Facebook IPO – Smart Money Slips Up?

Posted on by David Wright

The VCs and Zuck’s employees got paid today. But not by me.

Here’s one skeptical take.

The Facebook IPO has priced at $38, at the high end of its revised range, representing a market cap of $108.6B, assuming exercise of vested options.

The price is about 26 times trailing revenues and 104 times earnings, which discounts 66.2% compound annual growth over the next 10 years.  In comparison, Google grew at a 42.4% CAGR in the 8 years after it hit the $4B revenue milestone.

As consumer Internet use shifts decisively toward mobile platforms, Facebook’s ability to monetize their position is constrained by the control that Apple and Google have over 3rd party Apps.

GM’s repudiation of its Facebook ads is also troubling, calling into question the efficacy of ads, even on the browser platform.

Here’s some general detail:

“I think that the market was not there for this many shares,” said Michael Pachter of Wedbush Securities. “They priced it right if the goal was for the stock to trade flat [um… so they priced it properly? -DW], but it appears that the addition of 50 million shares on Wednesday night caused a supply/demand imbalance, and the market appetite wasn’t sufficient to support the stock above issue price.”

Some analysts believe the offering was priced too high, maximizing the return for the company itself, but not leaving sufficient room for an upside in trading — or that first-day pop that many Internet debuts have experienced.

If my company IPO’d with a first day pop I’d be spitting nails furious. Not today, and good. So what happens when there isn’t a pop? Well, it might mean you priced it correctly. It might also mean you priced it too high and the Investment Banks mask the error by aggressively making a market to support the flippers (via).

“Stabilization is the bidding for and purchase of securities by an underwriter immediately after an offering for the purpose of preventing or retarding a fall in price. Stabilization is price manipulation, but regulators allow it within strict limits – notably that stabilization may not occur above the offer price. For legislators and market authorities, a false market is a price worth paying for an orderly market.

They’re buying up those shares to save face. The beneficiaries? The lieutenants who got paid:

Multi-million dollar mansions and $100,000 Porsches are flying off local shelves in the Palo Alto, Santa Clara and Menlo Park areas of California. And the charge of luxury living is being led by a group of young entrepreneurs and techies as well as investors and venture capitalists that have scored famously from Facebook’s Nasdaq debut.

More Angel investors, more startups to come.

Addendum: holy cow, the WSJ has an awesome graphic of who sold:

Back When Everything Was New

Posted on by David Wright

Here is a series of photos from 1962, 50 years ago (pretty similar to today I’d say). A similar photo essay from 50 years before that, 1912, would present a much bigger change. From 50 years before THAT, 1862, maybe not as much.

This was an econoblog meme a little while ago and Scott Sumner had the best explanation…

Many key products were first invented in the late 1800s or early 1900s (electric lights, home appliances, cars, airplanes, etc) and were widely adopted by about 1973.  No matter how rich people get, they really don’t need 10 washing machines.  One will usually do the job.  So as consumer demand became saturated for many of these products, we had to push the technological frontier in different directions.  And that has proved surprisingly difficult to do.

You can’t really make airplanes 10 times bigger than the 747, at least in a cost effective way.  We went to the moon in 1969, but still don’t have much better propulsion technology.  The Titanic was much bigger than earlier ships, but 1000 feet is long is long enough.  The new ships are wider, but no one is building 3000 foot liners.  Improvements in cars are now incremental.

There are physical limits to the mechanical innovations that transformed the world between the 1910s and the 1970s. And we hit them.

THAT’s what the great stagnation is to me. THAT’s why we’re in a debt crisis now. THAT’s why everyone is scratching their heads at the biggest IPO of 2012.

Turing Test as Trojan Horse

Posted on by David Wright

Bryan Caplan, I think, coined the “Ideological Turing Test”, which is a neat idea. Tyler Cowen likes it, too.

Put me and five random liberal social science Ph.D.s in a chat room.  Let liberal readers ask questions for an hour, then vote on who isn’t really a liberal.  Then put Krugman and five random libertarian social science Ph.D.s in a chat room.  Let libertarian readers ask questions for an hour, then vote on who isn’t really a libertarian.  Simple as that.

My challenge: Nail down the logistics, and I’ll happily bet money that I fool more voters than Krugman.  Indeed, I’ll happily bet that any libertarian with a Ph.D. from a top-10 social science program can fool more voters than Krugman.  We learn his worldview as part of the curriculum.  He learns ours in his spare time – if he chooses to spare it.

We learn from Psyblog, though, that:

Janis and King (1954) tested this by having some participants give a talk while two others listened. Then they swapped around and one of the passive listeners gave a talk to the other two on a different topic.

What emerged was that, on average, people were more convinced by the talk when they gave it themselves than when they merely heard it passively. This suggests that we really are persuaded more strongly when we make the argument ourselves, even if it isn’t in line with our own viewpoint.

There’s a powerful signalling story to all this, of course. He who more convincingly passes the ITT can say he withstood the powers of self-persuasion. He is RIGHT.

And ideologues everywhere are scrambling to seize the ITT high ground. Caplan’s inspiration is Paul Krugman, who once said this:

[I]f you ask a liberal or a saltwater economist, “What would somebody on the other side of this divide say here? What would their version of it be?” A liberal can do that. A liberal can talk coherently about what the conservative view is because people like me actually do listen. We don’t think it’s right, but we pay enough attention to see what the other person is trying to get at. The reverse is not true.

Eric Barker disagrees:

Who was best able to pretend to be the other?

The results were clear and consistent. Moderates and conservatives were most accurate in their predictions, whether they were pretending to be liberals or conservatives. Liberals were the least accurate, especially those who described themselves as “very liberal.”

The bottom line? The stakes are too high for anyone to actually undergo a real ITT.

One Last Pivot

Posted on by David Wright

The key question when trying to value Facebook’s stock is: can they find another business model that generates significantly more revenue per user without hurting the user experience?…

If they do that, the company is probably worth a lot more than the expected $100B IPO valuation. If they don’t, it’s probably worth a lot less.

That’s Chris Dixon.

I personally don’t like sponsored content in my feeds and Chris makes some good observations on those. GM isn’t convinced either.

My favorite test for a business’ viability is this: people only spend *real* money to make money. If your business isn’t better than your competitors at helping other people get rich, you don’t get rich.

I like Chris’ perspective, which is that Facebook is an incomplete product at the moment. And you can’t predict pivots.

Michael Bloomberg, Javascript Jockey

Posted on by David Wright

Here’s Jeff Atwood with some, perhaps needed, pushback on the whole “everyone should learn to code” thing. The final straw for him was Mayor Bloomberg’s recent tweet:

Jeff asks: if everyone needs to code, how would coding make the Mayor better at his job?

Most jobs don’t need coding today, that’s a fact. But here are some other arguments:

  • Substantially all productivity improvements in most industries are coming from coding.
  • There are people out there who would be excellent programmers today if they were exposed to programming at a young enough age.
  • The world needs more programmers solving programming problems.

My love affair with coding as a macro phenomenon isn’t about supporting today’s patters of production, it’s about supporting the rate of change of those patterns.

Michael Bloomberg, who owns a software company fercrissakes, should support this movement.

Excel Min If and Max If Functions

Posted on by David Wright

Unfortunately, the only way to do this is with array formulas, which are pretty intimidating beasts. Here is a simple sumif function:

=sum(if(((a1=b1:b5)),1,0))

Then hit ctrl+shift+enter (CSE: some call these CSE formulas). See here for more on array formulas.

Have a look at the attached file (“array_formulas“). It looks for matches between a1 and whatever’s in b. It sums the values from the matching rows but in the c column. Hard to explain in words, have a look at the attached.

What’s cool is that you can do this with an unlimited number of criteria and use max or min. Like this:

=max(if(((a1=b1:b5)),c1:c5,0))

=min(if(((a1=b1:b5)),c1:c5))

Note with min, you can’t set the FALSE condition of the If statement to 0 because 0 will always be the min!

Next version is to set the multiple criteria using * signs:

=max(if(((a1=b1:b5)*(a1=d1:d5)),c1:c5,0))

And can set or conditions using a + sign:

=max(if(((a1=b1:b5)+(a1=d1:d5)),c1:c5,0))

What these are really doing is giving you some database functionality in excel. If you work with datasets smaller than 50,000 rows or so the pain of putting something into a database isn’t worth the extra speed for searching. And excel’s function system is much more powerful than SQL for even moderately advanced analysis.

Excel gives you database query functionality with the pivot tables, but I find these a pain to work with and usually just build my own pivots with array formulas.

One big note of caution: array formulas are super duper resource hogs. Eventually you’ll bog your system down in endless calculations if you use them too much. Which I do all the time.

Knock, Knock

Posted on by David Wright

Here’s an interesting article about how the FBI came a-knockin’ on a company’s door one day.

Some things that I found interesting:

– having the FBI breathing down your neck is incredibly distracting. It’s no wonder companies in countries where arbirary law enforcement is the norm can’t get anything done. Serving your customers takes a complete back seat.
– If the FBI does come along and take your server, have a backup ready in case they never give it back. Prevents downtime!
– Wow, encryption works
– The fact that the FBI gave the server back a few days later, and went to some lengths to reinstall it, suggests that, perhaps, government employees actually want to do the right thing here. The culture of the civil service matters.
– The people who run this shop are clearly bible-thumping free speech fundamentalists, which is fine. The question is whether a lesser (more naiive?) ideologue might have gotten better treatment. Unlikely perhaps.

Dear Science Fiction Authors: You Were Right

Posted on by David Wright

Freddie is a disembodied creature, an animal that is more important as data than as meat or muscle. Though he’s been mentioned in thousands of web pages and dozens of trade industry articles, no one mentions where he was born or where the animal currently lives. He is, for all intents and purposes except for his own, genetic material that comes in the handy form of semen. His thousands of daughters will never smell him and his physical location doesn’t matter to anyone.

What is Freddie? The greatest sire of diary cows the world has ever seen.

While there are more than 8 million Holstein dairy cows in the United States, there is exactly one bull that has been scientifically calculated to be the very best in the land. He goes by the name of Badger-Bluff Fanny Freddie….

In January of 2009, before he had a single daughter producing milk, the United States Department of Agriculture took a look at his lineage and more than 50,000 markers on his genome and declared him the best bull in the land. And, three years and 346 milk- and data-providing daughters later, it turns out that they were right.

More here. It’s a big data story of course and they’re lucky to have great data and narrow predictive objectives:

Data-driven predictions are responsible for a massive transformation of America’s dairy cows. While other industries are just catching on to this whole “big data” thing, the animal sciences — and dairy breeding in particular — have been using large amounts of data since long before VanRaden was calculating the outsized genetic impact of the most sought-after bulls with a pencil and paper in the 1980s.

Dairy breeding is perfect for quantitative analysis. Pedigree records have been assiduously kept; relatively easy artificial insemination has helped centralized genetic information in a small number of key bulls since the 1960s; there are a relatively small and easily measurable number of traits — milk production, fat in the milk, protein in the milk, longevity, udder quality — that breeders want to optimize; each cow works for three or four years, which means that farmers invest thousands of dollars into each animal, so it’s worth it to get the best semen money can buy. The economics push breeders to use the genetics.

And on Freddie’s eventual fate:

It might seem that Badger-Bluff Fanny Freddie is the pinnacle of the Holstein bull. He’s been the top bull since the day his genetic markers showed up in the USDA database and his real-world performance has backed up his genome’s claims. But he’s far from the best bull that science can imagine…

He will be replaced very soon by the next top bull, as subject to the pressures of our economic system as the last version of the iPhone.

Love Thyself

Posted on by David Wright

Amazing article in the wsj (mercifully ungated) on a study about what happens when you talk about yourself:

Talking about ourselves—whether in a personal conversation or through social media sites like Facebook and Twitter—triggers the same sensation of pleasure in the brain as food or money, researchers reported Monday.

About 40% of everyday speech is devoted to telling others about what we feel or think. Now, through five brain imaging and behavioral experiments, Harvard University neuroscientists have uncovered the reason: It feels so rewarding, at the level of brain cells and synapses, that we can’t help sharing our thoughts.

“People were even willing to forgo money in order to talk about themselves,” Ms. Tamir said.

Isn’t that amazing? You can see why people say stupid things in interviews and the like: they’re so high on having someone listen to them that they mess up!

I’d love to see a study of people who read transcripts of themselves talking about themselves months later: I’d imagine they’d judge it harshly.