UAL falls victim to GIGO processing at hyper-speed

Interesting piece in the WSJ today about “the computer glitch that cratered UAL’s stock yesterday“.  Apparently, this was a case of GIGO processing at hyper speed:

“…blame spread to the computers that robotically troll the Web for news stories and execute stock trades automatically.

An old article about UAL’s 2002 bankruptcy-court filing resurfaced Monday as an apparently fresh report on Google’s news service. Stock in the parent company of United Airlines quickly dropped to $3 a share from nearly $12.50 before the Nasdaq Stock Market halted trading and UAL issued a statement denying any fresh Chapter 11 filing.”

The evolving story on the glitch involves web-crawling, search engine optimization (SEO), syndication and complex event processing (CEP):

Web Crawling

“Google traces the appearance of the 2002 article in its search engine to a process that began late last Saturday night. At 10:36 p.m. PDT, Google’s “crawler” — the technology that finds Web pages — discovered a new link on the Web site of Tribune’s South Florida Sun-Sentinel newspaper in a section called “Popular Stories: Business.” The article — which didn’t carry a date but was published by the Chicago Tribune in December 2002 — hadn’t appeared there when Google’s crawler last visited the page at 10:17 p.m., the company said.”

Search Engine Optimization

“Amid serious storms in Florida and on the East Coast, Web surfers checking for news about travel delays may have stumbled onto the old UAL story by mistake, and a small number of fresh hits may have been enough to drive it onto the list. A Tribune spokesman declined to say how many hits the article received but said there was no indication of fraud.”

Syndication

“From the Sun-Sentinel site, the article became available through Google News service, accessible if a user searched for keywords like “United Airlines.” The article didn’t appear in any of the headlines on Google News’s home page, but it was picked up and sent via email to people who had created a custom Google News alert about UAL or related topics.

The stock market opened Monday with no drop in UAL shares, but the UAL story began circulating widely via a posting by research firm Income Securities Advisors Inc. that was made available to users of Bloomberg L.P., the financial-news service widely watched on Wall Street. Shortly after a headline from the outdated report flashed across Bloomberg screens at about 10:45 a.m., UAL shares began a precipitous drop. Over the next 15 minutes, before Nasdaq halted trading, they dropped as low as $3.”

Complex Event Processing | Algorithmic Trading

“The damage was exacerbated by the growing use on Wall Street of automated programs that trigger stock trades without any human interaction. The so-called algorithmic trading mechanisms, which buy and sell stocks based on news headlines and earnings data, were responsible for roughly a quarter of New York Stock Exchange trades in the last week of August.

Investors said simple human scrutiny would have indicated the UAL story was old, but computerized trading systems don’t make such determinations.

“A trader can pull back before proceeding, but some of these less sophisticated [automated trading systems] can’t do that,” said Bernie McSherry, a senior vice president with New York institutional brokerage Cuttone & Co.”

At the end of trading, UAL’s stock had regained much of its value, but the loss to traders and market value was still significant:

“UAL’s stock price ended Tuesday’s session at $10.60, down 2.8% on the day and nearly 13% off Monday’s open.”

As regular readers know, I’m a big proponent of automation, syndication and event processing — casting a wide information net to discover opportunities and threats, and reacting accordingly.  So, I’m not posting this to create FUD — I hate FUD. 

Instead, I am posting this to remind folks that shiny technology alone doesn’t guarantee better decisions.  Just faster decisions. 

Good decisions require good data, and for that tried, true and boring concepts like data quality and source checking remain imperative.  Oh, and when something seems too good or bad to be true, add a little human scrutiny.