Another funny article by an amateur financial analyst. I recall reading another one previously and that was no less entertaining.
After having a quick laugh, I was going to move on to read something just as informative and believable like an article on the fantastic growth prospects for BlackBerry, but then I saw a number of comments to this article with the authors of those comments being upfront about the fact that this is unfamiliar territory for them.
Not wanting to let them think that they just read something with any actual value, I figured I should bang out some quick comments of my own.
Let me summarize what the article says: if you take Apple's quarterly guidance and multiply out all the numbers, and add some, and substract some, and divide some, you will get summary financials that are consistent with Apple's guidance. And then as long as you add some plugs that have apparently had a sizable range over the last several quarters (years? I can only take nonsense in small doses so I started to skim...) you will get numbers that are close to what Apple came up with internally. And not only that but, also, none of the analysts on Wall Street with Harvard MBAs and base salaries exceeding $300M have ever been able to crack this mysterious, arcane, unfathomable code!!!
Well, okay, but no...
(BTW, $300M means $300 thousand -- "M" is standard banking convention for thousands and "MM" is used for millions -- for any who might want to have jumped on me for suggesting that an Associate is making $300 million...)
The author of this article, which could have been submitted for someone's high-school business class and come back with a C+, fails to demonstrate any understanding whatsoever of how the real analysts actually perfom any analysis and even less understanding of how sophisticated traders make highly profitable trades.
There is no comparative advantage to be gained -- none -- from being able to take Apple's guidance (or any company's actually), throw it into the model, and update the pro formas.
That type of model requires such great sophistication that it's typically the sort of project that a summer intern might work on for a few days.
The simplicity of identifying the types of correlates, trends, etc. that seem to comprise the remainder of the "Never Before Revealed!!!" magic in this article is something that would keep the intern busy for the rest of the week.
OK, folks, here's the real world.
The real financial analysts actually use very sophisticated models that take the guidance and churns out the obvious financial forecast in a second or two to be used as a base-case scenario. This is something that could be done standing in front of a urinal during a bio break using nothing but the calculator app on my iPhone. I will concede that I'd probably need to turn my iPhone sideways to get the really super cool functionality in the calculator app...
That base-case forecast is then used in a variety of scenario and sensitivity analyses, which would typically include forecasts around the overall economy, interest rates, commodity prices, market share, supply-chain analysis, sell-through, product introductions, consumer demand, etc. etc.
From there, the analyst might use something as simple as boilerplate worst case and best case scenarios and in comparison to the company guidance come up with a near-term view of expected financial performance.
At the more sophisticated end of the spectrum, the analyst who might have a PhD in physics from MIT in addition to her Harvard MBA could perform a Monte Carlo analysis using 10,000 simulations to come up with a 97.5% CI forecast distribution... blah... blah... blah...
The point being that there is a considerable amount of sophistication, brain power, information gathering, and highly detailed forecasting that goes into real financial analysis.
Why? Well obviously because there is a real financial return from investing the time, effort, and cost into doing a thorough analysis.
That's because the point of doing the analysis is to try to develop insights into expected or probable performance where those insights exceed the information available to anyone else.
To make real money you need to have a more accurate, greater quality, more timely, more predictive, etc. etc. perspective on the current and future performance of a particular company within the context of the entire industry, all of the other relevant competitors in that industry, the global economy, etc. etc. In other words, you need to have a competitive advantage. If you're just using the same numbers that everyone else is, that doesn't really seem like an advantage...
If you look at this purely from a trading perspective, the objective isn't to get this all figured out as precisely as possible just before the company releases it's earnings so that you can run off and make a single trade. The goal is to make a continuous series of highly profitable trades based on the best available information on a minute-by-minute basis.
Estimates that vary by 16 to 18% each quarter are of no benefit when millions of dollars are made in trades that are executed in less than a second from the time that the trading model identifies a trade, with the trading position possibly being held for seconds, and being based on bid-ask margins of a small fraction of a penny.
The author seems to think that Wall Street financial analysts don't know what they're doing because their math doesn't result in numbers matching Apple's guidance as closely as his do. They don't because they actually reflect skills and knowledge beyond algebra.
Full disclosure: I am not currently a financial analyst, banker, trader, broker, dealer, or regulator. I am not an employee of Apple or any of its competitors. (I'm also not a "journalist" for The Onion...). However, I'm highly qualified to speak intelligently on this topic.