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Own the House

June 20, 2018

How’s this for a sentence sure to grab Wall Street clicks and eyeballs:

 

“Professional poker players are experts at extracting signal from noise across many channels, and at integrating information from those channels both to exploit their opponents and protect themselves.”

 

Let’s count the financial market dogwhistles: 1) Poker, an enduring fave among market operators; 2) extracting signal from noise, an effort on which banks and funds spend billions in human and algorithmic talent; 3) exploiting opponents, for the alpha traders, and; 4) protecting themselves, for the beta investors.

 

But the sentence didn’t originally appear at Zero Hedge or Seeking Alpha or some such content farm. Rather, it is from a short article on the University of California Davis school blog titled Success is Not Just How You Play Your Cards, But How You Play Your Opponents (hard to tell whether the article was written by either Andy Fell and/or Karen Nikos-Rose). That post in turn summarizes a just-published UC Davis study by Seth Frey, Paul Williams and Dominic Albino dauntingly titled Cognitive Information Encryption in the Expert Management of Strategic Uncertainty. The blog post and, to a lesser extent, the underlying study have been making the rounds on financial news sites (see here). While I don’t feel comfortable making strong claims about anything related to investing or the market because I lack the exposure needed to be confident in such remarks, poker is a different matter, and in at least one instance I strongly disagree with the paper’s conclusion.

 

My problem is with how the researchers approached bluffing. This section of Fell’s post illustrates my problem nicely: “Frey and co-authors look at the No-limit Texas Hold’em variant of poker, which works well for the study because the game is designed to make bluffing a central aspect of play. The game offers many mechanisms by which players can strategically misinform each other about the value of their cards. Players with strong hands may signal weak hands with small bets to keep the pot growing, and players with weak hands may signal strong hands with large bets to intimidate their opponents into folding before ‘showdown,’ when all players left in the game must reveal their hands.”

 

This is explicitly not how expert players view bluffing, although many amateurs believe it to be the case. It’s not fair to criticize the blogger for this misunderstanding, however, as the researchers don’t seem to have it quite right either:

 

“Players with strong hands may signal weak hands with small bets to keep the pot growing, and players with weak hands may signal strong hands with large bets to intimidate their opponents into folding before showdown.”

 

Again, this is not how it works at the game theory level. The primary concern of expert poker players in their strategy is balance. If we were to assume, as Frey et al. seem to, that players were employing the methods described above, then opponents would easily exploit them. This approach could be profitable against low skill opponents who won’t grasp the subtleties and nuances of the situation, but that the majority of online players are too sophisticated for this approach to work.

 

So, if your opponent is competent, what do you do? Balance, balance, and balance. The study never uses that word but it does reference a ‘synergy’ that appeared consistent with the ‘shark’s’ hand histories and not apparent in the ‘fish’s’ histories. I’ll be honest here for a second and admit to not fully understanding the data I’m about to show. They used some fancy pairwise math that is above my head but their analysis is spot on.

 

 

The goal of poker - to me at least - is to be as hard as possible to play against. To accomplish this your opponents need to be always guessing what you have. Whether you are betting for value or for a bluff your bet size should communicate the same story.  By deviating among your sizings, such as betting big when you are bluffing and betting medium to small when you aren’t, not only are experts going to exploit you but you aren’t going to be making as much profit as you should be.

 

Simple beats complex. When I make the best hands I want to bet big. When I make decent hands I want to bet small. These are super simplifications and don’t consider any nuance but it is the logic behind expert strategy and where game theory comes into play. In order for people to call my big bets with their good hands (good hands meaning hands that are worse than the hand I’m betting with) they need to know I don’t have the better hand every time. The way this is accomplished is through bluffing.

 

Bluffing isn’t the means in which experts look to win pots but rather how they establish balance in their strategy. The study writes:

 

“It should come as no surprise that experts are more integrative information processors; it is entirely likely that more processing leads to more profitable behavior in complex strategic settings like NLHE. The surprise is the ability of synergistic information processing, beyond its direct effect on one’s own behavior, to increase opponents’ strategic uncertainty about what that behavior will be.”

 

Uncertainty is the key to beating opponents. As soon as someone knows what you’re doing you become an ATM. This is the market comparison that sticks with me the most.  As Michael Batnick puts it in his recent Halftime Report appearance on CNBC, “The stock market is a great opponent and I think that the market is just a petri dish of making bad mistakes.” You can never know if the market is going up or down. The market is an expert at balance and the reason for why active investing will always be a challenge if not impossible. A sobering stat that de-motivates me every time I want to play poker is that the best players can only beat bad players at most 60% of the time. And when your opponent is as unpredictable as the market the best strategy is to always own the house.

 

links:

https://www.cnbc.com/video/2018/06/18/how-the-best-investors-reacted-to-their-worst-investments.html

http://blogs.ucdavis.edu/egghead/2018/06/15/4414/

https://www.marketwatch.com/story/what-you-can-learn-from-poker-players-according-to-science-2018-06-19

https://arxiv.org/abs/1605.04233

 

 





 

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