Until recently, Netflix was seen as a high-growth company that might surprise people with "upside," so it didn't seem crazy for a video streaming business with a DVD rental-by-mail component to be valued so highly. From June 30, 2010, until June 30 of this year, revenues rose 1.6x, but the share price of the company rose 2.4x. People were buoyant about the company's fortunes. After sleeping on Netflix in late 2009 and 2010, investors were eager for shares.

Earlier this month, Netflix raised prices on their DVD plans causing a surprising amount of outrage. Then, yesterday, the company beat Wall Street's expectations for their earnings per share, but ended up seeing its stock pilloried, falling 10 percent in after-hours trading. Why? They slightly missed Wall Street's revenue expectations, and guided analysts a little lower for the third quarter. Suddenly, the Netflix story of a high-growth company didn't quite work, and a new one would have to be constructed.

I've always marveled at how analysts justify the price of a (tech) stock. First, you look at its current price and come up with reasons why it's around the price that it is but a little over or undervalued. Second, you come up with a model that can sorta generate the company's earnings per share. Finally, you take whatever your spreadsheet tells you the company can earn and assign a multiplier to it of anywhere from 10 to 60 or even more. That's the price-to-earnings ratio that you think the stock deserves, based on any number of factors like its management or potential for growth that's not priced in or whatever else. That gives you a target price for the stock, which then shapes investor sentiment, which helps drive the price.

And thus people can justify Amazon's 93:1 price-to-earnings ratio versus Google's 23:1 P/E to IBM's 15:1 to eBay's 26:1 to Apple's 16:1 to Netflix's 73:1 with hard numbers. The spread between these numbers is interesting in and of itself. But what's long been more interesting to me is how narrative Wall Street really is. Analysts tell and are seduced by stories and personalities and hunches, which they translate into the strange language of Excel in the boxes of their spreadsheets.