Saturday, July 25, 2020

"Poker and the Psychology of Uncertainty"

As noted in the intro to "The Bezos '70 percent rule' for decision-making":
There is a history of Decision Making Under Uncertainty as a distinct discipline going back to Pascal and his wager and Bernoulli and his Expected Utility vs Expected Value. It is now taught as the heart of Decision Theory and as a cousin of Game Theory....
And our headliner from Wired, June 23:

The game has plenty to teach about making decisions with the cards we’ve been dealt—on and off the table.
“You are going to be a gambler?”

That’s my grandmother Baba Anya speaking. My last living grandparent. I’ve come to Boston for a family visit, nearly bouncing with excitement at my new project, and she is not impressed. To call her lukewarm would be the understatement of the hour. She has a way of setting her jaw that makes it jut out like it’s about to slice through stone. The chiseled expression of a conquering hero atop a pedestaled horse. A conquering hero—or an angry general. I can feel the full brunt of grandmotherly disappointment gather on my shoulders. She has almost (though not quite) come to forgive me for not wanting kids after over a decade of my persistent explanations, but this—this is a new low. If you think you know the kind of disappointment a five-foot-some-odd 92-year-old is capable of, think again. She was a Soviet-era schoolteacher. She’s had more practice than an army drill sergeant.
She shakes her head.

“Masha,” she says—my Russian nickname. “Masha.” The word is laden with so much sadness, so much regret for the life I’m about to throw away. In a single word, she has managed to convey that I’m on the brink of ruin, about to make a decision so momentously bad that it is beyond comprehension. A Harvard education and this, this, is what I’m choosing to do?
“Masha,” she repeats. “You are going to be a gambler?”
My grandmother’s reaction may be extreme—nothing is quite as personal as your grandchildren heading out to ruin on your watch; you have to throw your body in the breach—but it is far from atypical. In the coming months, I’ll be accused of being responsible for a society-wide “sin slide” for advocating for poker as a teaching tool. I’ll be called a moral degenerate by strangers. A group of highly intelligent people at a retreat will tell me playing poker is all well and good, but how do I feel about encouraging people—children even!—to lie?

The world of poker is laden with misconceptions. And first among them is the very one I’m seeing from a stricken Baba Anya: equating poker with gambling. To my mind, the journey was well motivated: Of course people would understand that poker was an important way to learn about decisionmaking. I mean, think of John von Neumann! One of the great polymaths of the 20th century, father of the computer, one of the inventors of the hydrogen bomb, the creator of game theory. And a poker player! Not just a poker player, but someone for whom poker inspired brilliant insights into human decisionmaking, someone who considered it the ultimate game for approximating the strategic challenges of life. Let’s get to the tables! But looking at Baba Anya, I realize that the battle for support—and the justification for poker as not just a learning tool, but as one of the best tools there is for making decisions that have nothing to do with the game itself—is going to take a bit more fighting. I’m going to be explaining this over and over, so I may as well get it right.
Poker, to the untrained eye, is easy. Just like everyone who meets me seems to have “a book in them,” which they’ll write just as soon as they get a chance, so everyone who meets my coach, Erik Seidel—one of the most legendary poker players in the world—thinks they are just a hop away from becoming a poker pro or, at the very least, a badass poker bro. Most of us underestimate the skill involved. It just seems so simple: get good cards and rake in the dough. Or bluff everyone blind and rake in the dough once more. Either way, you’re raking it in.

And poker does have an element of chance, to be sure—but what doesn’t? Are poker professionals “gamblers” any more than the man signing away his life on a professional football contract, who may or may not be injured the next week, or find himself summarily dropped from the team in a year because he failed to live up to his promise? We judge the poker player for gambling; we respect the stockbroker for doing the same thing with far less information. In some ways, poker players gamble less than most. After all, even if they lose an arm, they can still play.
But the misperception is ingrained in the popular mind for one simple reason. Unlike, say, Go or chess, poker involves betting. And betting involves money. And as soon as that enters the picture, you might as well be playing craps or baccarat—games that truly are gambling. And so I tell my grandmother the words that I’ve come to repeat so often they are like my own private mantra: In poker, you can win with the worst hand and you can lose with the best hand. In every other game in a casino—and in games of perfect information like chess and Go—you simply must have the best of it to win. No other way is possible. And that, in a nutshell, is why poker is a skilled endeavor rather than a gambling one.
Imagine two players at a table. The cards are dealt. Each player must look at her cards and decide whether or not the cards on their own are good enough to bet. If she wishes to play, she must at minimum “call” the big blind—that is, place as much into the pot as the highest bet that already exists. She may also choose to fold (throw out her cards and sit this hand out) or raise (bet more than the big blind). But who knows what factors she’s using to make her decision? Maybe she has a premium hand. Maybe she has a mediocre hand but thinks she can outplay her opponent and so chooses to engage anyway. Maybe she has observed that the other player views her as conservative because she doesn’t play many hands, and she’s taking advantage of that image by opening up with worse cards than normal. Or maybe she’s just bored out of her mind. Her reasoning, like her cards, is known only to her.
The other player observes the action and reacts accordingly: If she bets big, she may have a great hand—or be bluffing with a bad one. If she simply calls, is it because her hand is mediocre or because she’s a generally passive player or because she wants to do what’s known as “slow playing”—masking an excellent hand by playing it in a restrained fashion, as Johnny Chan did in that 1988 World Series Of Poker matchup with Erik Seidel? Each decision throws off signals, and the good player must learn to read them. It’s a constant back-and-forth interpretive dance: How do I react to you? How do you react to me? More often than not, it’s not the best hand that wins. It’s the best player. This nuance, this back-and-forth, this is why von Neumann saw the answer to military strategy in the cards. Not because everyone is a gambler, but because to be a winning player, you have to have superior skill, in a very human sense.

Indeed, when the economist Ingo Fiedler analyzed hundreds of thousands of hands played on several online poker sites over a six-month period, he found that the actual best hand won, on average, only 12 percent of the time, and less than a third of hands went to showdown (meaning that players were skillful enough to persuade others to let go of their cards prior to the end of the hand). In mid-stakes games, with blinds of 1/ 2 and 5/10—that is, where the blind bets two players are forced to pay each round to start the action are $1 and $2, or $5 and $10, respectively—there were some players who were consistent winners, and as stakes went to nosebleed, 50/100 and up, the variability in skill went down significantly. That is, the higher the amount of money for which people played, the greater their actual skill edge. When Chicago economists Steven Levitt and Thomas Miles looked at live play and compared the ROI, or return on investment, for two groups of players at the 2010 WSOP, they found that recreational players lost, on average, over 15 percent of their buy-ins (roughly $400), while professionals won over 30 percent (roughly $1,200). They write, “The observed differences in ROIs are highly statistically significant and far larger in magnitude than those observed in financial markets where fees charged by the money managers viewed as being most talented can run as high as 3 percent of assets under management and 30 percent of annual returns.” Success in poker, in other words, implies far more skill than does success in that far more respectable profession, investing....

As noted in the intro to a 2011 post, the ability to make decisions under conditions of incomplete information is a talent that can be developed:
Why Analysts Should Keep it Simple (BAC)
I just read half of a manager's lengthy defense of a position in Bank of America that sounds to be seriously underwater.
After a few thousand words I asked myself if this was the highest use of my time and got a ringing "No" for an answer.
I've never cared for the 37-page investment thesis approach to investing.
Instead, I've hung around people who are very quick on their feet and who make decisions-based-on-imperfect-information all day long and I've sort of acquired the trait....
And from a 2007 post on carbon markets:
...Here's economist John Kay in the Financial Times last year:...The first problem was the lawyers, whose instinct is to write rules to cover every possible contingency. But no one can anticipate every possible contingency. Some economists believe in, and lawyers aspire to, a world in which contracts and property rights are completely specified. But business must face imperfect information today and inescapable uncertainty tomorrow. The genius of the market system is that it responds flexibly, if imperfectly, to a future that will not have been predicted. That is why clear and transparent regulation is hard to achieve in a market economy.... 
Paul Tudor Jones On 'Imperfect Information'

"How to Choose With Less Than Perfect Information"
Following up on yesterday's "Paul Tudor Jones On 'Imperfect Information'", a repost from 2014:
Less-than-perfect-information is a term from decision theory.

"Poker, Speeding Tickets, and Expected Value: Making Decisions in an Uncertain World"

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