If You Read Blogs, You Could Have Shorted Apple Early

Apple today announced on Hot News - their stealth blog - that the Leopard operating system is going to be late because they had to pull developers off to finish the iPhone. The stock is already down 3% in after hours and it could get hit harder tomorrow.

However, if you were a trader and you were reading Apple blogs today, you would have seen the tea leaves at 1PM EST, way before the official after-market post. A report from AppleInsider posted in the early afternoon reported that there were a rash of bugs in the latest Leopard beta. Naturally, this would cast doubt on the official company word - that the product would be completed in time for the summer as originally promised.

The stock then was at $92.05. The lesson - read good blogs that break news and then make your own decisions. These sites can be wrong just as much as they are right. Still, some have averages that are rather amazing. (Disclosure: Apple competes with Microsoft, an Edelman client.)

Comments

[MG Siegler]

That's a good thought Steve and a practice I occasionally partake in. Though admittedly I was kind of burned on Netflix a couple months back when I read about their streaming service before release - which I thought sounded like the greatest thing ever - bought up the stock - then it turns out the service was not exactly what it was built up as and the stock took a dive.

But yeah, would have been good to sell today on Apple, then buy up again at the low point tomorrow because you know those shares are going past $100 when iPhone hits.

[Darren Kelly, VP Research Strategy, Collective Intellect, Inc]

Steve, I completely agree with your point. In fact, we've been making the same point for a couple of years. The BIG problem is that Apple gets over 7000 posting per day from its own Apple.com threads, and thousands of other postings from the general blogosphere. There are honestly THOUSANDS of "false positives" about Apple products during any given week. Knowing which postings are credible and relevant is the trick. This is the problem we at Collective Intellect have been focused on for the past couple of years. The good news is that IS possible to filter this avalanche of information - you just need a good filtering technology layer.