Why stock markets crash: critical events in complex financial systems
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Princeton [u.a.]
Princeton University Press
2004
|
| Edition: | 5. print., and 1. paperback print. |
| Series: | Princeton paperbacks
|
| Subjects: | |
| Online Access: | Table of contents Publisher description Inhaltsverzeichnis |
| Item Description: | Literaturverz. S [397] - 418. - Hier auch später erschienene, unveränderte Nachdrucke |
| Physical Description: | XX, 421 S. Ill., graph. Darst., Kt. |
| ISBN: | 0691118507 0691096309 9780691118505 |
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| 245 | 1 | 0 | |a Why stock markets crash |b critical events in complex financial systems |c Didier Sornette |
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Record in the Search Index
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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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| series2 | Princeton paperbacks |
| spelling | Sornette, Didier Verfasser aut Why stock markets crash critical events in complex financial systems Didier Sornette 5. print., and 1. paperback print. Princeton [u.a.] Princeton University Press 2004 XX, 421 S. Ill., graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier Princeton paperbacks Literaturverz. S [397] - 418. - Hier auch später erschienene, unveränderte Nachdrucke Geschichte gnd rswk-swf Geschichte Mathematisches Modell Critical phenomena (Physics) Financial crises Forecasting Financial crises History Financial crises Mathematical models Stock exchanges Börse (DE-588)4007502-3 gnd rswk-swf Finanzwirtschaft (DE-588)4017214-4 gnd rswk-swf Krise (DE-588)4033203-2 gnd rswk-swf Währungskrise (DE-588)4396352-3 gnd rswk-swf USA (DE-588)4078704-7 gnd rswk-swf Börse (DE-588)4007502-3 s Finanzwirtschaft (DE-588)4017214-4 s Krise (DE-588)4033203-2 s DE-604 USA (DE-588)4078704-7 g Währungskrise (DE-588)4396352-3 s Geschichte z 1\p DE-604 http://www.loc.gov/catdir/toc/prin032/2002024336.html Table of contents http://www.loc.gov/catdir/description/prin031/2002024336.html Publisher description Digitalisierung UB Bamberg application/pdf 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 Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| 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 |
| url | 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 |
| work_keys_str_mv | AT sornettedidier whystockmarketscrashcriticaleventsincomplexfinancialsystems |