Facebook had a flash-crash of sorts after it released its second quarter earnings on Wednesday.
Shares of Facebook plummeted about 4.6% lower after the market close on Wednesday, before recovering all of those losses and trading higher just ten minutes later. It’s not completely clear why the stock dropped and rebounded, though the crash came immediately after earnings data was reported incorrectly, and the stock surged once the confusion was cleared up.
Publicly traded companies are required to release earnings data each quarter by the SEC. Some firms summarize it on a wire service almost instantly. Investors write algorithms which trade on these summarized wire stories automatically.
After Facebook’s earnings data was released, Bloomberg released a wire service summary of the earnings results and the data was immediately traded on.
The summary Bloomberg initially released said Facebook missed its earnings expectations, and a series of trades were made on this data, at about 4:06 pm. A series of trades were priced at $US158 a share, about 4.6% lower than Wednesday’s close. The drop in price erased about $US22 billion in value from the company in mere moments.
The company later issued a correction. Ten minutes after that drop, after the mistake was fixed and correct wire service data was released, the stock had regained its initial losses.
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.” Bloomberg declined to comment for this story. The stock was up around 3% Thursday 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 wasn’t because of an earnings miss.
The rapid stock move highlights the impact of modern-day algorithmic trading. Publishers often have to correct headlines or details from a story, but the speed with which that information is consumed and traded on now means that an erroneous headline or tweet can move a market. Traders’ models are set to read data and act on it as quickly as possible, as mere fractions of a second can change whether a trader catches a stock before it moves due to earnings data.