blacks swans, the dragon king, and the power law
February 24, 2017 11:35 PM   Subscribe

How Dragon Kings Could Trump Black Swans, MIT Technology Review, 4 AUG 2009.
Sornette goes on to identify a number of data sets showing power laws with outliers that he says are the result of positive feedback mechanisms that make them much larger than their peers. He calls these events dragon kings. What’s interesting about them is that they are entirely unaccounted for by a current understanding of power laws, from which Nassim Nicholas Taleb built the idea of black swans.
So what to make of this? Sornette offers one interesting observation. The seemingly ubiquitous presence of these dragon kings in all kinds of data sets means that extreme events are significantly more likely than power laws suggest.
Prof. Dr. Didier Sornette is the Professur f. Entrepreneurial Risks at Eidgenössische Technische Hochschule Zürich and author of Why Stock Markets Crash:
Critical Events in Complex Financial Systems
and Critical Phenomena in Natural Sciences: Chaos, Fractals, Selforganization and Disorder: Concepts and Tools, also lectures: Power Laws and Dragon-kings Heavy Tails and Long Tails [PDF]

From 2013: How We Can Predict The Next Financial Crisis, a TED Talk (transcript)

Predictability of catastrophic events: Material rupture, earthquakes, turbulence, financial crashes, and human birth [PDF], Didier Sornette, PNAS, February 19, 2002, vol. 99, 2522–2529
We propose that catastrophic events are ‘‘outliers’’ with statistically different properties than the rest of the population and result from mechanisms involving amplifying critical cascades. We describe a unifying approach for modeling and predicting these catastrophic events or ‘‘ruptures,’’ that is, sudden transitions from a quiescent state to a crisis. Such ruptures involve interactions between structures at many different scales. Applications and the potential for prediction are discussed in relation to the rupture of composite materials, great earthquakes, turbulence, and abrupt changes of weather regimes, financial crashes, and human parturition (birth).
Dragon-Kings, Black Swans and the Prediction of Crises, Didier Sornette, 24 June 2009 - International Journal of Terraspace Science and Engineering 2(1), 1-18 (2009) [PDF]
We develop the concept of ``dragon-kings'' corresponding to meaningful outliers, which are found to coexist with power laws in the distributions of event sizes under a broad range of conditions in a large variety of systems. These dragon-kings reveal the existence of mechanisms of self-organization that are not apparent otherwise from the distribution of their smaller siblings. We present a generic phase diagram to explain the generation of dragon-kings and document their presence in six different examples (distribution of city sizes, distribution of acoustic emissions associated with material failure, distribution of velocity increments in hydrodynamic turbulence, distribution of financial drawdowns, distribution of the energies of epileptic seizures in humans and in model animals, distribution of the earthquake energies). We emphasize the importance of understanding dragon-kings as being often associated with a neighborhood of what can be called equivalently a phase transition, a bifurcation, a catastrophe (in the sense of Rene Thom), or a tipping point. The presence of a phase transition is crucial to learn how to diagnose in advance the symptoms associated with a coming dragon-king. Several examples of predictions using the derived log-periodic power law method are discussed, including material failure predictions and the forecasts of the end of financial bubbles.
Dragon-kings: mechanisms, statistical methods and empirical evidence[arXiv PDF] ,Eur. Phys. J. Special Topics 205, 1-26, 2012 Didier Sornette, Guy Ouillon

reach back and find: Didier Sornette: Critical phase transitions made self-organized : a dynamical system feedback mechanism for self-organized criticality. [PDF] Journal de Physique I, EDP Sciences, 1992, 2 (11), pp.2065-2073.
According to Kadanoff, self-organized criticality (SOC) implies the operation of a feedback mechanism that ensures a steady state in which the system is marginally stable against a disturbance. Here, we extend this idea and propose a picture according to which SOC relies on a non-linear feedback of the order parameter on the control parameter(s), the amplitude of this feedback being tuned by the spatial correlation length I. The self-organized nature of the criticality stems from the fact that the limit is attracting the non-linear feedback dynamics. It is applied to known self-organized critical systems such as « sandpile » models as well as to a simple dynamical generalization of the percolation model. Using this feedback mechanism, it is possible in principle to convert standard « unstable » critical phase transitions into self-organized critical dynamics, thereby enlarging considerably the number of models presenting SOC. These ideas are illustrated on the 2D Ising model and the values of the various « avalanche» exponents are expressed in terms of the static and dynamic Ising critical exponents.
Of Disasters and Dragon Kings: A Statistical Analysis of Nuclear Power Incidents and Accidents. Spencer Wheatley, Benjamin Sovacool, Didier Sornette, Risk Analysis, Volume 37, Issue 1. January 2017 Pages 99–115.
We perform a statistical study of risk in nuclear energy systems. This study provides and analyzes a data set that is twice the size of the previous best data set on nuclear incidents and accidents, comparing three measures of severity: the industry standard International Nuclear Event Scale, the Nuclear Accident Magnitude Scale of radiation release, and cost in U.S. dollars. The rate of nuclear accidents with cost above 20 MM 2013 USD, per reactor per year, has decreased from the 1970s until the present time. Along the way, the rate dropped significantly after Chernobyl (April 1986) and is expected to be roughly stable around a level of 0.003, suggesting an average of just over one event per year across the current global fleet. The distribution of costs appears to have changed following the Three Mile Island major accident (March 1979). The median cost became approximately 3.5 times smaller, but an extremely heavy tail emerged, being well described by a Pareto distribution with parameter α = 0.5–0.6. For instance, the cost of the two largest events, Chernobyl and Fukushima (March 2011), is equal to nearly five times the sum of the 173 other events. We also document a significant runaway disaster regime in both radiation release and cost data, which we associate with the “dragon-king” phenomenon.
Slaying dragon-kings could prevent financial crashes and Using Chaos Theory to Predict and Prevent Catastrophic ‘Dragon King’ Events
Predictability and Suppression of Extreme Events in a Chaotic System, Hugo L. D. de S. Cavalcante, Marcos Oriá, Didier Sornette, Edward Ott, and Daniel J. Gauthier. Phys. Rev. Lett. 111, 198701 – Published 4 November 2013
In many complex systems, large events are believed to follow power-law, scale-free probability distributions so that the extreme, catastrophic events are unpredictable. Here, we study coupled chaotic oscillators that display extreme events. The mechanism responsible for the rare, largest events makes them distinct, and their distribution deviates from a power law. On the basis of this mechanism identification, we show that it is possible to forecast in real time an impending extreme event. Once forecasted, we also show that extreme events can be suppressed by applying tiny perturbations to the system.
Black Swan, Dragon King, Greek Tragedy – Lessons from a “Diplomatic Debate” - "In May 2014, there was a very stimulating ETH-sponsored debate between Nassim Taleb and Didier Sornette which threw further light on their “Diametrically Opposite Approaches to Risk & Predictability”, so the title of the meeting. "
posted by the man of twists and turns (9 comments total) 46 users marked this as a favorite
 
Unexpected losses produced by Dragon Kings are known colloquially as having "taken an arrow to the knee."
posted by leotrotsky at 4:14 AM on February 25, 2017 [5 favorites]


Just a bunch of poorly known bifurcations.
posted by kadmilos at 5:05 AM on February 25, 2017 [1 favorite]


Yes but what about Scorpion Kings
posted by grumpybear69 at 6:46 AM on February 25, 2017 [2 favorites]


Like I appreciate the attempt to say "there's no such thing as normal" but I really do think the idea that we can infer similarities in organizing principles from similarities in specific summary statistics is basically data phrenology.
posted by PMdixon at 6:53 AM on February 25, 2017 [8 favorites]


What is the equivalent of a rat king? Is it now? Are we in a rat king event?

Goddammit.

I look forward to learning something from this tremendous post, but I confess that I will be looking for theories about the inevitable product of decades of ratfucking the entire time.
posted by schadenfrau at 7:00 AM on February 25, 2017 [4 favorites]


What made the 2008 crash so horrible was that the rising housing market of 2002-2005 was serving as a money turbo throwing off serious cash to tens of millions of households, and when the valuations stopped increasing in 2006 the specuvestors were going to default, taking down the entire housing market with them.

And once the housing market fell, so would the financial system, since there were TRILLIONS of suicide loans on the books by late 2007, and AIG et al. were making promises that their resources couldn't match.

https://fred.stlouisfed.org/graph/?g=cQ1Q

is the graph of mortgage rates (blue) vs real (2016 dollars) annual per-capita mortgage debt take-on.

The rate drops of 2002-2004 enabled all homeowners to refi their existing loans and either take equity out as cash, extend their mortgage out again, and/or enjoy a lower payment due to the much lower iterest rate.

Lower rates and the Bush tax cuts of 2001-2003 were twin accelerants to the housing market, and the third was the rise of liberalized -- risky -- lending, with the popularity of 80/20 financing, negative-am financing, people getting qualified on the teaser rate of ARMs, stated-income, etc etc etc. The fourth accelerant was that there was a ready pool of cash looking for yields [thanks to the 'global saving glut' result of 1990s monetary expansion], and Wall Street firms willing and able to take the mortgages and create the derivatives that hid the risk (thanks to the bond ratings agencies also in on the game) and made them money.

When the housing market bubbles, watch out. It's an immense stimulus, both for local economies and the macro.

During the 2004-2007 good times it giving us a flow of ~$4,000 per adult per year on average. When that flow stopped, so went the Bush Economy.
posted by Heywood Mogroot III at 9:01 AM on February 25, 2017 [6 favorites]


we show that it is possible to forecast in real time an impending extreme event. Once forecasted, we also show that extreme events can be suppressed by applying tiny perturbations to the system.

All too often, when you manage things with "tiny perturbations" rather than basic structural changes, you don't so much prevent problems as stave them off and magnify their eventuality enormously into true unstoppability; such as we ought to have learned by suppressing all forest fires, using grid interties to cope with small power blackouts, managing the Mississippi with levees, and etc. -- and as we are about to learn with a crushing finality as we allow human population to increase far beyond anything approaching sustainability.
posted by jamjam at 11:46 AM on February 25, 2017 [3 favorites]


Most forest fires start as tiny perturbations and grow enormous only through the kind of positive feedback loop Sornette attributes to dragon kings -- and stopping such a tiny fire would itself, I suppose, count as a tiny perturbation.
posted by jamjam at 10:16 PM on February 25, 2017


Homeostasis preserves life itself by tiny perturbations that only postpone the inevitable death. Some further argument against the practice is needed to convince me.
posted by clew at 11:53 AM on February 26, 2017 [2 favorites]


« Older “...the dogs run on about ten acres of her...   |   Online art community Deviantart bought by Wix.com... Newer »


This thread has been archived and is closed to new comments