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Dragon-Kings: Mechanisms, Criticality” Introduced in Bak Et Al

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Dragon-Kings: Mechanisms, Criticality” Introduced in Bak Et Al future event cannot be forecasted in advance. This is for instance the view espoused by P. Bak (1996) in the conceptual framework called “Self-organized Dragon-kings: mechanisms, criticality” introduced in Bak et al. (1987). This concept has become popular since Nassim Taleb’s statistical methods and empirical book “The Black Swan” (2007). This view is evidence particularly pessimistic, and even alarming if true, as it casts a strong doubt on possibilities of precise hazard a,* b prediction, with all the societal consequences. In our Didier Sornette , Guy Ouillon mind, it is even dangerous as it promotes an attitude of a D-MTEC, and Department of Earth Sciences, ETH Zürich Kreuzplatz 5,CH-8032 Zürich, Switzerland irresponsibility: in a world where catastrophes (in (e-mail: [email protected]) human-controlled activities, for instance) are pure b Lithophyse, 4 rue de l'Ancien Sénat, 06300 Nice, France surprises, no one can be responsible. In contrast, the (e-mail: [email protected]) concept of dragon-kings, if their occurrences can be diagnosed ex-ante, brings back responsibility and accountability. Are extreme events really due to the same Abstract This introductory article presents the special Discussion and mechanisms? Sornette (2009) argues that the power Debate volume “From black swans to dragon-kings, is there life law paradigm may miss an important population of beyond power laws?” We summarize and put in perspective the events that he refers to as “dragon-kings”. contributions into three main themes: (i) mechanisms for Dragon-kings are defined as extreme events that do dragon-kings, (ii) detection of dragon-kings and statistical tests not belong to the same population as the other events, and (iii) empirical evidence in a large variety of natural and in a precise quantitative and mechanistic sense that social systems. Overall, we are pleased to witness significant advances both in the introduction and clarification of will be developed below. The hypothesis articulated in underlying mechanisms and in the development of novel (Sornette, 2009) is that dragon-kings appear as a result efficient tests that demonstrate clear evidence for the presence of amplifying mechanisms that are not necessary fully of dragon-kings in many systems. However, this positive view active for the rest of the population. This gives rise to should be balanced by the fact that this remains a very delicate specific properties and signatures that may be unique and difficult field, if only due to the scarcity of data as well as characteristics of dragon-kings. the extraordinary important implications with respect to hazard assessment, risk control and predictability. For instance, in hydrodynamic turbulence, dragon-kings correspond to coherent structures or solitons developing in an otherwise incoherent noise Keywords: dragon-kings, black swans, power laws, extremes, background (L'vov et al., 2001). Dragon-kings could predictability, statistical tests, mechanisms be related in some cases to critical transitions of the underlying dynamics. In such cases, extreme events would be somewhat predictable from the observation 1. Introduction of the spatio-temporal dynamics of preceding small Many phenomena in the physical, natural, economic events. and social sciences can be characterized by power-law There is growing evidence that some of the statistics, for which there are many different mechanisms that have been documented to be at the mechanisms (Mitzenmacher, 2003; Newman, 2005; origin of power law distributions may, under slight Sornette, 2006). Power-law (i.e. self-similar) changes of conditions and constraints, lead to distributions of the sizes of events suggest that log-normal distributions (Saichev et al., 2009) or to mechanisms of nucleation and growth dynamics distributions with two regimes, such as dragon-kings, remain the same over the whole spectrum of relevant due to a transition from a kind of self-organized spatial and temporal scales. According to this critical regime to a synchronized phase under paradigm, small, large and extreme events belong to increasing coupling strengths between constitutive the same population, the same distribution, and reflect elements (Sornette et al., 1994, 1995; Osorio et al., the same underlying mechanism(s). Major 2010). catastrophes are just events that started small and did The term ‘dragon’ stresses the idea that the not stop growing to develop into large or extreme mythological “animal” that a dragon embodies is sizes. endowed with mystical supernatural powers above Following that reasoning, a majority of the those of the rest of the animal kingdom. The term scientific community considers those events as ‘king’ (Laherrère and Sornette, 1998), refers to the unpredictable, in the sense that the final size of a fact that kings in certain countries are much more wealthy that the wealthiest inhabitants of their *Corresponding author. countries in a precise sense: while the wealth E-mail address: [email protected] distribution over the whole population excluding the 2 Guy Ouillon and Didier Sornette king obeys the well-known power law Pareto dragon-kings occurrence in a large variety of natural distribution, the king (including his family) is an and social systems (Section 4). Section 5 discusses the “outlier'', with a wealth many times larger than potential implications of the dragon-kings concept in predicted by the extrapolation of the Pareto the predictability of major events. Section 6 calls for a distribution. This “king” regime may result from new research and operational implementation of cumulative historical developments, i.e., specific dragon-king simulators to endow decision makers with geo-political-cultural mechanisms that have enhanced the tools to address the daunting challenges of the the special king status in the wealth distribution (and future crises. also in other associated attributes that also contributed to the accumulation of wealth by the royal family). 2. Mechanisms for dragon-kings The dragon-king hypothesis has first been alluded to with the introduction of the term ‘king’ by 2.1 Synthetic dragon-kings in random walks with Laherrère and Sornette (1998). It was then developed long-range dependence by Johansen and Sornette (1998a; 2001), who Werner et al. (2011) construct synthetic examples discovered dragon-kings in the distribution of where dragon-kings can be detected in the financial drawdowns, proposed as a pertinent measure auto-correlation function of complex time series of the of risks (at that time, they referred to these random walk type. To make the problem relevant to dragon-kings as ‘outliers’; this term is now abandoned complex systems that often exhibit long-range to distinguish the dragon-kings, considered to be temporal dependence, they use the hierarchical important parts of the dynamics, from the notion of Weierstrass - Mandelbrot Continuous - time Random statistical ‘outliers’, which usually refers to data that Walk (WM-CTRW) model. The first type of must be discarded because anomalous and surmised to dragon-king corresponds to a sustained drift whose be artifacts). Chapter 3 of (Sornette, 2003) provides a duration time is much longer than that of any other general review on the evidence for and importance of event. This first abnormal event thus results from a dragon-king, with an emphasis on their implication for mechanism that is similar in spirit to the abnormally financial market risks. A synthesis of the concept and large deterministic growth of Golosovsky and proposed applications to seven different systems can Solomon (2011) of stochastic proportional growth that be found in (Sornette, 2009; Satinover and Sornette, is explained below. The second type of dragon-king 2010). takes the form of an abrupt shock whose amplitude The present special volume contains a series of velocity is much larger than those corresponding to articles that examine three classes of questions any other event. Werner et al. quantify the durations of underlying the concept of dragon-kings: the abnormal drifts and the amplitudes of the abnormal (i) What are their mechanisms? shocks that lead to clearly differentiated signatures in (ii) How to detect them? With what methods the tail of the velocity autocorrelation function of the and/or statistical tests? persistent random walks, or in other words, to clearly (iii) What is the empirical evidence for visible dragon-kings. dragon-kings in various natural and social systems? 2.2 Abnormal deterministic grow leading to A fourth question on the predictability of dragon-kings dragon-kings in a population following stochastic is mostly left aside here. We briefly touch this subject proportional growth. at the end of this introductory article and refer to Golosovsky and Solomon (2011) study the distribution Sornette (2002; 2003; 2009) for progresses in this of the citations up to July 2008 of 418,438 Physics direction. papers published between 1980 and 1989. They show The systems, in which articles in the present that the lognormal distribution model is adequate up to special volume investigate the possible existence of about 400 citations. This means that the number of dragon-kings, include: geosciences (earthquakes, Physics papers with citations less than about 400 volcanic eruptions, landslides, floods), economics citations have a frequency of occurrence well (financial drawdowns, distribution of wealth), social represented by the lognormal law. In contrast, Physics sciences (distribution of city sizes), medicine papers with citations
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