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49
Why stock market crash
, 2003
"... The young science of complexity, which studies systems as diverse as the human body, the earth and the universe, offers novel insights on the question raised in the title. The science of complexity explains largescale collective behavior, such as wellfunctioning capitalistic markets, and also pre ..."
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Cited by 107 (13 self)
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The young science of complexity, which studies systems as diverse as the human body, the earth and the universe, offers novel insights on the question raised in the title. The science of complexity explains largescale collective behavior, such as wellfunctioning capitalistic markets, and also predicts that financial crashes and depressions are intrinsic properties resulting from the repeated nonlinear interactions between investors. Applying concepts and methods from complex theory and statistical physics, we have developed mathematical measures to successfully predict the emergence and development of speculative bubbles as well as depressions. This essay attempts to capture and extend the essence of the book with the same title published in January 2003 by Princeton University Press. Recent novelties and live predictions are available at
Large Stock Market Price Drawdowns Are Outliers
 Journal of Risk
, 2000
"... Drawdowns (loss from the last local maximum to the next local minimum) are essential aspects of risk assessment in investment management. They o#er a more natural measure of real market risks than the variance or other cumulants of daily (or some other fixed time scale) distributions of returns. Her ..."
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Cited by 31 (8 self)
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Drawdowns (loss from the last local maximum to the next local minimum) are essential aspects of risk assessment in investment management. They o#er a more natural measure of real market risks than the variance or other cumulants of daily (or some other fixed time scale) distributions of returns. Here, we extend considerably our previous analysis by analyzing the major financial indices, the major currencies, gold, the twenty largest U.S. companies in terms of capitalisation as well as nine others chosen randomly. We find for the major financial markets that approximately 98% of the distributions of drawdowns is wellrepresented by an exponential (or a minor modification of it with a slightly fatter tail), while the largest to the few ten largest drawdowns are occurring with a significantly larger rate than predicted by the exponential: the largest drops thus constitute genuine outliers. This is confirmed by extensive testing on surrogate data, which unambiguously show that large stock ...
The US 20002002 market descent: How much longer and deeper? Quantitative Finance
"... A remarkable similarity in the behavior of the US S&P500 index from 1996 to August 2002 and of the Japanese Nikkei index from 1985 to 1992 (11 years shift) is presented, with particular emphasis on the structure of the bearish phases. Extending a previous analysis of Johansen and Sornette [1999, ..."
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Cited by 26 (4 self)
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A remarkable similarity in the behavior of the US S&P500 index from 1996 to August 2002 and of the Japanese Nikkei index from 1985 to 1992 (11 years shift) is presented, with particular emphasis on the structure of the bearish phases. Extending a previous analysis of Johansen and Sornette [1999, 2000] on the Nikkei index “antibubble ” based on a theory of cooperative herding and imitation working both in bullish as well as in bearish regimes, we demonstrate the existence of a clear signature of herding in the decay of the S&P500 index since August 2000 with high statistical significance, in the form of strong logperiodic components. We offer a detailed analysis of what could be the future evolution of the S&P500 index over the next two years, according to three versions of the theory: we expect an overall continuation of the bearish phase, punctuated by local rallies; we predict an overall increasing market until the end of the year 2002 or at the beginning of 2003 (first quarter); we predict a strong following descent (with maybe one or two severe up and downs in the middle) which stops during the first semester of 2004. After this strong minimum, the market is expected to recover. Beyond, our prediction horizon is made fuzzy by the possible effect of additional nonlinear collective effects
Characterization of large price variations in financial markets
 Proceedings of Econophysics conference
, 2002
"... Statistics of drawdowns (loss from the last local maximum to the next local minimum) plays an important role in risk assessment of investment strategies. As they incorporate higher (> two) order correlations, they offer a better measure of real market risks than the variance or other cumulants of ..."
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Cited by 16 (3 self)
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Statistics of drawdowns (loss from the last local maximum to the next local minimum) plays an important role in risk assessment of investment strategies. As they incorporate higher (> two) order correlations, they offer a better measure of real market risks than the variance or other cumulants of daily (or some other fixed time scale) of returns. Previous results have shown that the vast majority of drawdowns occurring on the major financial markets have a distribution which is wellrepresented by a stretched exponential, while the largest drawdowns are occurring with a significantly larger rate than predicted by the bulk of the distribution and should thus be characterized as outliers [1, 2]. In the present analysis, the definition of drawdowns is generalised to coarsegrained drawdowns or socalled ǫdrawdowns and a link between such ǫoutliers and preceding logperiodic power law bubbles previously identified [3] The characterization of stock market moves and especially large drops, i.e., large negative moves in the price, are of profound importance to risk management. A drawdown is defined as a persistent decrease in the price over consecutive days. A drawdown is thus the cumulative loss from the last maximum to the next minimum of the price, specifically the daily close in the analysis presented here. Since the definition
Evidence of Intermittent Cascades from Discrete Hierarchical Dissipation
 in Turbulence, Physica D 165
, 2002
"... We present the results of a search of logperiodic corrections to scaling in the moments of the energy dissipation rate in experiments at high Reynolds number ( ≈ 2500) of threedimensional fully developed turbulence. A simple dynamical representation of the RichardsonKolmogorov cartoon of a cascade ..."
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Cited by 16 (6 self)
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We present the results of a search of logperiodic corrections to scaling in the moments of the energy dissipation rate in experiments at high Reynolds number ( ≈ 2500) of threedimensional fully developed turbulence. A simple dynamical representation of the RichardsonKolmogorov cartoon of a cascade shows that standard averaging techniques erase by their very construction the possible existence of logperiodic corrections to scaling associated with a discrete hierarchy. To remedy this drawback, we introduce a novel “canonical ” averaging that we test extensively on synthetic examples constructed to mimick the interplay between a weak logperiodic component and rather strong multiplicative and phase noises. Our extensive tests confirm the remarkable observation of statistically significant logperiodic corrections to scaling, with a prefered scaling ratio for length scales compatible with the value γ = 2. A strong confirmation of this result is provided by the identification of up to 5 harmonics of the fundamental logperiodic undulations, associated with up to 5 levels of the underlying hierarchical dynamical structure. A natural interpretation of our results is that the RichardsonKolmogorov mental picture of a cascade becomes a realistic description if one allows for intermittent births and deaths of discrete cascades at varying scales. 1
Statistical Significance of periodicity and logperiodicity with heavytailed correlated Noise
, 2001
"... We estimate the probability that random noise, of several plausible standard distributions, creates a false alarm that a periodicity (or logperiodicity) is found in a time series. The solution of this problem is already known for independent Gaussian distributed noise. We investigate more general s ..."
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Cited by 16 (9 self)
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We estimate the probability that random noise, of several plausible standard distributions, creates a false alarm that a periodicity (or logperiodicity) is found in a time series. The solution of this problem is already known for independent Gaussian distributed noise. We investigate more general situations with nonGaussian correlated noises and present synthetic tests on the detectability and statistical significance of periodic components. A periodic component of a time series is usually detected by some sort of Fourier analysis. Here, we use the Lomb periodogram analysis which is suitable and outperforms Fourier transforms for unevenly sampled time series. We examine the falsealarm probability of the largest spectral peak of the Lomb periodogram in the presence of powerlaw distributed noises, of shortrange and of longrange fractionalGaussian noises. Increasing heavytailness (respectively correlations describing persistence) tends to decrease (respectively increase) the falsealarm probability of finding a large spurious Lomb peak. Increasing antipersistence tends to decrease the falsealarm probability. We also study the interplay between heavytailness and longrange correlations. In order to fully determine if a Lomb peak signals a genuine rather than a spurious periodicity, one should
Financial Bubbles, Real Estate bubbles, Derivative Bubbles, and the Financial and Economic Crisis. URL http://arxiv.org/abs/0905.0220. To appear
 in the Proceedings of APFA7. 16/17
, 2009
"... Abstract The financial crisis of 2008, which started with an initially welldefined epicenter focused on mortgage backed securities (MBS), has been cascading into a global economic recession, whose increasing severity and uncertain duration has led and is continuing to lead to massive losses and dam ..."
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Cited by 14 (6 self)
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Abstract The financial crisis of 2008, which started with an initially welldefined epicenter focused on mortgage backed securities (MBS), has been cascading into a global economic recession, whose increasing severity and uncertain duration has led and is continuing to lead to massive losses and damage for billions of people. Heavy central bank interventions and government spending programs have been launched worldwide and especially in the USA and Europe, with the hope to unfreeze credit and boltster consumption. Here, we present evidence and articulate a general framework that allows one to diagnose the fundamental cause of the unfolding financial and economic crisis: the accumulation of several bubbles and their interplay and mutual reinforcement has led to an illusion of a “perpetual money machine ” allowing financial institutions to extract wealth from an unsustainable artificial process. Taking stock of this diagnostic, we conclude that many of the interventions to address the socalled liquidity crisis and to encourage more consumption are illadvised and even dangerous, given that precautionary reserves were not accumulated in the “good times ” but that huge liabilities were. The most “interesting ” present times constitute unique opportunities but also great challenges, for which we offer a few recommendations.
Endogenous versus Exogenous Crashes in Financial Markets
 SUBMITTED TO JOURNAL OF ECONOMIC DYNAMICS AND CONTROL
, 2008
"... In a series of papers based on analogies with statistical physics models, we have proposed that most financial crashes are the climax of socalled logperiodic power law signatures (LPPS) associated with speculative bubbles ..."
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Cited by 14 (5 self)
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In a series of papers based on analogies with statistical physics models, we have proposed that most financial crashes are the climax of socalled logperiodic power law signatures (LPPS) associated with speculative bubbles
Predictability of large future changes in major financial indices
 in press in the International Journal of Forecasting (2005) (http://arXiv.org/abs/condmat/0304601
"... Predictability of large future changes in major financial indices We present a systematic algorithm testing for the existence of collective selforganization in the behavior of agents in social systems, with a concrete empirical implementation on the Dow Jones Industrial Average index (DJIA) over th ..."
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Cited by 14 (2 self)
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Predictability of large future changes in major financial indices We present a systematic algorithm testing for the existence of collective selforganization in the behavior of agents in social systems, with a concrete empirical implementation on the Dow Jones Industrial Average index (DJIA) over the 20th century and on Hong Kong Hang Seng composite index (HSI) since 1969. The algorithm combines ideas from critical phenomena, the impact of agents ’ expectation, multiscale analysis and the mathematical method of pattern recognition of sparse data. Trained on the three major crashes in DJIA of the century, our algorithm exhibits a remarkable ability for generalization and detects in advance 8 other significant drops or changes of regimes. An application to HSI gives promising results as well. The results are robust with respect to the variations of the recognition algorithm. We quantify the prediction procedure with error diagrams.