Get There Early, Adverse Selection, Don Johnson, and... Taleb
Connecting dots that never asked to be connected
I once wrote about the contenders for the greatest gambling scene, and I offered the boardroom scene from Margin Call as my favorite. For this post I am going to start in an adjacent place.
My favorite piece of culture about having an edge is from the final season of The Wire. It’s the scene where Mike kills Snoop1.
The TLDR is that Snoop is planning to kill Mike, but Mike figures it out. Snoop asks how Mike knew, and the answer is:
“You all taught me. Get there early.”
So, don’t show up to something where you’re at an information disadvantage.
If you do, you’re just hoping to get lucky.
I love “get there early” (GTE) as a maxim about preparation, and due diligence… and ultimately having the goods.
Let me offer a few examples from the podcast that are emblematic of this idea of GTE:
Mr. Doppy’s Twitter handle says that he is a “fine print reader extraordinaire” - this is a very strange flex… unless you’re an advantage player, in which case the exact rules and details will matter. If you want another example of how fine print can matter, here’s a writeup from Telemachus about exploiting sportsbook rules.
In the episode “Movers” we heard about a group of sports bettors, and one of their guys just drives around the country, looking for casinos that will take $20,000 on college basketball totals. Their probing is not limited to scraping a website. Also, when they do this they are not just attempting to GTE on the casino. It’s also GTE on their competitors. The other sports bettors.
Marc Cohodes would go to the warehouse of the company he was shorting, and dig through their dumpster.
By the time the Twitter merger rolled around, Chance had been following the key Delaware court for years. She had an amount of knowledge and context that could not be replaced with cramming.
It’s All Adverse Selection Nowadays
Another way to say that we should seek to GTE - we want to be the ones that have the goods - is that we’d like to avoid the business end of adverse selection.
Kris Abdelmessih writes the wonderful Moontower newsletter and he had a post a few weeks ago about adverse selection.
The examples that Kris uses are from the financial markets, but I will offer a prototypical example from the land market.
Imagine there’s some property listed for $1 million, and your fair value is $800,000. You think for a minute about the lowest price you could offer and still get a counter-offer. So you send an offer at $600,000.
The seller accepts it the same day.
You should be happy right?
Of course not. The person who already owns this thing, and knows a lot more about it than you do, just signed your offer and sent it back. What happened to your assumed edge in that situation?
Mark it zero.
Real estate folks have a very simple solution to this problem, which is to just re-trade the price prior to closing. Make up some excuse, any excuse. Tell the seller that the contract price won’t work, but some lower price will work. Try to walk the fine line between making the Seller believe that you could walk away, or, you could also close.
Actually, if you see that happen enough you might develop some intuition as to the Buyer’s real price, conditional on the way they re-trade. I mentioned in the Twitter merger episode that I didn’t think Elon Musk was very good at re-trading.
But adverse selection is everywhere. The guests of the podcast deal with it daily.
Although it occurred to me that perhaps the most interesting victim of adverse selection is a group we’ve never heard from - i.e. the people who run casinos.
Some readers/listeners may be familiar with the story of Don Johnson - once dubbed the Man Who Broke Atlantic City.
If we use the details of the story that have been most publicly shared, then Johnson won many millions of dollars from casinos using loss rebates2. He took advantage of casinos when they were most in need of business, and negotiated good terms at very table high limits.
I will offer a bit of context here and say that Johnson’s wins were probably in-part responsible for the shitcanning of one casino executive. Mark Giannantonio was ousted as CEO of Tropicana Atlantic City for a myriad of reasons, one of which was the beating they took from Johnson.
So to return to the issue of adverse selection, if you are running a casino, do you need to worry at all about who your players are?
Do you need to worry at all about the size of bets you take?
Do you need to worry about whether your marketing strategy is exploitable?
Of course you do.
Because casinos aren’t somehow immune to adverse selection. Actually, next time you’re in a casino try to count how many of their procedures exist to avoid being adversely selected.
Have you ever sat at a blackjack table and heard the dealer call out “checks play”? Why would the casino care about a player raising their bet if the casino has the house edge on their side? Shouldn’t they want to take as much as the players can bet?
Well, it depends.
And Now… Taleb
There is a sometimes forgotten section of Nassim Taleb’s book “The Black Swan” which discusses an idea that he calls the “ludic fallacy.” From the book:
What is the ludic fallacy? Ludic comes from ludus, Latin for games.
…the class of risks casinos encounter are very insignificant outside of the building, and their study not readily transferable. My idea is that gambling was sterilized and domesticated uncertainty. In the casino you know the rules, you can calculate the odds, and the type of uncertainty we encounter there, we will see later, is mild, belonging to Mediocristan. My prepared statement was this: “The casino is the only human venture I know where the probabilities are known, Gaussian (i.e., bell-curve), and almost computable.” You cannot expect the casino to pay out a million times your bet, or to change the rules abruptly on you during the game — there are never days in which “36 black” is designed to pop up 95 percent of the time.
I think that this chapter of Taleb’s book could have easily been a tweet that just said “Other distributions also exist!” - I’m not sure that we really needed the term “ludic fallacy” because if you read the chapter it’s pretty clear that he’s just creating a strawman in order to sound off on something that annoys him.
Taleb likes to talk about extreme events, and he doesn’t think that casino games offer the kind of “unknown unknowns” which abound in the real world. So instead of dealing with casino games as they actually exist - and the ways that you could study them to learn about uncertainty - he treats them as if they are only the rolling of the dice, or only the random selection of a card from a deck.
Basically Taleb only wants to talk about casino games as if people like Don Johnson don’t exist3. And also the things that casinos do to counter advantage players don’t exist. Things like: just steal the money.
Taleb says that the rules can’t change abruptly during a game… but of course they can.
Also, here’s another weird thing about Taleb’s section on the ludic fallacy. He actually starts it with a bit that undermines his entire point:
NNT (that is, me): Assume that a coin is fair, i.e., has an equal probability of coming up heads or tails when flipped. I flip it ninety-nine times and get heads each time. What are the odds of my getting tails on my next throw?
Dr. John: Trivial question. One half, of course, since you are assuming 50 percent odds for each and independence between draws.
NNT: What do you say, Tony?
Fat Tony: I’d say no more than 1 percent, of course.
NNT: Why so? I gave you the initial assumption of a fair coin, meaning that it was 50 percent either way.
Fat Tony: You are either full of crap or a pure sucker to buy that “50 percent” business. The coin gotta be loaded. It can’t be a fair game. (Translation: It is far more likely that your assumptions about the fairness are wrong than the coin delivering ninety-nine heads in ninety-nine throws.)
So Taleb starts with a simple probability example as a teaching tool, then moves on to claiming that simple probability examples are useless for understanding actual uncertainty. I think the fair treatment of Taleb’s ludic fallacy is to say: yes, if you strip out all of the real elements of casino games, then they do not reflect real uncertainty.
Lest you think that I am on thin ice here, crossing the greatest/most bombastic communicator of risk ideas that we have, here’s the kicker:
Taleb has basically admitted to this point. He wrote the foreword to Aaron Brown’s poker book and basically said: “Oh yeah when I wrote about the ludic fallacy I wasn’t really thinking about poker.”
I wanted to start this post with random thoughts about edge, and adverse selection. But people sometimes raise this ludic fallacy with me on Twitter, so I also wanted to cover it here. If you read the foreword to the Aaron Brown book, there isn’t much left of the ludic fallacy.
Like I said, it’s all adverse selection nowadays.
Apologies if you’re just getting the time to watch this (20 year old) series, and now I’ve spoiled it for you.
It’s probably fair to assume that there are many non-public details that we would need, in order to be certain as to exactly how Johnson won so much. He played with a group of the highest level advantage players - people that have been much less public about advantages they employ.
If you think that I’m picking an extreme example to help my point, I will just say that there are APs doing some variant of what Johnson did in lots of casinos around the country. Also, the big example that Taleb brings in favor of his position is a magician / tiger attack incident. So my example had a large impact (Black Swan-ish perhaps), and is probably more representative of risks that casinos faces every day… and is also more representative of risks that everyone faces everyday.