropped 600 points. Then 700. Then 800. At 2:47 PM, it hit the bottom — down 998.5 points from the day's open. Nearly 1,000 points in 36 minutes.

That's a 9% drop. In half an hour. In the most liquid, most sophisticated market on Earth.

02

The Twilight Zone: Stocks at Impossible Prices

The numbers on trading screens stopped making sense. Reality itself seemed to glitch.

Procter & Gamble, one of the most stable companies in America — maker of Tide, Gillette, and Pampers — crashed from $62 to $39.37 in minutes. A 37% drop in a company that sells soap and toothpaste.

But that wasn't even the craziest part.

~$62 $0.01! ~$60 ACCENTURE (ACN) 2:40 PM 2:47 PM 3:00 PM

The Penny Stock Nightmare

Accenture, a $30 billion consulting company, traded at ONE PENNY. Imagine buying a Fortune 500 company for the price of a gumball. For a few terrifying minutes, you could.

Some stocks went to zero. Others exploded upward — Apple briefly traded at $100,000 per share. Sotheby's, the auction house, spiked to $99,999.99.

The market had entered the twilight zone.

Accenture

$40 → $0.01
-99.97%

P&G

$62 → $39.37
-36.5%

Sotheby's

$33 → $99,999
+303,027%

Apple

Brief spike to
$100,000/share

03

The Recovery: As Fast As It Fell

At 2:47 PM, the Dow hit its low point: down 998.5 points, or about 9.2%.

Then, just as mysteriously as it crashed, the market roared back.

By 3:07 PM — just 20 minutes later — the Dow had recovered 600 of those points. By the closing bell at 4:00 PM, it was down "only" 347 points. Still a terrible day, but nothing compared to the abyss traders had stared into.

-998.5 pts Flash Crash Low 2:47 PM
20 Minutes
+600 pts Recovery 3:07 PM

Over 20,000 trades were later cancelled — deemed "clearly erroneous" by the exchanges. If you managed to buy Accenture at $0.01, sorry — that trade never counted.

But the damage was done. Trust in the market had been shattered. And everyone had one question:

What the hell just happened?

04

The $4.1 Billion Domino

Investigators spent months piecing together the puzzle. What they found was terrifying — and absurd.

The crash was triggered by a single trade. A firm called Waddell & Reed, a mutual fund company in Kansas City, wanted to hedge their portfolio. They used an algorithm to sell $4.1 billion worth of S&P 500 E-mini futures contracts.

$4.1 billion sounds like a lot. But in a market that trades trillions per day, it shouldn't have mattered. It was like dropping a pebble in the ocean.

But this pebble created a tsunami.

"The algorithm was programmed to sell at any price, as fast as possible. It didn't care about market conditions. It just kept selling."

— SEC Flash Crash Report
Waddell & Reed HFT Algos Market Makers The Algorithmic Domino Effect

The Chain Reaction

One algorithm's aggressive selling triggered other algorithms. Those triggered more. Market makers pulled out. Liquidity evaporated. Prices went haywire.

05

The Robots Were Trading With Themselves

Here's what made the Flash Crash different from any market crash in history: It wasn't caused by humans panicking. It was caused by algorithms.

By 2010, high-frequency trading (HFT) firms dominated the market. These weren't traders staring at screens — they were computers executing millions of trades per second, looking for tiny price differences to exploit.

When Waddell & Reed's algorithm started dumping futures, the HFT algorithms detected the selling pressure and... started selling too.

Algorithm A

"Someone's selling aggressively. I should sell before prices drop more."

Algorithm B

"Algorithm A is selling! This must be bad. Selling everything NOW."

Algorithm C

"Mass selling detected. Exit all positions immediately."

Result

"Hot potato" trading. Algos passing contracts at lower and lower prices. No one actually wanted to hold anything."

Investigators found that during the crash, HFT firms were trading contracts back and forth between themselves — a game of "hot potato" where no one wanted to be left holding the position.

In just 14 seconds, HFT firms traded 27,000 contracts. That's almost 2,000 trades per second. Between computers. With no human oversight.

"The machines were trading with each other at speeds no human could comprehend. We'd built a market where humans were just spectators."

— Market Structure Expert
06

The Liquidity Mirage

Before the Flash Crash, everyone believed modern markets were more liquid than ever. Billions of shares traded daily. Spreads were tight. Execution was instant.

The Flash Crash revealed this was an illusion.

When stress hit, the HFT firms that provided most of the "liquidity" simply... vanished. They turned off their algorithms. Pulled their bids. Left the market.

The Ghost Liquidity

HFT firms provide liquidity when times are good. But when you actually need it? They disappear in milliseconds — faster than any human can react.

This is why Accenture could trade at $0.01. There were no buyers. The order book was empty. When someone put in a market sell order, it just kept falling until it hit whatever bid was left — including "stub quotes" at absurd prices that were never meant to execute.

The market had become a Potemkin village of liquidity — looking solid on the surface, but hollow underneath.

07

The Scapegoat: Navinder Singh Sarao

For years, the "official" explanation blamed Waddell & Reed's algorithm. But in 2015, authorities arrested someone else entirely.

Navinder Singh Sarao was a 36-year-old trader working from his parents' house in a suburb of London. He traded in his bedroom, using a basic computer setup.

The Department of Justice claimed Sarao used "spoofing" — placing fake orders to manipulate prices — and that his actions contributed to the Flash Crash.

Location

His parents' house in Hounslow, UK

Setup

Basic computer, custom software

Profits

$40 million over 5 years

Sentence

Home detention (no prison)

But many experts questioned whether one guy in his bedroom could really crash the entire U.S. stock market. Sarao's spoofing was happening all morning — the crash didn't start until 2:32 PM.

Was he a villain or a scapegoat? The truth is likely somewhere in between. He was one factor among many in a system that was already fragile.

"Blaming Sarao for the Flash Crash is like blaming a butterfly for a hurricane. Was he doing something wrong? Maybe. Did he cause a trillion-dollar crash? That's a stretch."

— Financial Journalist
08

The Aftermath: Did We Learn Anything?

After the Flash Crash, regulators scrambled to prevent it from happening again. They implemented:

1

Circuit Breakers

Trading halts when individual stocks move too fast. Pause to let humans catch up with machines.

2

Limit Up-Limit Down

Stocks can't trade outside a price band. Prevents penny and $100K trades.

3

Better Monitoring

Consolidated Audit Trail to track every order across all exchanges.

4

Spoofing Laws

Made fake orders explicitly illegal. (They were already fraud, but now extra illegal.)

But here's the uncomfortable truth: Flash crashes keep happening.

August 2015: The Dow dropped 1,000 points at the open. February 2018: 1,600 point intraday drop. The algorithms are faster, more complex, and more interconnected than ever.

We've put guardrails on a highway where the cars drive themselves at 1,000 mph. Is that enough?

09

What Traders Should Learn

The Flash Crash wasn't just a technical glitch. It revealed fundamental truths about modern markets:

Liquidity Is a Lie

The bid you see might not be there when you need it. In a crisis, everyone runs for the exit at once.

Market Orders Are Dangerous

In a flash crash, a market order can fill at any price. Use limit orders. Always.

You're Trading Against Robots

HFT firms will always be faster. Don't compete on speed. Compete on insight and patience.

Stay Calm in Chaos

Those who bought Accenture at $0.01 made a fortune (before the trades were cancelled). Panic selling is never the answer.

10

The Machines Are Watching

The Flash Crash of 2010 was a warning shot. It showed us that we've built financial markets we don't fully understand or control.

Algorithms now execute over 70% of all stock trades. They make decisions in microseconds — far faster than any human brain can process. They're programmed by humans, but their interactions create emergent behavior no one predicted.

The market didn't crash because of a financial crisis. It didn't crash because a company went bankrupt. It crashed because lines of code, written by different people, interacted in ways no one expected.

And it recovered because those same algorithms detected the panic was irrational and started buying.

"May 6, 2010 was the day we learned that the machines run the markets. We're just guests in their casino now."

— Wall Street Veteran

The Flash Crash taught us that modern markets are faster, more connected, and more fragile than we ever imagined. In a world of algorithmic trading, the biggest risk isn't a company failing — it's a feedback loop between robots that turns a ripple into a tidal wave. Trade accordingly.

⏱️ Flash Crash Timeline

2:32 PM

The Trigger

Waddell & Reed's algorithm begins aggressive selling of E-mini futures.

2:41 PM

Hot Potato

HFT firms pass contracts back and forth. 27,000 trades in 14 seconds.

2:45 PM

CME Pause

Chicago Mercantile Exchange halts E-mini trading for 5 seconds.

2:47 PM

The Bottom

Dow hits low: -998.5 points. Accenture at $0.01. Total chaos.

3:00 PM

Recovery Begins

Algorithms detect oversold conditions. Buying resumes.

4:00 PM

Close

Dow ends down 347 points. 20,000+ trades cancelled.

Frequently Asked Questions

On October 19, 1987, the Dow dropped 22.6% in one day. Causes included: computerized portfolio insurance (automatic selling), overvaluation after 5-year bull run, rising interest rates, trade deficit concerns, and herding behavior. This led to creation of circuit breakers and 'too big to fail' concerns.

Warning signs include: extreme valuations (high P/E ratios), yield curve inversions, credit spread widening, excessive leverage in the system, VIX complacency (too low for too long), euphoric retail participation, IPO frenzy, and 'this time is different' narratives. Crashes usually come after extended calm periods.

Protection strategies: (1) Maintain 10-20% cash reserves, (2) Buy put options as insurance (costs premium), (3) Diversify across uncorrelated assets, (4) Have trailing stop-losses, (5) Reduce leverage before uncertain periods, (6) Don't panic sell at bottoms - have predetermined rules, (7) Consider inverse ETFs for hedging.

Historically, buying during crashes has been very profitable for long-term investors. Every major crash (1987, 2008, 2020) was followed by new highs. However, timing the bottom is nearly impossible. Better approach: buy in tranches during crashes rather than trying to catch the exact bottom. Have a plan before the crash.

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