The Anderson-Darling test of fit for the power law distribution from left censored samples

Maximum likelihood estimation and a test of fit based on the Anderson–Darling statistic are presented for the case of the power-law distribution when the parameters are estimated from a left-censored sample. Expressions for the maximum likelihood estimators and tables of asymptotic percentage points for the A2 statistic are given. The technique is illustrated for data from the Dow Jones Industrial Average index, an example of high theoretical and practical importance in Econophysics, Finance, Physics, Biology and, in general, in other related sciences such as Complexity Sciences.

[1]  Wentian Li,et al.  Random texts exhibit Zipf's-law-like word frequency distribution , 1992, IEEE Trans. Inf. Theory.

[2]  V. Plerou,et al.  A unified econophysics explanation for the power-law exponents of stock market activity , 2007 .

[3]  N. Goldenfeld Lectures On Phase Transitions And The Renormalization Group , 1972 .

[4]  Charles Gide,et al.  Cours d'économie politique , 1911 .

[5]  Anirban Chakraborti,et al.  The near-extreme density of intraday log-returns , 2011, 1106.0039.

[6]  Ralph B. D'Agostino,et al.  Goodness-of-Fit-Techniques , 2020 .

[7]  P. Gopikrishnan,et al.  Inverse cubic law for the distribution of stock price variations , 1998, cond-mat/9803374.

[8]  S. Strogatz Exploring complex networks , 2001, Nature.

[9]  A. Pettitt,et al.  Modified Cramér-von Mises statistics for censored data , 1976 .

[10]  Allen B. Downey,et al.  The structural cause of file size distributions , 2001, MASCOTS 2001, Proceedings Ninth International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems.

[11]  H. Stanley,et al.  Scaling, Universality, and Renormalization: Three Pillars of Modern Critical Phenomena , 1999 .

[12]  H. Stanley,et al.  Introduction to Phase Transitions and Critical Phenomena , 1972 .

[13]  M. Newman Power laws, Pareto distributions and Zipf's law , 2005 .

[14]  B. Gutenberg,et al.  Seismicity of the Earth and associated phenomena , 1950, MAUSAM.

[15]  C. Sparrow The Fractal Geometry of Nature , 1984 .

[16]  J. Durbin Distribution theory for tests based on the sample distribution function , 1973 .

[17]  J. P. BfflOF Computing the distribution of quadratic forms in normal variables , 2005 .

[18]  Chin Wen Cheong,et al.  A simple power-law tail estimation of financial stock return , 2009 .

[19]  V. Plerou,et al.  A theory of power-law distributions in financial market fluctuations , 2003, Nature.

[20]  H. F. Coronel-Brizio,et al.  On fitting the Pareto-Levy distribution to stock market index data: selecting a suitable cutoff value , 2004, cond-mat/0411161.

[21]  A. N. Pettitt Cramer-von Mises statistics for testing normality with censored samples , 1976 .

[22]  M. Crovella,et al.  Heavy-tailed probability distributions in the World Wide Web , 1998 .

[23]  K. Iguchi,et al.  q-exponential fitting for distributions of family names , 2008 .

[24]  Bikas K. Chakrabarti,et al.  Econophysics of Wealth Distributions , 2005 .

[25]  Albert-László Barabási,et al.  Internet: Diameter of the World-Wide Web , 1999, Nature.

[26]  New statistic for financial return distributions: power-law or exponential? , 2004, physics/0403075.

[27]  Michalis Faloutsos,et al.  On power-law relationships of the Internet topology , 1999, SIGCOMM '99.

[28]  V. Plerou,et al.  Scaling of the distribution of price fluctuations of individual companies. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[29]  V. Plerou,et al.  Statistical Physics and Economic Fluctuations , 2004 .

[30]  Mauro Gallegati,et al.  The power-law tail exponent of income distributions , 2006 .

[31]  Enrico Scalas,et al.  Fitting the empirical distribution of intertrade durations , 2008 .

[32]  Michael A. Stephens,et al.  Asymptotic Results for Goodness-of-Fit Statistics with Unknown Parameters , 1976 .

[33]  H. Bauke Parameter estimation for power-law distributions by maximum likelihood methods , 2007, 0704.1867.

[34]  Mark E. J. Newman,et al.  Power-Law Distributions in Empirical Data , 2007, SIAM Rev..

[35]  Mark A. McComb A Practical Guide to Heavy Tails , 2000, Technometrics.

[36]  Michel L. Goldstein,et al.  Problems with fitting to the power-law distribution , 2004, cond-mat/0402322.