The scientific study of complex systems has transformed a wide range of disciplines in recent years, enabling researchers in both the natural and social sciences to model and predict phenomena as diverse as earthquakes, global warming, demographic patterns, financial crises, and the failure of materials. In this book, Didier Sornette boldly applies his varied experience in these areas to propose a simple, powerful, and general theory of how, why, and when stock markets crash. Most attempts to explain market failures seek to pinpoint triggering mechanisms that occur hours, days, or weeks before the collapse. Sornette proposes a radically different view: the underlying cause can be sought months and even years before the abrupt, catastrophic event in the build-up of cooperative speculation, which often translates into an accelerating rise of the market price, otherwise known as a "bubble." Anchoring his sophisticated, step-by-step analysis in leading-edge physical and statistical modeling techniques, he unearths remarkable insights and some predictions--among them, that the "end of the growth era" will occur around 2050. Sornette probes major historical precedents, from the decades-long "tulip mania" in the Netherlands that wilted suddenly in 1637 to the South Sea Bubble that ended with the first huge market crash in England in 1720, to the Great Crash of October 1929 and Black Monday in 1987, to cite just a few. He concludes that most explanations other than cooperative self-organization fail to account for the subtle bubbles by which the markets lay the groundwork for catastrophe. Any investor or investment professional who seeks a genuine understanding of looming financial disasters should read this book. Physicists, geologists, biologists, economists, and others will welcome Why Stock Markets Crash as a highly original "scientific tale," as Sornette aptly puts it, of the exciting and sometimes fearsome--but no longer quite so unfathomable--world of stock markets.
The history of mankind is a story of ascent to unprecedented levels of comfort, productivity and consumption, enabled by the increased mastery of the basic reserves and flows of energy. This miraculous trajectory is confronted by the consensus that anthropogenic emissions are harmful and must decrease, requiring de-carbonization of the energy system. The mature field of indicator-based sustainability assessment provides a rigorous systematic framework to balance the pros and cons of the various existing energy technologies using lifecycle assessments and weighting criteria covering the environment, economy, and society, as the three pillars of sustainability. In such a framework, nuclear power is ranked favorably, but since emphasis is often placed on radioactive wastes and risk aversion, renewables are usually ranked top. However, quantifying the severity of the consequences of nuclear accidents on a rough integral cost basis and balancing severity with low core-damage accident probabilities indicates that the average external cost of such accidents is similar to that of modern renewables, and far less than carbon-based energy. This book formulates the overall goal and associated unprecedented demanding criteria of taming nuclear risks by excluding mechanisms that lead to serious accidents and avoiding extremely long stewardship times as far as possible, by design. It reviews the key design features of nuclear power generation, paving the way for the exploration of radically new combinations of technologies to come up with “revolutionary” or even “exotic” system designs. The book also provides scores for the selected designs and discusses the high potential for far-reaching improvements, with small modular lines of the best versions as being most attractive. Given the ambition and challenges, the authors call for an urgent increase in funding of at least two orders of magnitude for a broad international civilian “super-Apollo” program on nuclear energy systems. Experience indicates that such investments in fundamental technologies enable otherwise unattainable revolutionary innovations with massive beneficial spillovers to the private sector and the public for the next generations.
Some of the major industrial disasters could have been prevented. When the facts of what happened are established, their stories share a common thread: before things spiralled out of control, there were workers at the affected sites who knew that the situation was dangerous, and could become catastrophic unless immediate action was taken. But tragically, nobody dared to tell the decision-makers who could have authorized that action. With no idea of the risks they were taking, the people in charge continued as normal... and disaster struck. Because vital information about risks could not flow freely from the shop floor to the director’s office, the crucial decisions were not made in time. This observation has been documented in the following major technological accidents: Challenger space shuttle explosion (USA, 1986); Chernobyl nuclear plant disaster (USSR, 1986); Deepwater Horizon oil spill (USA, 2010); Fukushima-1 nuclear power plant disaster (Japan, 2011); and numerous other industrial disasters. After accidents like these, losses and costs for dealing with the consequences are often hundreds — or even thousands — of times greater than the finances that would have been required to deal with the risks when they were first recognized. This handbook is about how to transform the way large critical infrastructure companies communicate about safety and technological risks. It aims to support senior managers to get the information they need from their subordinates concerning the risks they are facing, in order to prevent accidents before it is too late. The recommendations in this handbook are based on interviews with 100 executives at various levels, working in 65 critical infrastructure companies around the world, in power, oil and gas, metals, chemicals and petrochemicals, mining and other industries. The recommendations of these leaders were also tested in the pilot project, in an industrial company which is the world leader in its sector. More than 400 managers at various levels of the corporate hierarchy, and employees at several of the company’s industrial plants, took part in the project. This open access handbook is written for the owners, senior managers, and industrial safety directors of critical infrastructure companies.
This book discusses the risks of information concealment in the context of major natural or industrial disasters – offering detailed descriptions and analyses of some 25 historical cases (Three Mile Island nuclear accident, Bhopal disaster, Challenger Space Shuttle explosion, Chernobyl nuclear disaster, Deepwater Horizon oil spill, Fukushima-Daiichi nuclear disaster, Enron’s bankruptcy, Subprime mortgage crisis, Worldwide Spanish flu and SARS outbreaks, etc.) and applying these insights to selected on-going cases where such information concealment is suspected. Some successful examples of preventive anti-concealment practice are also presented. In the book, the term ‘concealment’ is used to represent the two distinct behaviors uncovered in the investigations: (i) facts and information about an organization and its functioning being hidden from those that need them – here the concealment can be due to various factors, such as complexity and miscommunication, to name but two – and (ii) the conscious and deliberate action of keeping important information secret or misrepresenting it. This second meaning makes up a surprisingly important part of the evidence presented. Accordingly, emphasis has been put on this second aspect and the approach is more pragmatic than academic, remaining focused on evidence-based practical and useful factors. It raises awareness and provides valuable lessons for decision- makers, risk specialists and responsible citizens alike. This work is also intended as a fact-based reference work for future academic and scholarly investigations on the roots of the problem, in particular regarding any psychological or sociological modeling of human fallibility.
This book explores the major differences between the kinds of risk encountered in different sectors of industry - production (including agriculture) and services - and identifies the main features of accidents within different industries. Because of these differences, unique risk-mitigation measures will need to be implemented in one industry that cannot be implemented in another, leading to large managerial differences between these broad economic sectors. Based on the analysis of more than 500 disasters, accidents and incidents - around 230 cases from the production sector and around 280 cases from the service sector - the authors compare the risk response actions appropriate within different sectors, and establish when and how it is possible to generalize the experience of dealing with risks in any given industry to a wider field of economic activity. This book is mainly intended for executives, strategists, senior risk managers of enterprise-wide organizations and risk management experts engaged in academic or consulting work. By setting out clearly the sector differences in risk management, the authors aim to improve the practice of general risk assessment with regard to identifying and prioritizing risks, and of risk control with regard to planning appropriate mitigation measures.
After a major disaster, when investigators are piecing together the story of what happened, a striking fact often emerges: before disaster struck, some people in the organization involved were aware of dangerous conditions that had the potential to escalate to a critical level. But for a variety of reasons, this crucial information did not reach decision-makers. So, the organization moved ever closer to catastrophe, effectively unaware of the possible threat—despite the fact that some of its employees could see it coming. What is the problem with communication about risk in an organization, and why does this problem exist? What stops people in organizations or project teams from freely reporting and discussing critical risks? This book seeks to answer these questions, starting from a deep analysis of 20 disasters where the concealment of risks played a major part. These case studies are drawn from around the world and span a range of industries: civil nuclear power, coal, oil and gas production, hydropower energy, metals and mining, space exploration, transport, finance, retail manufacturing and even the response of governments to wars, famines and epidemics. Together, case studies give an insight into why people hesitate to report risks—and even when they do, why their superiors often prefer to ignore the news. The book reviews existing research on the challenges of voice and silence in organizations. This helps to explain more generally why people dread passing on bad news to others—and why in the workplace they prefer to keep quiet about unpleasant facts or potential risks when they are talking to superiors and colleagues. The discussion section of the book includes important examples of concealment within the Chinese state hierarchy as well as by leading epidemiologists and governments in the West during the novel coronavirus outbreak in Wuhan in 2019-2020. The full picture of the very early stage of the COVID-19 pandemic remains unclear, and further research is obviously needed to better understand what motivated some municipal, provincial and national officials in China as well as Western counterparts to obfuscate facts in their internal communications about many issues associated with the outbreak.
From 1966 to 1976, four large earthquakes shook the Bohai Bay rift basin of Northeast China. This prompted the Chinese to launch one of the worldâ (TM)s largest social and science experiments into earthquake prediction that would engage tens of thousands of common people. The climax of this came in February 1975 where a prediction was made hours before the Haicheng earthquake struck. Evacuation of the city of Yingkou and some rural districts saved thousands of lives. The Chinese were jubilant, believing they had cracked the earthquake prediction conundrum. Eighteen months later, however, on the 28th July, 1976, jubilation turned to despair when a great earthquake flattened the large industrial city of Tangshan resulting in 250,000 to 650,000 casualties. This book describes the geological, technical, political and sociological backgrounds to the Haicheng prediction success and the Tangshan prediction failure. Ahead of the Tangshan earthquake, Chinese seismologists had accumulated significant information that suggested an earthquake was imminent and came close to making a prediction. With improved knowledge and vastly improved ability to accumulate, consolidate and analyse data, this book suggests that Tangshan could have been predicted today using techniques developed in China in that epic decade of discovery. Building on these insights, it also offers a viable future pathway towards earthquake predictions that combines the insights and organisation of the 1966-1976 Chinese prediction program with modern technologies, in order to facilitate data gathering, interpretation and sharing.
Zipf’s law is one of the few quantitative reproducible regularities found in e- nomics. It states that, for most countries, the size distributions of cities and of rms (with additional examples found in many other scienti c elds) are power laws with a speci c exponent: the number of cities and rms with a size greater thanS is inversely proportional toS. Most explanations start with Gibrat’s law of proportional growth but need to incorporate additional constraints and ingredients introducing deviations from it. Here, we present a general theoretical derivation of Zipf’s law, providing a synthesis and extension of previous approaches. First, we show that combining Gibrat’s law at all rm levels with random processes of rm’s births and deaths yield Zipf’s law under a “balance” condition between a rm’s growth and death rate. We nd that Gibrat’s law of proportionate growth does not need to be strictly satis ed. As long as the volatility of rms’ sizes increase asy- totically proportionally to the size of the rm and that the instantaneous growth rate increases not faster than the volatility, the distribution of rm sizes follows Zipf’s law. This suggests that the occurrence of very large rms in the distri- tion of rm sizes described by Zipf’s law is more a consequence of random growth than systematic returns: in particular, for large rms, volatility must dominate over the instantaneous growth rate.
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