Why stock markets crash : critical events in complex financial systems / Didier Sornette.
2003
HB3722 .S66 2003 (Map It)
Available at Cellar
Formats
| Format | |
|---|---|
| BibTeX | |
| MARCXML | |
| TextMARC | |
| MARC | |
| DublinCore | |
| EndNote | |
| NLM | |
| RefWorks | |
| RIS |
Items
Details
Author
Title
Why stock markets crash : critical events in complex financial systems / Didier Sornette.
Published
Princeton, N.J. : Princeton University Press, [2003]
Copyright
©2003
Call Number
HB3722 .S66 2003
ISBN
0691096309 (alk. paper)
Description
xx, 421 pages : illustrations ; 25 cm
System Control No.
(OCoLC)49530264
Bibliography, etc. Note
Includes bibliographical references (pages [397]-418) and index.
Record Appears in
Table of Contents
Preface
Ch. 1
Financial Crashes: What, How, Why, and When?
3
What Are Crashes, and Why Do We Care?
3
The Crash of October 1987
5
Historical Crashes
7
Extreme Events in Complex Systems
15
Is Prediction Possible? A Working Hypothesis
20
Ch. 2
Fundamentals of Financial Markets
26
The Basics
27
The Efficient Market Hypothesis and the Random Walk
38
Risk-Return Trade-Off
47
Ch. 3
Financial Crashes are "Outliers"
49
What Are "Abnormal" Returns?
49
Drawdowns (Runs)
51
Drawdown Distributions of Stock Market Indices
60
The Presence of Outliers Is a General Phenomenon
69
Symmetry-Breaking on Crash and Rally Days
76
Implications for Safety Regulations of Stock Markets
77
Ch. 4
Positive Feedbacks
81
Feedbacks and Self-Organization in Economics
82
Hedging Derivatives, Insurance Portfolios, and Rational Panics
89
"Herd" Behavior and "Crowd" Effect
91
Forces of Imitation
99
"Anti-Imitation" and Self-Organization
114
Cooperative Behaviors Resulting from Imitation
121
Ch. 5
Modeling Financial Bubbles and Market Crashes
134
What Is a Model?
134
Strategy for Model Construction in Finance
135
The Risk-Driven Model
150
The Price-Driven Model
162
Risk-Driven versus Price-Driven Models
168
Ch. 6
Hierarchies, Complex Fractal Dimensions, and Log-Periodicity
171
Critical Phenomena by Imitation on Hierarchical Networks
173
Origin of Log-Periodicity in Hierarchical Systems
186
Nonlinear Trend-Following versus Nonlinear Fundamental Analysis Dynamics
217
Ch. 7
Autopsy of Major Crashes: Universal Exponents and Log-Periodicity
228
The Crash of October 1987
228
The Crash of October 1929
239
The Three Hong Kong Crashes of 1987, 1994, and 1997
242
Currency Crashes
254
The Crash of August 1998
259
Nonparametric Test of Log-Periodicity
263
The Slow Crash of 1962 Ending the "Tronics" Boom
266
The Nasdaq Crash of April 2000
269
"Antibubbles"
275
Synthesis: "Emergent" Behavior of the Stock Market
279
Ch. 8
Bubbles, Crises, and Crashes in Emergent Markets
281
Speculative Bubbles in Emerging Markets
281
Methodology
285
Latin-American Markets
286
Asian Markets
295
The Russian Stock Market
304
Correlations across Markets: Economic Contagion and Synchronization of Bubble Collapse
309
Implications for Mitigations of Crises
314
Ch. 9
Prediction of Bubbles, Crashes, and Antibubbles
320
The Nature of Predictions
320
How to Develop and Interpret Statistical Tests of Log-Periodicity
325
First Guidelines for Prediction
329
A Hierarchy of Prediction Schemes
334
Forward Predictions
338
Present Status of Forward Predictions
346
Ch. 10
2050: The End of the Growth Era?
355
Stock Markets, Economics, and Population
355
The Pessimistic Viewpoint of "Natural" Scientists
357
The Optimistic Viewpoint of "Social" Scientists
359
Analysis of the Faster-Than-Exponential Growth of Population, GDP, and Financial Indices
361
Refinements of the Analysis
369
Scenarios for the "Singularity"
383
The Increasing Propensity to Emulate the Stock Market Approach
395
References
397
Index
419