Levels of complexity in financial markets

We consider different levels of complexity which are observed in the empirical investigation of financial time series. We discuss recent empirical and theoretical work showing that statistical properties of financial time series are rather complex under several ways. Specifically, they are complex with respect to their (i) temporal and (ii) ensemble properties. Moreover, the ensemble return properties show a behavior which is specific to the nature of the trading day reflecting if it is a normal or an extreme trading day.

[1]  Enrico Scalas,et al.  Volatility in the Italian Stock Market: An Empirical Study , 1999 .

[2]  Didier Sornette,et al.  Scale Invariance and Beyond , 1997 .

[3]  P. Cizeau,et al.  Statistical properties of the volatility of price fluctuations. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[4]  G. Toulouse,et al.  Ultrametricity for physicists , 1986 .

[5]  E. Elton Modern portfolio theory and investment analysis , 1981 .

[6]  Neil F. Johnson,et al.  Crowd effects and volatility in markets with competing agents , 1999 .

[7]  Rosario N. Mantegna,et al.  Book Review: An Introduction to Econophysics, Correlations, and Complexity in Finance, N. Rosario, H. Mantegna, and H. E. Stanley, Cambridge University Press, Cambridge, 2000. , 2000 .

[8]  E. Fama,et al.  Efficient Capital Markets : II , 2007 .

[9]  Mantegna,et al.  Variety and volatility in financial markets , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[10]  A. Stuart,et al.  Portfolio Selection: Efficient Diversification of Investments , 1959 .

[11]  V. Plerou,et al.  Universal and Nonuniversal Properties of Cross Correlations in Financial Time Series , 1999, cond-mat/9902283.

[12]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[13]  P. Cizeau,et al.  CORRELATIONS IN ECONOMIC TIME SERIES , 1997, cond-mat/9706021.

[14]  A. Stuart,et al.  Portfolio Selection: Efficient Diversification of Investments. , 1960 .

[15]  W. Arthur,et al.  The Economy as an Evolving Complex System II , 1988 .

[16]  M. V. Valkenburg Network Analysis , 1964 .

[17]  Kathryn Fraughnaugh,et al.  Introduction to graph theory , 1973, Mathematical Gazette.

[18]  M. Mézard,et al.  Spin Glass Theory and Beyond , 1987 .

[19]  J. Gower Some distance properties of latent root and vector methods used in multivariate analysis , 1966 .

[20]  E. Fama EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .

[21]  Empirical properties of the variety of a financial portfolio and the single-index model , 2000, cond-mat/0009401.

[22]  T. Andersen THE ECONOMETRICS OF FINANCIAL MARKETS , 1998, Econometric Theory.

[23]  P. Cizeau,et al.  Volatility distribution in the S&P500 stock index , 1997, cond-mat/9708143.

[24]  K. Pearson Biometrika , 1902, The American Naturalist.

[25]  Rama Cont,et al.  Scale Invariance and Beyond , 1997 .

[26]  Maurizio Serva,et al.  Multiscaling and clustering of volatility , 1999 .

[27]  Journal of business , 2022 .

[28]  M. Potters,et al.  Theory of Financial Risk , 1997 .

[29]  Jean-Philippe Bouchaud,et al.  Correlation Structure of Extreme Stock Returns , 2000 .

[30]  R. Engle Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation , 1982 .

[31]  F. Lillo,et al.  High-frequency cross-correlation in a set of stocks , 2000 .

[32]  Rosario N. Mantegna,et al.  Turbulence and financial markets , 1996, Nature.

[33]  T. Bollerslev,et al.  Generalized autoregressive conditional heteroskedasticity , 1986 .