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Lacunarity and multifractal analysis of the large DLA mass distribution

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  • Rodriguez-Romo, Suemi
  • Sosa-Herrera, Antonio

Abstract

We show the methodology used to analyze fractal and mass-multifractal properties of very large Diffusion-Limited Aggregation (DLA) clusters with a maximum of 109 particles for 2D aggregates and 108 particles for 3D clusters, to support our main result; the scaling behavior obtained by our experimental results corresponds to the expected performance of monofractal objects. In order to estimate lacunarity measures for large DLA clusters, we develop a variant of the gliding-box algorithm which reduces the computer time needed to obtain experimental results. We show how our mass multifractal data have a tendency to present monofractal behavior for the mass distribution of the cases presented in this paper in the limit of very large clusters. Lacunarity analysis shows, provided we study small clusters mass distributions, data which might be interpreted as two different values of fractal dimensions while the cluster grows; however, this effect tends to vanish when the cluster size increases further, in such a way that monofractality is achieved. The outcomes of this paper lead us to conclude that the previously reported mass multifractality behavior (Vicsek et al., 1990 [13]) detected for DLA clusters is a consequence of finite size effects and floating point precision limitations and not an intrinsic feature of the phenomena, since the scaling behavior of our DLA clusters space corresponds to monofractal objects, being this situation remarkably noticeable in the limit of very large clusters.

Suggested Citation

  • Rodriguez-Romo, Suemi & Sosa-Herrera, Antonio, 2013. "Lacunarity and multifractal analysis of the large DLA mass distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3316-3328.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:16:p:3316-3328
    DOI: 10.1016/j.physa.2013.03.044
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    as
    1. Lee, Kyoung Eun & Lee, Jae Woo, 2007. "Probability distribution function and multiscaling properties in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 65-70.
    2. Jiang, J. & Ma, K. & Cai, X., 2007. "Non-linear characteristics and long-range correlations in Asian stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 399-407.
    3. François Schmitt & Daniel Schertzer & Shaun Lovejoy, 1999. "Multifractal analysis of foreign exchange data," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 15(1), pages 29-53, March.
    4. Laurent Calvet & Adlai Fisher, 2002. "Multifractality In Asset Returns: Theory And Evidence," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 381-406, August.
    5. Wei-Xing Zhou, 2009. "The components of empirical multifractality in financial returns," Papers 0908.1089, arXiv.org, revised Oct 2009.
    6. J.-P. Bouchaud & M. Potters & M. Meyer, 2000. "Apparent multifractality in financial time series," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 13(3), pages 595-599, February.
    7. Zhou, Wei-Xing, 2012. "Finite-size effect and the components of multifractality in financial volatility," Chaos, Solitons & Fractals, Elsevier, vol. 45(2), pages 147-155.
    8. A. Kasprzak & R. Kutner & J. Perelló & J. Masoliver, 2010. "Higher-order phase transitions on financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 76(4), pages 513-527, August.
    9. Kaushik Matia & Yosef Ashkenazy & H. Eugene Stanley, 2003. "Multifractal Properties of Price Fluctuations of Stocks and Commodities," Papers cond-mat/0308012, arXiv.org.
    10. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2008. "Multifractality in stock indexes: Fact or Fiction?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3605-3614.
    11. Francois Schmitt & Daniel Schertzer & Shaun Lovejoy, 2000. "Multifractal Fluctuations In Finance," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 361-364.
    12. Huang, Jingjing & Shang, Pengjian & Zhao, Xiaojun, 2012. "Multifractal diffusion entropy analysis on stock volatility in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5739-5745.
    13. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    14. Kwapień, J. & Oświe¸cimka, P. & Drożdż, S., 2005. "Components of multifractality in high-frequency stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 466-474.
    15. Lim, Gyuchang & Kim, SooYong & Lee, Hyoung & Kim, Kyungsik & Lee, Dong-In, 2007. "Multifractal detrended fluctuation analysis of derivative and spot markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 259-266.
    16. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2007. "Scale invariant distribution and multifractality of volatility multipliers in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 343-350.
    17. Kantelhardt, Jan W & Koscielny-Bunde, Eva & Rego, Henio H.A & Havlin, Shlomo & Bunde, Armin, 2001. "Detecting long-range correlations with detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(3), pages 441-454.
    18. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
    19. Zunino, L. & Tabak, B.M. & Figliola, A. & Pérez, D.G. & Garavaglia, M. & Rosso, O.A., 2008. "A multifractal approach for stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6558-6566.
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