Cover -- Half-title -- Title -- Copyright -- Contents -- Preface -- Part I Econophysics -- 1 Why econophysics? -- 1 Newton's apple paradigm revisited -- 1.1 Newton's apple -- 1.2 An economic parallel -- 2 Simple phenomena first -- 2.1 Two-body problems -- 2.2 Complexity classification -- 2.3 The role of time: Simon's bowl metaphor -- 2.4 Simple aspects of complex systems -- 3 From plausible reasons to regularities -- 3.1 The pot of yoghurt paradigm -- 3.2 Plausible causes versus scientific explanations -- 3.3 Regularities -- 3.4 Circumstantial causes versus structural factors -- 3.5 Models need accurate empirical targets -- 4 Conclusion -- 4.1 The primacy of observation -- 4.2 "Modest goals" -- 4.3 Clusters of events and comparative analysis -- 2 The beginnings of econophysics -- 1 Pre-econophysics -- 1.1 Pre-econophysicists -- 1.1.1 Quételet (1796-1874) -- 1.1.2 Walras (1834-1910) -- 1.1.3 Pareto (1848-1923) -- 1.1.4 Allais (1911-) -- 1.1.5 Other pre-econophysicists -- 1.2 Assessment of pre-econophysics -- 2 Institutional econophysics -- 2.1 Idiosyncrasies of economic journals -- 2.2 The beginnings of econophysics -- 2.3 Neurophysics -- 2.4 The fractal revolution -- 2.5 Formation of an econophysical community -- 2.6 A personal note -- 2.7 The future of econophysics -- Part II How do markets work? -- 3 Social man versus homo economicus -- 1 The social man and the Zeitgeist -- 1.1 Connection between fast growth sectors and Zeitgeist -- 1.1.1 Slave trade -- 1.1.2 X-ray medical instruments -- 1.2 Quantitative measure of the role of the Zeitgeist -- 1.3 Ways and means of the Zeitgeist -- 2 Regularities -- 2.1 The search for uniformities and regularities -- 2.2 Examples of speculative peaks -- 2.2.1 Commodity markets -- 2.2.2 Land and real estate -- 2.2.3 Postage stamps and antiquarian books -- 2.2.4 Share prices -- 2.2.5 Conclusion.

4 Organization of speculative markets -- 1 Trends -- 1.1 Concentration -- 1.1.1 Role of declining communication costs -- 1.1.2 Productivity increase -- 1.2 The thorny question of commission rates -- 2 Trading techniques -- 2.1 Short selling, futures, options -- 2.1.1 A "not so simple" transaction -- 2.1.2 Buying on margin -- 2.1.3 Options -- 2.1.4 How options can be used for hedging purposes -- 2.2 How to create a successful financial product? -- 2.3 Protection against market crashes -- 2.3.1 The specialist system -- 2.3.2 Investment funds -- 2.3.3 Emergency procedures -- 2.3.4 Stock options -- 2.4 Sources of instability: the boomerang effect -- 3 Organization of the banking system -- 3.1 The United States -- 3.2 Canada versus the United States -- 4 Time series for stock prices and bankruptcies -- 4.1 Stock prices -- 4.2 Downgrades, failure rate, and suspensions -- Part III Regularities in speculative episodes -- 5 Collective behavior of investors -- 1 High-tech booms -- 1.1 The high-tech boom of the automobile industry -- 1.2 The phase of "natural selection" -- 1.3 High-tech booms backed by venture capital -- 2 Flight to safety -- 2.1 Grain panics -- 2.2 Nineteenth-century banking panics -- 2.3 Relationship with grain crisis -- 2.4 "Deliver us from inflation" -- 2.4.1 Postage stamps -- 2.4.2 Antiquarian books -- 2.4.3 Precious metals -- 2.4.4 Conclusion -- 2.5 Flight to quality in equity markets -- 3 To sell or not to sell? -- 3.1 Formulation of the problem -- 3.2 Some methodological points -- 3.3 Short-term response (weekly fluctuations) -- 3.4 Long-term response (yearly fluctuations) -- 3.5 Effect of mutual funds purchases on stock prices -- 3.6 Conclusion -- 4 Connection between property and stock markets -- 4.1 Impact of property crashes on economic growth -- 4.2 Delay in the response of real estate markets.

4.3 The connection between property and stock bubbles -- 4.3.1 United States -- 4.3.2 France -- 6 Speculative peaks: statistical regularities -- 1 A "thermometer" of speculative frenzy -- 1.1 Real estate -- 1.2 Bonds -- 2 Shape of price peaks -- 2.1 Empirical evidence for asymmetry parameters -- 2.2 Mathematical description of the shape of peaks -- 2.3 Empirical evidence for shape parameters -- 3 Stock market crashes -- 3.1 When? -- 3.2 How? -- 3.2.1 The rebound effect -- 3.2.2 "Frightening Fridays" -- 3.3 Overnight crashes -- 3.4 Lawsuits in the wake of market crashes -- 4 Trading volume -- 4.1 Volume at the level of individual stocks -- 4.2 Volume movements at market level -- 4.2.1 Day traders -- 4.2.2 Decimalization -- 5 Economic consequences of stock market collapses -- 5.1 Consumer confidence -- 5.1.1 Consumer confidence estimates -- 5.1.2 Consumer confidence and consumption -- 5.1.3 How stock prices affect consumer confidence -- 5.2 Relationship between stock price levels and commission rates -- 5.3 Effect on the distribution of income -- 5.3.1 United States (1920-1945) -- 5.3.2 United Kingdom (1970-1980) -- 5.3.3 Japan (1976-1998) -- 5.3.4 Comparison -- Part IV Theoretical framework -- 7 Two classes of speculative peaks -- 1 Speculative peaks: two illustrative examples -- 1.1 Wheat price peaks -- 1.2 Real estate prices -- 2 The price multiplier criterion -- 3 The ensemble dispersion criterion -- 4 Two classes -- 5 Bond market -- 6 Differences in response times -- 6.1 Dispersion of peak times -- 6.2 Relationship between amplitude and response time -- 8 Dynamics of speculative peaks: theoretical framework -- 1 Main ideas -- 1.1 A comparative perspective -- 1.2 Shock versus permanent monitoring -- 1.3 Users and speculators -- 1.4 Transaction friction -- 1.5 Agents and markets form a compound -- 2 Implementation.

2.1 Recapitulation of empirical regularities -- 2.2 Dynamic equations: first order -- 2.3 Dynamic equations: second order -- 2.4 Dynamic equations: higher orders -- 2.5 Light or heavy damping? -- 3 Implications -- 3.1 Amplitude versus duration of the ascending phase -- 3.2 Peak amplitude and proportion of investors -- 3.3 Synchronization effects -- Appendix A: Green's function for a fourth-order equation -- 9 Theoretical framework: implications -- 1 The resilience effect -- 1.1 Description -- 1.2 Interpretation -- 1.3 Statistical evidence -- 2 Breakdown of scaling -- 2.1 First-order process -- 2.2 Second-order process -- 3 Ensemble coefficient of variation -- 4 The stochastic spatial arbitrage model for U-class goods -- 5 Perspectives -- Main data sources -- References -- Index.