Fractal Markets Hypothesis and the Global Financial Crisis: Scaling, Investment Horizons and Liquidity

We investigate whether the fractal markets hypothesis and its focus on liquidity and investment horizons give reasonable predictions about the dynamics of the financial markets during turbulences such as the Global Financial Crisis of late 2000s. Compared to the mainstream efficient markets hypothesis, the fractal markets hypothesis considers the financial markets as complex systems consisting of many heterogenous agents, which are distinguishable mainly with respect to their investment horizon. In the paper, several novel measures of trading activity at different investment horizons are introduced through the scaling of variance of the underlying processes. On the three most liquid US indices — DJI, NASDAQ and S&P500 — we show that the predictions of the fractal markets hypothesis actually fit the observed behavior adequately.

[1]  Stephen F. LeRoy EFFICIENT CAPITAL MARKETS: COMMENT , 1976 .

[2]  H. Santos,et al.  Electron Transmission through Graphene Bilayer Flakes , 2012 .

[3]  R. Cont Empirical properties of asset returns: stylized facts and statistical issues , 2001 .

[4]  C. Peng,et al.  Mosaic organization of DNA nucleotides. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[5]  T. D. Matteo,et al.  Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development , 2004, cond-mat/0403681.

[6]  John Goddard,et al.  Are European Equity Markets Efficient? New Evidence from Fractal Analysis , 2011 .

[7]  A. Goldberger,et al.  Finite-size effects on long-range correlations: implications for analyzing DNA sequences. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[8]  Harry Eugene Stanley,et al.  Econophysics: can physicists contribute to the science of economics? , 1999, Comput. Sci. Eng..

[9]  Edgar E. Peters Fractal Market Analysis: Applying Chaos Theory to Investment and Economics , 1994 .

[10]  R. Weron,et al.  Fractal market hypothesis and two power-laws , 2000 .

[11]  D. Sornette,et al.  Stock Market Crashes, Precursors and Replicas , 1995, cond-mat/9510036.

[12]  Marco Corazza,et al.  Multifractality in Foreign Currency Markets , 2008 .

[13]  T. D. Matteo,et al.  Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series , 2011, 1109.0465.

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

[15]  John Goddard,et al.  Unifractality and Multifractality in the Italian Stock Market , 2008 .

[16]  B. Malkiel The Efficient Market Hypothesis and Its Critics , 2003 .

[17]  Ladislav Kristoufek,et al.  Multifractal height cross-correlation analysis: A new method for analyzing long-range cross-correlations , 2011, 1201.3473.

[18]  Krzysztof Domino,et al.  The use of the Hurst exponent to investigate the global maximum of the Warsaw Stock Exchange WIG20 index , 2012 .

[19]  K. Domino The use of the Hurst exponent to predict changes in trends on the Warsaw Stock Exchange , 2011 .

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

[21]  E. Fama Random Walks in Stock Market Prices , 1965 .

[22]  T. D. Matteo,et al.  Multi-scaling in finance , 2007 .

[23]  Didier Sornette,et al.  Encyclopedia of Complexity and Systems Science , 2009 .

[24]  D. Grech,et al.  Comparison study of global and local approaches describing critical phenomena on the Polish stock exchange market , 2008 .

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

[26]  Robert A. Meyers,et al.  Encyclopedia of Complexity and Systems Science , 2009 .

[27]  Edgar E. Peters Chaos and Order in the Capital Markets: A New View of Cycles, Prices, and Market Volatility , 1996 .

[28]  Ladislav Kristoufek,et al.  On Hurst exponent estimation under heavy-tailed distributions , 2010, 1201.4786.

[29]  D. Grech,et al.  Can one make any crash prediction in finance using the local Hurst exponent idea , 2003, cond-mat/0311627.

[30]  H. Stanley,et al.  Multifractal Detrended Fluctuation Analysis of Nonstationary Time Series , 2002, physics/0202070.

[31]  Laurent E. Calvet,et al.  Multifractal Volatility: Theory, Forecasting, and Pricing , 2008 .

[32]  Svetlozar T. Rachev,et al.  CED model for asset returns and fractal market hypothesis , 1999 .

[33]  H. Eugene Stanley,et al.  Statistical physics and economic fluctuations: do outliers exist? , 2003 .

[34]  D. Grech,et al.  The local Hurst exponent of the financial time series in the vicinity of crashes on the Polish stock exchange market , 2008 .