The flip side of chaos

[VLS]

An interesting read I found when browsing online. Just sharing it  



Pop wisdom says that chaos theory proves that these high-dimensional complex systems -- such as the weather, the economy, army ants, and, of course, stock prices -- are intrinsically, no-way-around-it unpredictable. So ironclad is the popular assumption that in common perception any design for predicting the outcome of a complex system is considered naive or mad.

But chaos theory is vastly misunderstood. It has another face. Farmer suggests chaos is like a hit (vinyl) record with two sides. The lyrics to the hit side go: "By the laws of chaos, initial order can unravel into raw unpredictability. You can't predict far." But the flip side goes: "By the laws of chaos, things that look completely disordered may be predictable over the short term. You can predict short."

In other words, the character of chaos carries both good news and bad news. The bad news is that very little, if anything, is predictable far into the future. The good news -- the flip side of chaos -- is that in the short term, more may be more predictable than it first seems. Both the long-term, unpredictable nature of the high-dimensional systems and the short-term, predictable nature of low-dimensional systems derive from the fact that "chaos" is not the same thing as "randomness." "There is order in chaos," Farmer says.

Farmer should know. He was an original pioneer into the dark frontier of chaos before it jelled into a scientific theory and faddish field of study. In the hip California town of Santa Cruz in the 1970s, Doyne Farmer and friend Norm Packard co-founded a commune of nerd hippies who practiced collective science. They shared a house, meals, cooking, and credit on scientific papers.

As the "Chaos Cabal," the band investigated the weird physics of dripping faucets and other seemingly random generating devices. Farmer in particular was obsessed with the roulette wheel. He was convinced that there must be hidden order in the apparently random spinning of the wheel. If one could discern secret order among the spin-ning chaos, then . . . why, one could get rich . . . very rich.

In 1977, long before the birth of commercial microcomputers such as the Apple, the Chaos Cabal built a set of handcrafted, programmable, tiny microcomputers into the bottoms of three ordinary leather shoes. The computers were keyboarded with toes; their function was to predict the toss of a roulette ball. The home-brew computers ran code devised by Farmer based on the group's study of a purchased secondhand Las Vegas roulette wheel set up in one of the commune's crowded bedrooms. Farmer's computer algorithm was based not on the mathematics of roulette but on the physics of the wheel. In essence, the cabal's code simulated the entire rotating roulette wheel and bouncing ball inside the chip in the shoe. And it did this in a minuscule 4 Kbytes of memory, in an era when computers were behemoths demanding 24-hour air conditioning and an attendant priesthood.

On more than one occasion, the science commune played out the flip side of chaos in a scene like this: Wired up at the casino, one person (usually Farmer) wore a pair of magic shoes to calibrate the roulette operator's flick of the wheel, the speed of the bouncing ball, and the tilt of the wheel's wobble. Nearby, a cabal cohort wore the third magic shoe that was linked to Farmer's by radio signals and placed the actual bet on the table.

Earlier, using his toes, Farmer had tuned his algorithm to the idiosyncrasies of a particular wheel in the casino. Now, in the mere fifteen seconds or so between the drop of the ball and its decisive stop, his shoe-computer simulated the full chaotic run of the ball. About a million times faster than it took the real ball to land in a numbered cup, Farmer's prediction machinery buzzed out in small taps the ball's future destination on his right big toe. Typing with his left big toe, Farmer transmitted that information to his partner, who "heard" it on the bottom of his feet, and then, with a poker face, pushed the chips onto the predetermined squares before the ball stopped.

When everything worked, the chips won. The system never predicted the exact winning number: the cabal members were realists. Their prediction machinery forecast a small neighborhood of numbers -- one octave section of the wheel -- as the bettable destination of the ball. The gambling partner spread the bets over this neighborhood as the ball finished spinning. Out of the bunch, one won. While the companion bets lost, the neighborhood as a whole would win often enough to beat the odds. And make money.

The group sold the quasi-legal system to other gamblers because of unreliability in the hardware. But Farmer learned three important things about predicting the future from this adventure:

First, you can milk underlying patterns inherent in chaotic systems to make good predictions.

Second, you don't need to look very far ahead to make a useful prediction.

And third, even a little bit of information about the future can be valuable.

With these lessons firmly in mind, Farmer, together with five other physicists (one of them a former Chaos Cabal member) engineered a start-up company to crack every gambler's dream: Wall Street. They would use high-powered computers. They would stuff them with experimental nonlinear dynamics and other esoteric rocket-scientist formulas. They would hack the financial world with the help of banks; it would be very legal, too.

They would . . . (drum roll, please) . . . predict the future. With a bit of bravado, the old gang hung out their new shingle: the Prediction Company.

The guys in the Prediction Company figure that looking ahead a few days into the financial market future is all that is needed to make big bucks. Prediction machinery need not see like a prophet to be of use. It needs only to detect limited patterns -- almost any pattern -- out of a camouflage of randomness and complexity.

According to Farmer, there are two kinds of complexity: inherent and apparent. Inherent complexity is the "true" complexity of chaotic systems. It leads to dark unpredictability. The other kind of complexity is the complement of chaos -- apparent complexity obscuring exploitable order.

Farmer draws a square in the air. Going up the square increases apparent complexity; going across the square increases inherent complexity. "Physics normally works down here," Farmer says, pointing to the bottom corner of low complexity for both sorts, home of the easy problems. "Out there," pointing to the opposite upper corner, "it's all hard. But we are now sliding up to here, where it gets interesting -- where the apparent complexity is high, but the true complexity is still low. Up here, complex problems have something in them you can predict. And those are exactly the ones we are looking for in the stock market."

With crude computer tools that take advantage of the flip side of chaos, the Prediction Company hopes to knock off the easy problems in financial markets.

"We are using every method we can find," says partner Norman Packard, a former Chaos Cabalist. The idea is to throw proven pattern-finding strategies of any stripe at the data and "keep pounding on them" to optimize the algorithms. Find the merest hint of a pattern, and then exploit the daylights out of it. The mind-set here is that of a gambler: any positive edge is an advantage.

Farmer and Packard's motivating faith that chaos possesses a flip side firm enough to bank on is based on their own experience. Nothing overcomes doubts like the tangible money they won from their experiments with the Las Vegas roulette wheel.

In addition to experience, Farmer and Packard place a lot of faith in the well-respected theories they invented during their years in chaos research. Now they are testing their wildest, most controversial theory yet. They believe, against the unbelief of most economists, that "the market is not random." They hold that certain regions of otherwise complicated financial phenomena can be predicted accurately. Packard calls these areas "pockets of predictability" or "local predictability." In other words, the distribution of unpredictability is not uniform throughout systems. Most of the time, most of a complex system may not be forecastable, but some small part of it may be for short times. In hindsight, Packard believes local predictability is what allowed the Santa Cruz Chaos Cabal to make money forecasting the approximate path of a roulette ball.



Source @ Wired.com

[esoito]

Re: They hold that certain regions of otherwise complicated financial phenomena can be predicted accurately. Packard calls these areas "pockets of predictability" or "local predictability."

These men --  W D Gann...David Bowden  --  actually put this quote into regular practice to make a fortune from the markets. (Gann made tens of MILLIONS!!!)
 
See also:  Gann's cryptic book:  Tunnel Through The Air...   (Bowden cracked this)

And Gann's Strategy (one of several): Trading the ranges


Sooooo...where's the Gann of Roulette?  Who is he/she?

I ask because it's highly likely someone, somewhere, has found order in the chaos...

[Fripper]

This is a very good read and made me think about some things. So thanks for sharing dear Vic.

[ThomasGrant]

See also:  Gann's cryptic book:  Tunnel Through The Air...   (Bowden cracked this)

Did Bowden crack this?
How and when?
And where?

Please explain.

[esoito]

@Thomas

Look up Safety In The Market.

Bowden (Qld-based) started the company and used it to teach Gann's strategies to members.

Sadly, Parkinson's became quite serious and he had to sell the company and scale back on his teaching.

But Bowden certainly managed to decipher Gann's cryptic codes and instructions...very publicly he picked market highs and lows several times -- to the day, the hour and the minute!!

And he taught others to do it too.

[ThomasGrant]

@Thomas

Look up Safety In The Market.

Bowden (Qld-based) started the company and used it to teach Gann's strategies to members.

Sadly, Parkinson's became quite serious and he had to sell the company and scale back on his teaching.

But Bowden certainly managed to decipher Gann's cryptic codes and instructions...very publicly he picked market highs and lows several times -- to the day, the hour and the minute!!

And he taught others to do it too.

Ohh yeah...
That's right.
I remember now.

Thanks for that.

[GARNabby]

Chaos theory is really more about regression-mathematics, but which also applies various models of behavior... the application of a basic set of equations: linear (constant); non-linear (changing); or a combination of those, to a lot of simple data to determine if and where the underlaying directions in that data will produce some extreme result in the distant future.  The classic simplistic example of this, a butterfly's flapping having the capability of causing a tropical storm a week later on the other side of the planet.  

Anyway, the reward(s) of predicting something further out usually increase exponentially; while what happens immediately-following remains, whether too- obvious or unobvious, of little value.

And extrapolation is only one means of prediction... interpolation is the other.  Furthermore, one may extrapolate backwards from a known or possible event, whether that event has yet occurred.  (Poker players sometimes work back from the possibility of an opponent having a particular holding on the end, after ruling out the others... asking, "Did he/she bet and/or behave in a specific way leading up to it.")

[VLS]

what happens immediately-following remains, whether too- obvious or unobvious, of little value.

But GARNabby, one spin at a time makes the long-term picture.

Wouldn't one be better putting the efforts in predicting the very next spin? I mean, welcoming every previous statistics about the game, but applied at aiming to be ahead in the very next spin. (Advantage players do it and they seem to enjoy a good overall rate).



...Perform good in the "building trams", and you have mastered the whole road!

[GARNabby]

But GARNabby, one spin at a time makes the long-term picture.

Unquestionably.  I just fail to see what Chaos Theory has to do with that short-term.

The same problem arises in baccarat... as when to focus on eg, the streaks of W-L's or P-B's continuing, over several "flat bets"; or on a few progressive bets, trying to catch where it changes.  It's nice to have some recourse for both scenarios.

[GARNabby]

And for the most-long term of casino-predictions... to leave for the day, when the table(s) have nothing strong showing within sight.

[ThomasGrant]

Unquestionably.  I just fail to see what Chaos Theory has to do with that short-term.

Isn't RNG Chaos Theory in Action.?
Short term or long term.

[GARNabby]

Isn't RNG Chaos Theory in Action.?
Short term or long term.

Short answer... no, RNG's are are only examples of possible types of chaos.

Here're a couple of lines from Wikipedia about Chaos Theory... keeping in mind that, in my opinion anyway, that resource is seldom the definitive one, from the link at link:://en.wikipedia.org/wiki/Chaos_theory .

"Chaos theory is a field of study in mathematics, physics, economics and philosophy studying the behavior of dynamical systems that are highly sensitive to initial conditions. This sensitivity is popularly referred to as the butterfly effect. Small differences in initial conditions (such as those due to rounding errors in numerical computation) yield widely diverging outcomes for chaotic systems, rendering ***long-term*** prediction impossible in general.[1] This happens even though these systems are deterministic, meaning that their future behaviour is fully determined by their initial conditions, with no random elements involved.[2] In other words, the deterministic nature of these systems does not make them predictable."

"In common usage, "chaos" means "a state of disorder",[19] but the adjective "chaotic" is defined more precisely in chaos theory. Although there is no universally accepted mathematical definition of chaos, a commonly used definition says that, for a dynamical system to be classified as chaotic, it must have the following properties:[20]

it must be sensitive to initial conditions;
it must be topologically mixing; and
its periodic orbits must be dense.

The requirement for sensitive dependence on initial conditions implies that there is a set of initial conditions of positive measure which do not converge to a cycle of any length."
_________________________________________________________________________

Perhaps the best way someone who has had no theoretical experience with this concept per se can put it, I believe these matters are 'non-computational'... randomly-accessed and globally-determined; neither sequentially-accessed nor locally-determined.

Specifically, the advantage-player's roulette device-strategies are more about brute-force, last-second calculations made directly from the data at hand... with "Chaos Theory" thrown in to sell it to someone else, when that fails to do anything.  (I mean, why else the corny name for them in the first place?  Like calling everything else, voodoo.)