Net Net: Promoting innovation and managing change
Net Net: Promoting innovation and managing change

The Warren Buffett And Anne Hathaway Trade

Anne Hathaway and Warren Buffett
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Anne Hathaway and Warren Buffett have recently been linked in the media—though not romantically, thank god.

No, this linkage is purely statistical.

Dan Mirvish over at Huffington Post spotted the following unusual data blip: Whenever Anne Hathaway's name appeared with any regularity in news stories, Berkshire Hathaway A shares rose in value.

Mirvish's article is clever—and the genius/disturbing movie poster photoshop work   contained therein is definitely worth the jump.

Mirvish humorously submits the following mini-table of rather official looking data for our consideration:

Oct. 3, 2008—Rachel Getting Married opens: BRK.A up .44%

Jan. 5, 2009—Bride Wars opens: BRK.A up 2.61%

Feb. 8, 2010—Valentine's Day opens: BRK.A up 1.01%

March 5, 2010—Alice in Wonderland opens: BRK.A up .74%

Nov. 24, 2010—Love and Other Drugs opens: BRK.A up 1.62%

Nov. 29, 2010—Anne announced as co-host of the Oscars: BRK.A up .25%

Writing for the FT's Alphaville, Tracy Alloway picks up the story—adding both additional comic relief and raising a relevant point: Namely, that the advent of machine readable data creates the opportunity to detect such correlations: Visible and invisible—legitimate and spurious.

Alloway points to the following, from the Financial Times this January:

"So-called 'machine readable news' services, such as the new Thomson Reuters product, have grown up in parallel with the emergence of high-frequency and algorithmic trading, which depend on lightning-fast delivery of data and news to traders specialising in such computer-driven trading strategies. Machine readable news systems use computers to "scrub" thousands of breaking news stories, prioritising their relevance for traders—often based on simple key words—and delivering them in a special feed. This provides traders with "signals" that are used to drive their strategies."

But what are the pitfalls of publishing a panoply of parameterized data?

In the Anne/Berkshire Hathaway test case, it's pretty clear that the 'correlation' is more—or less—than serendipitous: It's driven purely by chance, rather than by any fundamental underlying relationship among the data.

Unless, of course, the tin foil hat types are right—and the illuminati and the WTO really do run Hollywood and Wall Street.

Which may make you wonder: In the absence of brain-melting conspiracy, does casting such a wide net lead analysts to hyperventilate over 100 of every 10 genuine phenomena?


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