[tt] NS 2944 Slaying dragon-kings could prevent financial crashes

[tt] NS 2944 Slaying dragon-kings could prevent financial crashes


Who will be in charge of the slaying? Will they operate a pure devotees of
the public interest, assuming they can find it?

NS 2944: Slaying dragon-kings could prevent financial crashes
http://www.newscientist.com/article/mg22029443.000-slaying-dragonkings-could-prevent-financial-crashes.html
* 20 November 2013 by Lisa Grossman

[Editorial: "Taming the beasts of the global economy" added.]

HUGO CAVALCANTE saw the disaster coming. From his lab at the Federal
University of Paraíba in Brazil, he detected the warning signs of an
epic crash. At the last minute, he managed to nudge his system back
to safety. Crisis averted.

OK, so Cavalcante"s impending crisis was only a pair of
credit-card-sized circuits that were about to start oscillating out
of sync - hardly the stuff of the evening news. But the experiment
is the first to show that a class of extreme events, colourfully
called dragon-kings, can be predicted and suppressed in a real,
physical system. The feat suggests that some day we may also be able
to predict, or in some cases prevent, some of the catastrophes in
the real world that seem unstoppable, including financial crashes,
brain seizures and storms.

"People were hoping if you could forecast extreme events, maybe we
could find a way to control them," says Cavalcante"s colleague
Daniel Gauthier at Duke University in Durham, North Carolina. "We
were able to completely suppress the dragon-king events."

Dragon-kings aren"t the first animal used to describe a class of
catastrophic events. In 2001, Nassim Taleb published a book called
The Black Swan, his name for catastrophes that always catch us
off-guard. But though difficult to predict, black swans actually
fall within an accepted mathematical distribution known as a power
law, which says there will be exponentially more small events than
large ones (see diagram).

Most events or objects found in a complex system - including
earthquakes, hurricanes, moon craters, even power imbalances in war
- also obey a power law, a ubiquity that some say hints at a deeper
organising principle at work in the universe. Others, like Taleb,
focus on the fact that a power law can"t predict when black swans
will occur.

Now there"s another beast to reckon with. In 2009, Didier Sornette
at the Swiss Federal Institute of Technology in Zurich reported that
some events lift their heads above the power law"s parapet, the way
a king"s power and wealth vastly outstrip that of the more plentiful
peasant. So big that they should be rare, these events have a
greater probability of occurring than a power law would mandate.

"There seem to be certain extremes that happen much more often than
they should if you just believe the power-law distribution predicted
by their smaller siblings," Sornette says.

He christened them dragon-kings. The dragon part of the name stems
from the fact that these events seem to obey different mathematical
laws, just as a dragon"s behaviour differs from that of the other
animals.

Sornette got his first whiff of dragon-kings when studying cracks
that develop in spacecraft. Since then, he has spotted them
everywhere, from a rainstorm that hit Venezuela in 1999 and the
financial crashes in 2000 and 2007, to some epileptic seizures.

But he wasn"t satisfied with merely recognising dragon-kings. The
fact that they don"t follow a power law suggests they are being
produced by a different mechanism, which raises the possibility
that, unlike events that follow the power law, dragon-kings may be
predictable.

He and his colleagues have had some success, predicting a slip in
the Shanghai Stock Exchange before it happened in August 2009 and
using a few electrical pulses to suppress seizures that might have
become dragon-kings in rats and rabbits. But the difficulty of
running controlled experiments in real financial systems or brains
prevented them from going any further.

Enter Cavalcante and Gauthier"s oscillating circuits. Gauthier spent
the early 1990s studying pairs of identical circuits that behaved
chaotically on their own, but would synchronise for long periods of
time when coupled in a certain way. "It"s a little bit politically
incorrect, but it"s sometimes called the "master-slave"
configuration," Gauthier says. He coupled the two circuits by
measuring the difference between the voltages running through them,
and injecting a current into the "slave" circuit to make it more
like the "master". Most of the time this worked and the two would
oscillate together like a pair of swinging pendulums, with only
slight deviations away from synchronisation.

But every so often, the slave would stop following the master and
march to its own beat for a short time, before getting back in step.
Gauthier realised at the time that there were recognisable signs
that this disconnect was about to happen. It wasn"t until he saw
Sornette"s work that he checked for dragon-kings.

He and his colleagues have now shown that the differences in the
circuits" voltages during these desynchronisations are indeed
dragon-kings. "They were as big as the system would physically
allow, like a major disaster," Gauthier says.

The pair went on to show that they could reliably forecast when a
big event was about to happen: whenever the differences between the
circuits" oscillations decreased to a certain value, a leap of
dragon-king proportions was almost always imminent. And once they
saw it coming, they found they could apply a small electrical nudge
to the slave circuit to make sure it didn"t tear away from its
master (Physical Review Letters, doi.org/p44).

"We basically kill the dragon-king in the egg," Sornette says. "The
counter-mechanism kills it when it is burgeoning."

It"s a long way to go from a pair of coupled circuits to the massive
complexity of the real world. But by using this simple system to
find out at what stage in the process a dragon-king can be
prevented, Sornette hopes to see whether financial regulation could
prevent a crash once a stock market bubble has already begun to
grow, a controversial topic among regulators.

"The fear of central banks is that their intervention might actually
worsen the situation and trigger the crashes, destabilising the
system even further," he says. "That"s the type of insight we could
test and check and probe with our system."

Some physicists think the gap between so-called low dimensional
systems like the pair of oscillators, which can be described by just
three variables each, and real-world complex systems like the stock
market, is too wide to bridge. "The conclusions of the paper appear
correct and interesting for people studying low dimensional chaos,"
says Alfred Hubler of the University of Illinois at
Urbana-Champaign. "But in the real world, low dimensional chaos is
very rare. Most real-world complex systems have many interacting
parts."

Others agree with Sornette that having a simple physical system to
manipulate will be useful. "Having a mechanical system where you can
explore it in the lab is crucially important," says Neil Johnson at
the University of Miami in Coral Gables. He studies dragon-kings in
simulations of stock markets and traffic jams and can"t wait to
start using a pair of oscillators to see how they relate.

Sornette thinks the circuits are just the beginning of a future in
which we can monitor, diagnose, forecast and ultimately control our
world. "I think we are on the verge of a revolution where we are
going to be able to steer our planet better, informed by this kind
of science." It"s quite a promise - not all storms, seizures and
crashes are dragon-kings, after all. But we now have a tool to
explore how to deal with those that are.
---
Editorial: Taming the beasts of the global economy
http://www.newscientist.com/article/mg22029441.900-taming-the-beasts-of-the-global-economy.html
* 21 November 2013

ECONOMICS has always had a fondness for animal metaphors. John
Maynard Keynes called the mix of instincts, emotions and cognitive
biases that drive human behaviour and shape markets "animal
spirits". Bulls and bears prowl Wall Street; hawks and doves debate
interest rates and credit ratings. More recently, we have been
introduced to "black swans" - the term used by author Nassim Taleb
to describe rare, catastrophic events that we are generally bad at
anticipating.

Now the bestiary has another member: "dragon-kings", fearsome events
that are even worse than black swans. But while slaying dragons
sounds more formidable than fending off swans, there are signs that
these events can be predicted and averted (see "Slaying dragon-kings
could prevent financial crashes"). Some of the big beasts that stalk
the global economy may be tameable after all.