Poker, Trading, and the Efficient-Market Hypothesis

In financial economics, the efficient-market hypothesis (EMH) states that asset prices fully reflect all available information. A direct implication is that it is impossible to “beat the market” consistently on a risk-adjusted basis since market prices should only react to new information or changes in discount rates (the latter may be predictable or unpredictable).
The EMH was developed by Professor Eugene Fama who argued that stocks always trade at their fair value, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall market through expert stock selection or market timing, and that the only way an investor can possibly obtain higher returns is by chance or by purchasing riskier investments.[1]
~https://en.wikipedia.org/wiki/Efficient-market_hypothesis

I have a friend who is quite into creating a strategy for trading that can be executed using automated software.  The basic idea of this project is to use programming code to back test trading strategies using historical data in order to “optimize” performance by highlighting superior strategies.

We have talked in various ways about efficient market hypothesis, however his view is that he is making profits from exploiting other traders exploitable strategies. The idea is that it is human error and market inefficiency his optimization algorithms are finding and profiting from.

I will try to explore this and shed light on this using poker as a metaphor for the evolving markets.

All Finite Games Have a Solution…

This is the the crux behind the Nash equilibrium, that games with a finite characteristic do indeed have some solution in which no player might UNILATERALLY deviate and gain.  In paper, rock, scissors for example a player might throw a random strategy of 1/3 of each paper, rock, or scissors.  We might be able to intuitively see that there is no such counter strategy that might gain vs this solution.

What is further interesting is that Nash did not provide the solution for all finite games.  This is not the cleverness of his discovery.  He simply was able to show that such a solution EXISTED, and it was clear to him the power of this insight.

We might learn of some of this power in this article.

Poker: Incentive for a Solution to an Unsolved Game

Poker is kind of interesting in this regard.  In the sense of the Nash equilibrium poker can be said to be finite and so the players are largely aware there is some optimal solution for it. Yet much of the allure for it is that Poker is NOT solved today (especially the no-limit variants!) and so there can easily be observed different levels of skill and knowledge on the game-not everyone is near the same level of talent!

In this we can see poker from a slightly different perspective than the normal status quo view.  Poker is a game that evolved in a way that we provide incentive for intelligent and creative peoples to solve it.

The advances in the strategy of the game, by being mixed with and studied by game theorists etc have been fuelled by the incentive provided to the winners that use these strategies.

We should expect then, that over time, poker will be more and more solved 🙂

How To Solve Unsolvable Games (Why Isn’t Poker Solved?)

There is a sort of theme to the wealthofchips chips that poker and games arose, over time, in relation to different social/economics boundaries that society hadn’t yet overcome.  As we pass through certain barriers, perhaps such as the advent of rubber, different games might arise (or perhaps games created technology, or perhaps there is simply an observable relationship between the two!).

Poker is one such game with an interesting history in this regard.

The basic premise created is that Poker became a necessarily complex game that is basically unsolvable by the individuals efforts. In its recent history computer programming and analytics combined with brute force have furthered the discovery of what will become GTO poker strategy.

Yet the complete solution is still believed to be far out of the capability of modern day computing power (excluding distributed networks like bitcoin!).

The Power of the Markets

Thewealthofchips shows that IF the poker industry could be arranged with optimal liquidity, optimal poker would be brute force solved by the players of the game. That is by observing strategies in relation to winrate’s one could have a great head start in figuring out what would be optimal strategy.

In this sense the markets act like a giant super computer in which each participant functions like a highly functioning component.  Winners spread their winning strategies and intelligent players adopt and experiment with what seems to work.

Since the fields will naturally tend toward GTO (you will get exploited harder if you don’t evolve!) there is then an observable trend to eventually follow.

In this we can see that poker will eventually be solved by brute market force.

The Problem With Today’s Conditions

Today such a trend is not so observable.  Why?  Remember that it is EFFICIENT Market Hypothesis. The current ipoker industry, which is the industry of poker (vs. live poker) that has the potentiating for enough liquidity to brute force solve such a complex problem, has been monopolized by Amaya/Poker Stars that controls over 70%+ of the market share.

Not only is the cost to player poker unnaturally high in this sense, but the industry standard practices of hiding players effective winrates PERTURBS the markets ability to brute force Poker’s solution.

This is a controversial subject obviously since so many players have been sold the false doctrine for many years that if bad players realize they are losing they will stop playing.  This seems detrimental to the “winning players” because now there are no “fish” to feed the “sharks”.

Furthermore as the monopolistic practises enforced by Poker Stars pervade the industry standards, winrates have suffered overtime which in turn effectively increases variance.

In some or many games variance is so high its nearly impossible to determine an effective winrate within any reasonable or useful context.

In other words “winning strategy” isn’t getting brute forced by the markets because it is getting more difficult to tell who the most winning players are over time (something few players are willing to admit or discuss!).

Expected Value and Expectation

Expected value is a concept where by one can make best based on the odds one is offered vs the probability of winning.  If there is a positive expectation in general the idea is one would take the bet.  A lottery has a negative expectation in this sense, where as a sure bet with a friend has a positive one (of course sureness may or may not be seen as subjective).

Players make their decisions based on pot odds and a best fit analysis of the average of all the possible hands their opponents COULD have vs all the possible hands the hero might have (this is far more proper than trying to guess what your opponent has vs what you do have!).

There is a belief that making these decisions creates a positive expectation for the player, however, players have evolved and trained/coached each other to ignore the overall effects of rake and effective rake on expectation.

In other words you can play good poker, or superior poker, and still lose over time if the house takes too much rake (hint: it does!)

Variance is Not a Sound a Horse Makes

What I wish to point out here is the effect of variance on a players perceived expectation. The higher the variance the larger the sample size that is needed to have statistical confidence in results.  Players that do not understand this are easily fooled. Over time as winrates have faded and games have gotten tougher (two sides of the same coin!) players have seemingly not become aware of the effects of variance on the psychology of the players and communities they make up.

Players have grown a distaste to talking about the true mathematical make-up and ramifications of high variance environments. And so there are varying levels of disinformation in regard to different levels of strategy that have grown amongst the community.

Players don’t seem to realize that an inability to maturely discuss variance is both a symptom and a cause of a degraded average intelligence.

In short without having statistical confidence in one’s winrate..and without being able to present a solution to Poker it is truly difficult to argue what strategies are optimal from who’s perspective.

Are the Global Markets a “Finite Game” and What Are the “Players” Solving?

My point might be still a little incoherent, but the idea here is that subjective valuations of strategy’s cannot be said to have a positive expectation.  Not from a gamblers perspective nor from a useful investors perspective.  And so there is some relevance in regard to variance involved, in showing a certain line or option is profitable since there is probability involved.

In regard to the markets I often ask my friend what is his expected rate of return.  We explore these thoughts together in an amusing an respectful fashion, but he cannot only answer with the stats he HAS, which in effect is an analysis of how his strategy might have performed in the past.

He takes this past roi%, that he WOULD have made, and uses the trend to predict what might be a possible future using the strategies he optimized.

But is the sample size big enough?
What is the variance?
What is happening over time?

This friend is capitalizing on what he feels are other peoples exploitable strategies and yet we can see with the evolution of such programs that their exploitable strategies, like poker, should over time trend towards to optimal solution.

That solution is price discovery of the objective valuation of market commodities.

“Solving the Markets”

The markets today aren’t “efficient” or free running as they could or should be, this is a common sentiment. Yet over time we should expect the bad strategies to be replaced by good ones, and technology and regulation to evolve more favourably for the participants.

The game the markets pose might not be “finite” per se but we can see there is some sense of an end game given that there should be some optimal value for each commodities (even if that value changes over time).

I think then what we have laid the philosophical foundation for, is that over time the profitability of trading in the sense of exploiting other strategies is something that will fade over time.

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