This book concerns the use of concepts from statistical physics in the description of financial systems. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully developed turbulent fluids. These concepts are then applied to financial time series. The authors also present a stochastic model that displays several of the statistical properties observed in empirical data. Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling permit an understanding of the global behaviour of economic systems without first having to work out a detailed microscopic description of the system. Physicists will find the application of statistical physics concepts to economic systems interesting. Economists and workers in the financial world will find useful the presentation of empirical analysis methods and well-formulated theoretical tools that might help describe systems composed of a huge number of interacting subsystems.

Preface; 1. Introduction; 2. Efficient market hypothesis; 3. Random walk; 4. Lévy stochastic processes and limit theorems; 5. Scales in financial data; 6. Stationarity and time correlation; 7. Time correlation in financial time series; 8. Stochastic models of price dynamics; 9. Scaling and its breakdown; 10. ARCH and GARCH processes; 11. Financial markets and turbulence; 12. Correlation and anti-correlation between stocks; 13. Taxonomy of a stock portfolio; 14. Options in idealized markets; 15. Options in real markets; Appendix A: notation guide; Appendix B: martingales; References; Index.