Asymmetric multifractal spectrum distribution based on detrending moving average cross-correlation analysis

被引：4
作者：
Shen, Na [1 ]
Chen, Jiayi [1 ]
机构：
[1] Shenzhen Univ, Coll Elect & Informat Engn, Shenzhen, Peoples R China
来源：
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2023年 / 615卷
基金：
中国国家自然科学基金;
关键词：
Multifractal spectrum distribution; Asymmetric multifractal analysis; Bitcoin; Gold; AMERICAN STOCK-MARKET; CRUDE-OIL; BITCOIN; GOLD; PRICE; PERSISTENCE; BEHAVIOR; RETURNS; VOLUME;
D O I：
10.1016/j.physa.2023.128559
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
This paper proposes the asymmetric multifractal spectrum distribution based on de-trending moving average cross-correlation analysis (A-DMCA-MFSD) algorithm to cal-culate time-varying multifractal spectrum under different market trends. Numerical results of this algorithm applied to analyzing artificially generated data show superior performance in terms of accuracy and robustness. The algorithm is further applied to investigate auto-correlations of Bitcoin and Gold return series. Asymmetric behaviors of Bitcoin and Gold are obviously observed in small-scale fluctuations. In addition, Bitcoin series shows greater singularity strength than Gold in most of the time. Cross-correlations between Bitcoin and Gold are also studied utilizing A-DMCA-MFSD. Greater cross-correlation is observed during upward trends of Bitcoin (downward trends of Gold) than during downward trends (upward trends, respectively).(c) 2023 Elsevier B.V. All rights reserved.
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页数：16
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共 61 条
  • [1] A DFA approach for assessing asymmetric correlations
    Alvarez-Ramirez, Jose
    Rodriguez, Eduardo
    Echeverria, Juan Carlos
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2009, 388 (12) : 2263 - 2270
  • [2] [Anonymous], 2012, ECONOMICS
  • [3] Understanding the source of multifractality in financial markets
    Barunik, Jozef
    Aste, Tomaso
    Di Matteo, T.
    Liu, Ruipeng
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2012, 391 (17) : 4234 - 4251
  • [4] Effect of nonlinear correlations on the statistics of return intervals in multifractal data sets
    Bogachev, Mikhail I.
    Eichner, Jan F.
    Bunde, Armin
    [J]. PHYSICAL REVIEW LETTERS, 2007, 99 (24)
  • [5] Bouchaud JP, 2000, EUR PHYS J B, V13, P595
  • [6] Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions
    Bouri, Elie
    Gupta, Rangan
    Tiwari, Aviral Kumar
    Roubaud, David
    [J]. FINANCE RESEARCH LETTERS, 2017, 23 : 87 - 95
  • [7] On the interplay between multiscaling and stock dependence
    Buonocore, R. J.
    Brandi, G.
    Mantegna, R. N.
    Di Matteo, T.
    [J]. QUANTITATIVE FINANCE, 2020, 20 (01) : 133 - 145
  • [8] Asymmetric multifractal scaling behavior in the Chinese stock market: Based on asymmetric MF-DFA
    Cao, Guangxi
    Cao, Jie
    Xu, Longbing
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2013, 392 (04) : 797 - 807
  • [9] On non-scale-invariant infinitely divisible cascades
    Chainais, P
    Riedi, R
    Abry, P
    [J]. IEEE TRANSACTIONS ON INFORMATION THEORY, 2005, 51 (03) : 1063 - 1083
  • [10] An empirical analysis of herd behavior in global stock markets
    Chiang, Thomas C.
    Zheng, Dazhi
    [J]. JOURNAL OF BANKING & FINANCE, 2010, 34 (08) : 1911 - 1921
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