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A note on power-law cross-correlated processes

Author

Listed:
  • Fernández-Martínez, M.
  • Sánchez-Granero, M.A.
  • Casado Belmonte, M.P.
  • Trinidad Segovia, J.E.

Abstract

In this paper, some mathematical support is provided to properly justify the validity of the so-called multifractal height cross-correlation analysis (MFHXA), first contributed by Kristoufek (2011)[1]. With this aim, we extend several concepts from univariate random functions and their increments to the bivariate case. Specifically, we introduce the bivariate cumulative range as well as the concepts of co-self-similar processes and random processes with co-affine increments of bivariate parameter. They allow us to introduce a new procedure, named multifractal cross-correlated fractal dimension (MFXFD) algorithm. We theoretically prove the validity of such a novel approach to calculate the bivariate Hurst exponent of a pair of processes with co-affine increments. Interestingly, that class of random functions is characterised theoretically in terms of co-self-similar processes. Moreover, we prove that a pair of univariate self-similar processes are co-self-similar and their bivariate Hurst exponent coincides with the mean of their univariate parameters. Finally, we test the behavior of the new algorithm to calculate the bivariate Hurst exponent of a pair of time series. Both DCCA and MFHXA procedures are involved in such an empirical comparison. Our results suggest that the new MFXFD performs (at least) as well as the other approaches with shorter deviations with respect to the mean of the bivariate Hurst exponents.

Suggested Citation

  • Fernández-Martínez, M. & Sánchez-Granero, M.A. & Casado Belmonte, M.P. & Trinidad Segovia, J.E., 2020. "A note on power-law cross-correlated processes," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    • Handle: RePEc:eee:chsofr:v:138:y:2020:i:c:s0960077920303143
    DOI: 10.1016/j.chaos.2020.109914
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    as
    1. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    2. Lux, Thomas, 2008. "The Markov-Switching Multifractal Model of Asset Returns: GMM Estimation and Linear Forecasting of Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 194-210, April.
    3. Rebecca J. Sela & Clifford M. Hurvich, 2012. "The averaged periodogram estimator for a power law in coherency," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(2), pages 340-363, March.
    4. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    5. 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.
    6. Wei-Xing Zhou, 2009. "The components of empirical multifractality in financial returns," Papers 0908.1089, arXiv.org, revised Oct 2009.
    7. Rak, Rafał & Grech, Dariusz, 2018. "Quantitative approach to multifractality induced by correlations and broad distribution of data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 48-66.
    8. He, Ling-Yun & Chen, Shu-Peng, 2011. "A new approach to quantify power-law cross-correlation and its application to commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3806-3814.
    9. Kristoufek, Ladislav, 2013. "Mixed-correlated ARFIMA processes for power-law cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6484-6493.
    10. Thomas Lux, 2004. "Detecting Multifractal Properties In Asset Returns: The Failure Of The "Scaling Estimator"," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 481-491.
    11. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    12. Pawe{l} O'swic{e}cimka & Stanis{l}aw Dro.zd.z & Marcin Forczek & Stanis{l}aw Jadach & Jaros{l}aw Kwapie'n, 2013. "Detrended Cross-Correlation Analysis Consistently Extended to Multifractality," Papers 1308.6148, arXiv.org, revised Feb 2014.
    13. Cajueiro, Daniel O. & Tabak, Benjamin M., 2009. "Multifractality and herding behavior in the Japanese stock market," Chaos, Solitons & Fractals, Elsevier, vol. 40(1), pages 497-504.
    14. Eisler, Z. & Kertész, J., 2004. "Multifractal model of asset returns with leverage effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 603-622.
    15. 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.
    16. Zhi-Qiang Jiang & Wei-Xing Zhou, 2011. "Multifractal detrending moving average cross-correlation analysis," Papers 1103.2577, arXiv.org, revised Mar 2011.
    17. N. Vandewalle & M. Ausloos, 1998. "Sparseness and Roughness of Foreign Exchange Rates," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 9(05), pages 711-719.
    18. Zebende, G.F., 2011. "DCCA cross-correlation coefficient: Quantifying level of cross-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 614-618.
    19. Ma, Feng & Wei, Yu & Huang, Dengshi, 2013. "Multifractal detrended cross-correlation analysis between the Chinese stock market and surrounding stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1659-1670.
    20. Hols, Martien C A B & de Vries, Casper G, 1991. "The Limiting Distribution of Extremal Exchange Rate Returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(3), pages 287-302, July-Sept.
    21. Laurent Laloux & Pierre Cizeau & Marc Potters & Jean-Philippe Bouchaud, 2000. "Random Matrix Theory And Financial Correlations," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 391-397.
    22. Rafal Rak & Dariusz Grech, 2018. "Quantitative approach to multifractality induced by correlations and broad distribution of data," Papers 1805.11909, arXiv.org.
    23. Grech, Dariusz, 2016. "Alternative measure of multifractal content and its application in finance," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 183-195.
    24. 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.
    25. Zoltan Eisler & Janos Kertesz, 2004. "Multifractal model of asset returns with leverage effect," Papers cond-mat/0403767, arXiv.org, revised May 2004.
    26. Richard T. Baillie & Tim Bollerslev, 1991. "Intra-Day and Inter-Market Volatility in Foreign Exchange Rates," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 565-585.
    27. Rama Cont & Marc Potters & Jean-Philippe Bouchaud, 1997. "Scaling in stock market data: stable laws and beyond," Science & Finance (CFM) working paper archive 9705087, Science & Finance, Capital Fund Management.
    28. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
    29. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.
    30. Norouzzadeh, P. & Jafari, G.R., 2005. "Application of multifractal measures to Tehran price index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 356(2), pages 609-627.
    31. Shi, Wenbin & Shang, Pengjian & Wang, Jing & Lin, Aijing, 2014. "Multiscale multifractal detrended cross-correlation analysis of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 35-44.
    32. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    33. Benoit Mandelbrot & Adlai Fisher & Laurent Calvet, 1997. "A Multifractal Model of Asset Returns," Cowles Foundation Discussion Papers 1164, Cowles Foundation for Research in Economics, Yale University.
    34. B. Podobnik & I. Grosse & D. Horvatić & S. Ilic & P. Ch. Ivanov & H. E. Stanley, 2009. "Quantifying cross-correlations using local and global detrending approaches," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(2), pages 243-250, September.
    35. repec:arx:papers:1501.02947 is not listed on IDEAS
    36. 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.
    37. Gao-Feng Gu & Wei-Xing Zhou, 2010. "Detrending moving average algorithm for multifractals," Papers 1005.0877, arXiv.org, revised Jun 2010.
    38. Parameswaran Gopikrishnan & Martin Meyer & Luis A Nunes Amaral & H Eugene Stanley, 1998. "Inverse Cubic Law for the Probability Distribution of Stock Price Variations," Papers cond-mat/9803374, arXiv.org, revised May 1998.
    39. Xi-Yuan Qian & Ya-Min Liu & Zhi-Qiang Jiang & Boris Podobnik & Wei-Xing Zhou & H. Eugene Stanley, 2015. "Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces," Papers 1504.02435, arXiv.org, revised Apr 2015.
    40. Peter Carr & Helyette Geman, 2002. "The Fine Structure of Asset Returns: An Empirical Investigation," The Journal of Business, University of Chicago Press, vol. 75(2), pages 305-332, April.
    41. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    42. P. Gopikrishnan & M. Meyer & L.A.N. Amaral & H.E. Stanley, 1998. "Inverse cubic law for the distribution of stock price variations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 3(2), pages 139-140, July.
    43. Turiel, Antonio & Pérez-Vicente, Conrad J., 2005. "Role of multifractal sources in the analysis of stock market time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(2), pages 475-496.
    44. Mizuno, Takayuki & Takayasu, Hideki & Takayasu, Misako, 2006. "Correlation networks among currencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 336-342.
    45. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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