Chaos-on-a-chip model shows market bubbles may be predictable, controllable

Oct 18, 2013
stock market

(Phys.org) —It's an idea financial regulators have dreamed of. Experiments on a simple model of chaos have found that it may be possible not only to predict an extreme event, like a stock market collapse, but to intervene and prevent it from happening.

In a paper appearing October 21 in the journal Physical Review Letters, an international team of researchers say that these extreme events, which they call "dragon kings," are less random than had been thought and that, in a simple experiment at least, they can be anticipated and controlled.

"These dragon kings are predictable, if we knew what to measure," said co-author Dan Gauthier, the Robert C. Richardson professor of physics at Duke University.

The latest finding is an outgrowth of experimental work Gauthier has been doing since the 1990s with simple electrical he calls "chaos generators." Two identical circuits consisting of two capacitors, an inductor, a nonlinear diode and a power source, are each set to generate chaotic oscillations in their voltages and currents. Being identical, the credit-card sized circuit boards are supposed to oscillate in synch with each other when they are coupled - called "synchronized chaos." But in practice, they experience subtle variations in behavior so that the voltages and currents in one circuit do not match their twin.

Because the behavior of each circuit is chaotic, the voltages and current change in an erratic manner over time, but both circuits are synchronized, so that they both change together and show the same behavior most of the time, Gauthier said.

During a long run of the experiment, the data reveal that the chaotic behavior visits "hot spots" in which an extreme event, "a bubble," might occur. This is an event in which the circuits suddenly and temporarily loose synch. Sometimes the size of the event is small, like a small change in a financial market, and other times it is gigantic, like a market crash. And the size of most of these disturbances follows a distribution, in which one variable changes as a power of the other. The most extreme events, the "dragon kings," are responsible for significant deviations from the curve of the power law.

Extreme events that may be governed by these laws would include sudden population crashes in species or freak waves in the ocean, Gauthier said. Other examples might be epileptic storms of activity in the brain and rolling power outages caused by an initial small disturbance, like a squirrel shorting out one substation on a large grid. Other examples could be found in the occurrence of incipient failure of materials and of engineering structures, in the synchronized behavior of kidney and heart cells in the body, in meteorological front dynamics and in climate change, among many others.

In a series of experiments performed with the coupled chaos circuits by Gauthier's colleague and former post-doctoral research associate, Hugo Cavalcante, who is now at the Federal University of Paraiba in Brazil, it was found that the introduction of a tiny amount of current injected into one of the circuits at just the right time prevented a predicted dragon king from happening. "Maybe tiny nudges can make a big difference," Gauthier said.

Gauthier and Cavalcante co-authored the paper with Edward Ott of the University of Maryland, College Park; Marcos Oria from the Federal University of Paraiba; and Didier Sornette of the Swiss Federal Institute of Technology, who is director of a group called the Financial Crisis Observatory. The Observatory has applied similar principles to predict several market disturbances in recent years.

Sornette coined the term "dragon king," which he explained in a TED-Global lecture in Edinburgh, Scottland in June 2013.

"The limitation of our paper is that we haven't shown that our circuit has relevance to the ," which has many more variables, Gauthier said. "We aren't yet sure where to look, but for this one simple system, we figured out how to find it."

Gauthier said the five-page paper faced a difficult gauntlet of reviewers before being accepted in PRL. "We're trying to open up people's thinking to the possibility that systems that change are constantly evolving in time," he said. "We're trying to show that there's a wider, richer set of systems that express ," Gauthier said, "and that they might be controlled."

Explore further: Thermoelectric power plants could offer economically competitive renewable energy

More information: "Predictability and Suppression of Extreme Events in a Chaotic System," Hugo L.D. de S. Cavalcante, Marcos Oriá, Didier Sornette, Edwart Ott, Daniel J. Gauthier. Physical Review Letters, Oct. 21, 2013. On Arxiv: arxiv.org/pdf/1301.0244v3.pdf

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User comments : 8

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QuixoteJ
1 / 5 (9) Oct 18, 2013
Being identical, the credit-card sized circuit boards are supposed to oscillate in synch with each other when they are coupled - called "synchronized chaos." But in practice, they experience subtle variations in behavior so that the voltages and currents in one circuit do not match their twin ... During a long run of the experiment, the data reveal that the chaotic behavior visits "hot spots" in which an extreme event, "a bubble," might occur. This is an event in which the circuits suddenly and temporarily loose synch.
I wonder if the deviations can be explained/measured from the subtle variations in actual component values. What tolerance resistors and capacitors did they use? Can they minimize the "hot spots" by ensuring they use components that were produced right next to each other in the same lot? Ensure that temperature is exactly the same for both circuits? Might help find what is responsible for hot spots in more complex systems. Also, "nonlinear diode" is redundant.
Doug_Huffman
1.4 / 5 (10) Oct 18, 2013
LOL Benoit Mandelbrot is spinning in his grave. Think magnetic confinement of plasma, squeeze harder, control 'harder' and the field pops out somewhere else, makes a new hole.

Read Nassim Nicholas Taleb on complex systems. He and collaborator Mandelbrot called reality "fractally complex."

Taleb attributes the worsening of economic bubble collapses to ever tighter controls, squeezing harder for profit.
jdbertron
1 / 5 (9) Oct 18, 2013
Ah right, if physics researchers say it, then Market bubbles can't possibly be predictable.
This is so ridiculous, it's almost propaganda. Did Janet Yellen sponsor this article ?
cantdrive85
2 / 5 (13) Oct 18, 2013
Some aspects of market bubbles are predictable, take the housing bubble for example. A handful of people made billions "predicting" an end to that bubble. We are now in the throes of a treasury bubble, it can't be predicted when it will end, but it will end and it will end very badly for us sorry pleebs.
wealthychef
3 / 5 (4) Oct 18, 2013
There is one thing that is predictable here: the markets will game any attempt to predict them. Someone will design a vehicle that predicts bubbles and it will interfere with the bubble prediction itself... markets are inherently resistant to analysis because analysis affects their behaviors. Why isn't this understood by these people? It seems simple to me.
gjbloom
not rated yet Oct 18, 2013
In his simple electronic model he uses two chaotic attractors. To extrapolate to the market, he would need to identify the chaotic attractors that determine market price. I submit that the market has several million chaotic attractors, called humans. So all he needs to do is predict the chaotic behavior of several million humans and he could then perhaps get a leg up on market behavior.
EnricM
1 / 5 (9) Oct 20, 2013
markets are inherently resistant to analysis because analysis affects their behaviors. Why isn't this understood by these people? It seems simple to me.


Because chaos mathematicians gained rock star status in the 80's when their models were able to yield some good results and when stock exchange still was considered sexy.
Their fans are basically all these Powerpoint slinging people working at finance interested in having stuff they can have ready-made in an excel sheet (or better a dedicated app where they only have to press a big button). Just recall the now infamous work of David X. Li
DavidHumus
1 / 5 (6) Oct 21, 2013
What good results came from Chaos Theory models? I don't recall anything that panned out with the possible exception of the realization that "predicting things is hard".

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