I love this talk of "analysts". Did the "analysts" miss that Google just bought a struggling 10B+ Motorola? Do they expect it to be some magic unicorn that can turn Motorolas losses into Googles profits in a single quarter?
38 separate analysts, high estimate was $13, low estimate was $9.92. Average was $10.65, actual numbers were $9.03, so below even the most pessimistic analyst. That usually means the publicly available info just wasn't accurate, that something happened privately that only Google knew about.
Usually companies avoid this kind of thing by giving some mid-quarter update so that they can mitigate some of the damage.
Google actually provides no EPS guidance at all though, which also caused problems with a big miss in January 2012. Analysts like to have something to work off of.
Which should theoretically let you "put your money where your mouth is", since if analysts are systematically wrong, and the prices move in response to analysts...
Although I think most serious investors either ignore analysts or know to adjust for their biases. Some of the real victims are lazy academics, as the paper discusses.
Actuarial work, bioinformatics, social science. These are data-driven cultures. They actually require scientifically valid and methodologically sound data to make a claim.
Programming, on the other hand, is dominated by fashion. Language wars, methodology wars, business bullshit, buzzword chasing. Programming is not data-driven AT ALL! When was the last time a computer scientist actually did some SCIENCE? When was the last time a programmer actually ran a double blind study?
99% of programming is not data-driven whatsoever. The sweeping decisions in programming are made by corporate big wigs operating on their intuition, or are design choice (extremely subjective!) made by "architects" who, for instance, created UNIX.
Were the people who created Python, Ruby, Java, C, etc DATA-DRIVEN? What studies did they use to decide that so-and-so feature should be like this and not like this?
Programming is mostly a craft and has essentially nothing to do with being data-driven. Doing A-B tests does not mean your culture is data driven when A-B tests are like 0.1% of everything you do. And most A-B tests are methodologically unsound anyway and would be shamed out of any real social science department.
Economics, on the other hand, is an actual science with actual data that performs actual methodologically sound studies using advanced statistics. Practicing economists have to use actual valid data procured from real studies to have careers. Programmers mostly twiddle their bits around until something works. That IS NOT being data driven.
One of the most maligned professions when it comes to forecasts is meteorology. Nate Silver does and excellent job here, shedding some light on the challenges and triumphs of predicting the weather.[1]
Software engineering can involve difficult models about different scaling scenarios. Civil engineering might involve unexpected surprises about how standing waves emerge in bridge design. Financial analysis involves a forecast of the total revenue stream the company will generate between now and the end of time, and a guess about what other market players will predict about the future a quarter from now, since the stock price, too, can affect its income.
Take P/E ratios for example. Should you look at them as a sanity check, or think of them as a broad measure of the market's beliefs about the issue's future growth potential?
Regardless of where you stand, it is patently absurd to state that financial analysis is not data driven, and the decision making does not reward empirically successful results. Whether you recommend your fund bets with or against the market you get less of a say next time when you have less money left to bet, or decrease your assets under management by losing your clients' money.
Sometimes I sense a lot of derision from some folks towards "analysts" on these posts. A good analyst has a lot of public data and history to go along with their own sleuthing and detecting (talking to larger customers, suppliers, partners etc) where they should arrive at good estimates. Lord knows they get paid pretty well to be good at it. So if this was the cause of the big shortfall and all the analysts missed it then it is a poor job they're doing. I just don't think we should deride analysts and or let them off the hook based on the idea that there isn't a discipline here that can be followed.
Something like 9/10 funds under perform the market as a whole, right? Analysts are almost all liars marketing themselves, I don't think they need a 'break'.
There's a lot of derision because the profession of stock analyst is about equal to Snake Oil Salesman.
I think you just catalogued the definition of the bias that exists here as being based upon sweeping generalizations and ignorance:
"Something like 9/10 funds under perform the market as a whole, right?" - What does that mean? That 9 out of 10 mutual funds return less than the average improvement in the Dow? That means that 9 out of 10 funds would be weighting in the bottom 50% of all stocks?
"Analysts are almost all liars marketing themselves, I don't think they need a 'break'."
- When has it ever worked out for someone to say "All or nearly all people are X" when you're talking about a large group? It reflects very poorly on the author whenever they make sweeping generalizations like this.
"the profession of stock analyst is about equal to Snake Oil Salesman"
- Which is really just a step above name calling in the schoolyard. And a stock analyst is very different from a fund analyst but I doubt that really matters to you.
I have often suspected that one of the things that drives PG was this generalization that programmers by their very nature don't understand how business works and therefore don't need a seat at the business table. It's always better to be breaking down stereotypes rather than playing into them.
Ok, name a dependable public stock analyst, one who accurately portrays companies and makes good predictions. One of the better analysts I know of is Warren Buffet, but he doesn't share his analysis publicly, nor does he make his money based on publishing his analysis. He's also wrong sometimes, but his his right moves have far outweighed the wrong moves.
Most analysts are not Warren Buffet, or even close to it.
My favorite example: Costco. I love Costco, shop there all the time, the CEO is Mr. Fantastic as far as giant corporate CEOs are concerned in my book. Cashiers make too much money there, according to analysts. (Quoting from Wikipedia, but originally from the Houston Chronicle)
In an interview published in the Houston Chronicle on July 17, 2005, he told Steven Greenhouse that he was not interested in Wall Street analysts who took issue with his care for employees and customers rather than happier shareholders. Investors might want higher earnings, but Sinegal stated, “We want to build a company that will still be here 50 and 60 years from now." A favorite saying of his is “you have to take the shit with the sugar”. Investors who bought $10,000 of Costco stock in 1992 had $43,564 ten years later, a return of 354% (or 15.855% annually).
So it's not just "Computer Programmers" who are skeptical of stock analysts. I have a minor in Mathematics, I can compute earning ratios just as well as the analysts. I don't paint them with a broad brush because I know little about what they do, I paint them with a broad brush because I know A LOT about what they do.
And what they do is akin to "reading the bones", unless they have insider information, based on past performance. I mentioned Buffet before, but he only makes decisions when he's almost certain(and still stometimes wrong) he knows about he company he invests in. The talking head analysts I see have no such certainty requirement.
Totally agree, but Buffet's angle was that you play for the long haul, right? To me that's not what an "analyst" does. It what an "investor" does. Research research research.
He's not trying to figure out what exact earnings-per-share are going to be for companies every quarter. In fact, he was trying to discourage companies from giving earnings guidance.
Well, we know Buffet knows what a company's earnings are and has his private projections. One of the way he picks a stock is based on its earnings and potential earnings to price ratio, ie: is the stock "cheap". So, whether a stock is making $.32 or $.33 a quarter he doesn't say, but I bet he has his own estimates based on his research, but probably only on the companies he's interested in.
But yes, your point he isn't what we think of as a typical 'analyst' is correct.
er Warren Buffet learned from a guy called Benjamin Graham who's books are still in print and considered clasics the K&R or Kunth of investing if you will.
> What does that mean? That 9 out of 10 mutual funds return less than the average improvement in the Dow?
Yes, and this or something near it is a fact (http://business.time.com/2009/04/20/breaking-news-mutual-fun...). Although the underperformance typically comes from management fees, because we would expect mutual fund portfolios to average with the market. But then you have to pay the managers and analysts.
Generalizations are OK when they are true and backed up by scientific data.
The oft-cited statistic that mutual funds do not return as much as the dow ignore the concept of risk-adjusted returns. A mutual fund very well should return less than the dow if it takes upon lower risk. (However you might define risk, there are many definitions, volatility only being one.) The article presumes the goal of every investor is to maximize return vis a vis some arbitrary benchmark.
A stock-based mutual fund might actually be doing its job if it is simply not losing money when the dow surges since it's goal might be diversification via non-correlation by long-shorting the market.
There is of course some truth to the fact that mutual funds often do not earn their fees. But simply saying they cannot "beat the market" overlooks important questions about what those funds actually set out to do in the first place, and what their respective risk-taking philosophy was.
Of course, please perpetuate this nonsense, as it makes life easier for those of us who are investing relying upon it.
What's worse is that the phrase "missed analyst expectations" is common in the media yet nobody questions what that really means anymore. It's just generally perceived to be an instant negative.
>It's just generally perceived to be an instant negative.
It's an aggregated consensus of short term future earnings best guesses. It is assumed that these expectations are "priced in" to the stocks's price. When a company releases earnings and "misses", there is an adjustment to the share price.
Prediction is difficult, especially if it's about the future.
There will probably be at least a few analyses published in the next few days claiming this miss was "obvious" for various reason, all with the equal benefit of hindsight.
If you can consistently identify things which analysts and those who follow them are prone to overlook or fail to comprehend, there's all kinds of money to be made.
Personally, I've had some great successes putting money behind my own predictions.
No, they account for such things, and did, and despite that, Google "missed" the estimated earnings.
There is no bigger industry on the planet than the financial industry. That means a ton of money flowing around. There is far more sophistication there than you give it credit for.
