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Why stock markets crash: critical events in complex financial systems

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Bibliographische Detailangaben
Beteilige Person:	Sornette, Didier (VerfasserIn)
Format:	Buch
Sprache:	Englisch
Veröffentlicht:	Princeton [u.a.] Princeton University Press 2004
Ausgabe:	5. print., and 1. paperback print.
Schriftenreihe:	Princeton paperbacks
Schlagwörter:	Geschichte Mathematisches Modell Critical phenomena (Physics) Financial crises > Forecasting Financial crises > History Financial crises > Mathematical models Stock exchanges Börse Finanzwirtschaft Krise Währungskrise USA
Links:	http://www.loc.gov/catdir/toc/prin032/2002024336.html http://www.loc.gov/catdir/description/prin031/2002024336.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012948364&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Beschreibung:	Literaturverz. S [397] - 418. - Hier auch später erschienene, unveränderte Nachdrucke
Umfang:	XX, 421 S. Ill., graph. Darst., Kt.
ISBN:	0691118507 0691096309 9780691118505

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Datensatz im Suchindex

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adam_text	Contents xiii Preface Chapter 1 3 What Are Crashes, and Why FINANCIAL CRASHES: Do We Care? WHAT, HOW, WHY, AND WHEN? 5 The Crash of October 1987 3 7 Historical Crashes 7 The Tulip Mania 9 The South Sea Bubble 12 The Great Crash of October 1929 15 Extreme Events in Complex Systems 20 Is Prediction Possible? A Working Hypothesis Chapter 2 27 The Basics FUNDAMENTALS OF 27 Price Trajectories FINANCIAL MARKETS 30 Return Trajectories 26 33 Return Distributions and Return Correlation 38 The Efficient Market Hypothesis and the Random Walk 38 The Random Walk VI CONTENTS 42 A Parable: How Information Is Incorporated in Prices, Thus Destroying Potential Free Lunches 45 Prices Are Unpredictable, or Are They? 47 Risk-Return Trade-Off Chapter 3 FINANCIAL CRASHES ARE OUTLIERS 49 Chapter 4 POSITIVE FEEDBACKS 81 49 What Are Abnormal Returns? 51 Drawdowns (Runs) 51 Definition of Drawdowns 54 Drawdowns and the Detection of Outliers 56 Expected Distribution of Normal Drawdowns 60 Drawdown Distributions of Stock Market Indices 60 The Dow Jones Industrial Average 62 The Nasdaq Composite Index 65 Further Tests 69 The Presence of Outliers Is a General Phenomenon 70 Main Stock Market Indices, Currencies, and Gold 73 Largest U.S. Companies 75 Synthesis 76 Symmetry-Breaking on Crash and Rally Days 77 Implications for Safety Regulations of Stock Markets 82 Feedbacks and Self-Organization in Economics 89 Hedging Derivatives, Insurance Portfolios, and Rational Panics 91 Herd Behavior and Crowd Effect 91 Behavioral Economics CONTENTS νπ 94 Herding 96 Empirical Evidence of Financial Analysts Herding 99 Forces of Imitation 99 It Is Optimal to Imitate When Lacking Information 104 Mimetic Contagion and the Urn Models 106 Imitation from Evolutionary Psychology 108 Rumors 111 The Survival of the Fittest Idea 112 Gambling Spirits 114 Anti-Imitation and Self-Organization 114 Why It May Pay to Be in the Minority 115 El-Farol s Bar Problem 117 Minority Games 118 Imitation versus Contrarian Behavior 121 Cooperative Behaviors Resulting from Imitation 122 The Ising Model of Cooperative Behavior 130 Complex Evolutionary AdaDtive Systems of Boundedly Rational Agents Chapter 5 134 What Is a Model? MODELING FINANCIAL 135 Strategy for Model Construction BUBBLES AND in Finance MARKET CRASHES 134 135 Basic Principles 136 The Principle of Absence of Arbitrage Opportunity 137 Existence of Rational Agents 139 Rational Bubbles and Goldstone Modes of the Price Parity Symmetry Breaking 140 Price Parity Symmetry Vlil CONTENTS 144 Speculation as Spontaneous Symmetry Breaking 148 Basic Ingredients of the Two Models 150 The Risk-Driven Model 150 Summary of the Main Properties of the Model 152 The Crash Hazard Rate Drives the Market Price 155 Imitation and Herding Drive the Crash Hazard Rate 162 The Price-Driven Model 162 Imitation and Herding Drive the Market Price 164 The Price Return Drives the Crash Hazard Rate 168 Risk-Driven versus Price-Driven Models Chapter 6 173 Critical Phenomena by Imitation on HIERARCHIES, Hierarchical Networks COMPLEX FRACTAL 173 The Underlying Hierarchical DIMENSIONS, AND Structure of Social Networks LOG-PERIODICITY 177 Critical Behavior in Hierarchical 171 Networks 181 A Hierarchical Model of Financial Bubbles 186 Origin of Log-Periodicity in Hierarchical Systems 186 Discrete Scale Invariance 188 Fractal Dimensions 192 Organization Scale by Scale: The Renormalization Group 192 Principle and Illustration of the Renormalization Group 195 The Fractal Weierstrass Function: A Singular Time-Dependent Solution of the Renormalization Group CONTENTS ι 198 Complex Fractal Dimensions and Log-Periodicity 208 Importance and Usefulness of Discrete Scale Invariance 208 Existence of Relevant Length Scales 209 Prediction 210 Scenarios Leading to Discrete Scale Invariance and Log-Periodicity 211 Newcomb-Benford Law of First Digits and the Arithmetic System 213 The Log-Periodic Law of the Evolution of Life? IX 217 Nonlinear Trend-Following versus Nonlinear Fundamental Analysis Dynamics 218 Trend Following: Positive Nonlinear Feedback and Finite-Time Singularity 220 Reversal to the Fundamental Value: Negative Nonlinear Feedback 223 Some Characteristics of the Price Dynamics of the Nonlinear Dynamical Model Chapter 7 228 autopsy of major 231 crashes: universal 236 exponents and log- periodicity 228 242 The Crash of October 1987 Precursory Pattern Aftershock Patterns 239 The Crash of October 1929 The Three Hong Kong Crashes of 1987, 1994, and 1997 242 The Hong Kong Crashes 246 The Crash of October 1997 and Its Resonance on the U.S. Market 254 Currency Crashes 259 The Crash of August 1998 263 Nonparametnc Test of Log-Periodicity CONTENTS 266 The Slow Crash of 1962 Ending the Tronies Boom 269 The Nasdaq Crash of April 2000 275 Antibubbles 276 The Bearish Regime on the Nikkei Starting from January 1, 1990 278 The Gold Deflation Price Starting in Mid-1980 279 Synthesis: Emergent Behavior of the Stock Market Chapter 8 281 BUBBLES, CRISES, AND CRASHES IN EMERGENT MARKETS 281 286 285 295 304 309 Speculative Bubbles in Emerging Markets Methodology Latin-American Markets Asian Markets The Russian Stock Market Correlations across Markets: Economic Contagion and Synchronization of Bubble Collapse 314 Implications for Mitigations of Crises Chapter 9 320 PREDICTION OF BUBBLES, CRASHES, AND ANTIBUBBLES 320 329 329 330 334 334 335 The Nature of Predictions How to Develop and Interpret Statistical Tests of Log-Periodicity First Guidelines for Prediction What Is the Predictive Power of Equation (15)? How Long Prior to a Crash Can One Identify the Log-Periodic Signatures? A Hierarchy of Prediction Schemes The Simple Power Law The Linear Log-Periodic Formula CONTENTS Xl 336 The Nonlinear Log-Periodic Formula 336 The Shank s Transformation on a Hierarchy of Characteristic Times ЪЪ1 Application to the October 1929 Crash 338 Application to the October 1987 Crash 338 Forward Predictions 339 Successful Prediction of the Nikkei 1999 Antibubble 342 Successful Prediction of the Nasdaq Crash of April 2000 342 The U.S. Market, December 1997 False Alarm 346 The U.S. Market, October 1999 False Alarm 346 Present Status of Forward Predictions 346 The Finite Probability That No Crash Will Occur during a Bubble 347 Estimation of the Statistical Significance of the Forward Predictions 347 Statistical Confidence of the Crash Roulette 349 Statistical Significance of a Single Successful Prediction via Bayes s Theorem 351 The Error Diagram and the Decision Process 352 Practical Implications on Different Trading Strategies Chapter 10 355 Stock Markets, Economics, 2050: the end of and Population THE GROWTH ERA? oc_ _ n .·,.,, . c 357 The Pessimistic Viewpoint of Natural Scientists 359 The Optimistic Viewpoint of Social Scientists CONTENTS 361 Analysis of the Faster-Than- Exponential Growth of Population, GDP, and Financial Indices 369 Refinements of the Analysis 369 Complex Power Law Singularities 371 Prediction for the Coming Decade 377 The Aging Baby Boomers 378 Related Works and Evidence 383 Scenarios for the Singularity 384 Collapse 389 Transition to Sustainability 393 Resuming Accelerating Growth by Overpassing Fundamental Barriers 395 The Increasing Propensity to Emulate the Stock Market Approach 397 References 419 Index
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spellingShingle	Sornette, Didier Why stock markets crash critical events in complex financial systems Geschichte Mathematisches Modell Critical phenomena (Physics) Financial crises Forecasting Financial crises History Financial crises Mathematical models Stock exchanges Börse (DE-588)4007502-3 gnd Finanzwirtschaft (DE-588)4017214-4 gnd Krise (DE-588)4033203-2 gnd Währungskrise (DE-588)4396352-3 gnd
subject_GND	(DE-588)4007502-3 (DE-588)4017214-4 (DE-588)4033203-2 (DE-588)4396352-3 (DE-588)4078704-7
title	Why stock markets crash critical events in complex financial systems
title_auth	Why stock markets crash critical events in complex financial systems
title_exact_search	Why stock markets crash critical events in complex financial systems
title_full	Why stock markets crash critical events in complex financial systems Didier Sornette
title_fullStr	Why stock markets crash critical events in complex financial systems Didier Sornette
title_full_unstemmed	Why stock markets crash critical events in complex financial systems Didier Sornette
title_short	Why stock markets crash
title_sort	why stock markets crash critical events in complex financial systems
title_sub	critical events in complex financial systems
topic	Geschichte Mathematisches Modell Critical phenomena (Physics) Financial crises Forecasting Financial crises History Financial crises Mathematical models Stock exchanges Börse (DE-588)4007502-3 gnd Finanzwirtschaft (DE-588)4017214-4 gnd Krise (DE-588)4033203-2 gnd Währungskrise (DE-588)4396352-3 gnd
topic_facet	Geschichte Mathematisches Modell Critical phenomena (Physics) Financial crises Forecasting Financial crises History Financial crises Mathematical models Stock exchanges Börse Finanzwirtschaft Krise Währungskrise USA
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