Automated trading algorithms accidentally wiped $22Bn off Facebooks share price
Algorithmic traders use automation to their advantage to try to beat the market, but when data goes bad the shockwaves can reverberate across Wall Street and the global markets
Key takeaways
- The crash came immediately after Bloomberg reported the earnings data incorrectly, and once the mistake was cleared up the stock surged – and there’s the smoking gun.
- Bloomberg then issued a correction ten minutes later with the right data and the stock bounced back.
- A large drop in stock price isn't abnormal during earnings season, and a big miss on earnings can send a stock plummeting.
Cite or link to this article
Griffin, M. (2017) 'Automated trading algorithms accidentally wiped $22Bn off Facebooks share price', 311 Institute, 27 July. Available at: https://www.311institute.com/automated-trading-algorithms-accidentally-wiped-22bn-off-facebooks-share-price/ (Accessed: 1 October 2026).
Facebook’s stock suffered a dramatic flash crash yesterday seconds after it released its second quarter earnings, and shares plunged 4.6%, wiping out over $22 Billion of value, before eventually recovering just ten minutes later, and while no one is certain why the stock crashed and rebounded so quickly, or dramatically, they believe that automation and algorithmic trading might be to blame.
The crash came immediately after Bloomberg reported the earnings data incorrectly, and once the mistake was cleared up the stock surged – and there’s the smoking gun.
Publicly traded companies are required to release earnings data each quarter by the SEC, and some firms, like Facebook, summarise it on a wire service almost instantly, but over the past decade investors, increasingly known as Quantitative traders, or Quants, have been increasingly writing algorithmic trading programs, and even creating companies, such as Aidyia, that are completely automated and run without anyone in control, that trade based on these summarised wire stories automatically, and that’s what many people believe happened here.
In this case after Facebook's earnings data was released Bloomberg released a wire service summary of the earnings results and the data was immediately traded on, but the summary Bloomberg initially released said Facebook missed its earnings expectations, and at 4.06pm a series of trades, priced at $158, were executed automatically. Bloomberg then issued a correction ten minutes later with the right data and the stock bounced back.
Coincidence? Probably not.
The headline "CORRECT: Facebook 2Q Revenue Beats Estimates" ran at 4:14 pm on Bloomberg's wires and had the note "This story was produced with the assistance of Bloomberg Automation."
The stock was up around 3% this afternoon.
A large drop in stock price isn't abnormal during earnings season, and a big miss on earnings can send a stock plummeting. In addition, Facebook is a heavily traded stock with a certain amount of volatility, but Facebook recorded a beat across the board in earnings per share, revenue, and user growth, so its initial drop was in no way as the result of a simple earnings miss.
The rapid stock move though highlights the benefits, but also the dangers that automated trading can have on a stock, and it raises wider questions – if one bad story can wipe out $22 Billion what could two bad stories do? Or three? Then, going one step further what if one or more of the wires gets hacked – the impact could be severe, and the returns, for criminals at least could make this one "correction" look like chump change.
FAQ
Why does this matter?
Algorithmic traders use automation to their advantage to try to beat the market, but when data goes bad the shockwaves can reverberate across Wall Street and the global markets

About the author
Matthew Griffin Founder, 311 Institute
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."
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Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 15-time best selling author of the "Codex of the Future" series, Matthew is the Founder and Futurist in Chief of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.
An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity program, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.
As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.
Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.
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Source: first published by the 311 Institute on 27 July 2017. Cite as: Griffin, M. (2017). Automated trading algorithms accidentally wiped $22Bn off Facebooks share price. 311 Institute. https://www.311institute.com/automated-trading-algorithms-accidentally-wiped-22bn-off-facebooks-share-price/
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