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Multifractal characterization of gold market: A multifractal detrended fluctuation analysis

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  • Mali, Provash
  • Mukhopadhyay, Amitabha

Abstract

The multifractal detrended fluctuation analysis technique is employed to analyze the time series of gold consumer price index (CPI) and the market trend of three world’s highest gold consuming countries, namely China, India and Turkey for the period: 1993–July 2013. Various multifractal variables, such as the generalized Hurst exponent, the multifractal exponent and the singularity spectrum, are calculated and the results are fitted to the generalized binomial multifractal (GBM) series that consists of only two parameters. Special emphasis is given to identify the possible source(s) of multifractality in these series. Our analysis shows that the CPI series and all three market series are of multifractal nature. The origin of multifractality for the CPI time series and Indian market series is found due to a long-range time correlation, whereas it is mostly due to the fat-tailed probability distributions of the values for the Chinese and Turkey markets. The GBM model series more or less describes all the time series analyzed here.

Suggested Citation

  • Mali, Provash & Mukhopadhyay, Amitabha, 2014. "Multifractal characterization of gold market: A multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 361-372.
  • Handle: RePEc:eee:phsmap:v:413:y:2014:i:c:p:361-372
    DOI: 10.1016/j.physa.2014.06.076
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    References listed on IDEAS

    as
    1. Bacry, E. & Delour, J. & Muzy, J.F., 2001. "Modelling financial time series using multifractal random walks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 84-92.
    2. Amihud, Yakov & Mendelson, Haim & Pedersen, Lasse Heje, 2006. "Liquidity and Asset Prices," Foundations and Trends(R) in Finance, now publishers, vol. 1(4), pages 269-364, February.
    3. Parameswaran Gopikrishnan & Vasiliki Plerou & Luis A. Nunes Amaral & Martin Meyer & H. Eugene Stanley, 1999. "Scaling of the distribution of fluctuations of financial market indices," Papers cond-mat/9905305, arXiv.org.
    4. Xavier Gabaix & Parameswaran Gopikrishnan & Vasiliki Plerou & H. Eugene Stanley, 2006. "Institutional Investors and Stock Market Volatility," The Quarterly Journal of Economics, Oxford University Press, vol. 121(2), pages 461-504.
    5. Lu, Xinsheng & Tian, Jie & Zhou, Ying & Li, Zhihui, 2013. "Multifractal detrended fluctuation analysis of the Chinese stock index futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1452-1458.
    6. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2011. "Analysis of the efficiency and multifractality of gold markets based on multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 817-827.
    7. Oświe¸cimka, P. & Kwapień, J. & Drożdż, S., 2005. "Multifractality in the stock market: price increments versus waiting times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 347(C), pages 626-638.
    8. Kantelhardt, Jan W. & Rybski, Diego & Zschiegner, Stephan A. & Braun, Peter & Koscielny-Bunde, Eva & Livina, Valerie & Havlin, Shlomo & Bunde, Armin, 2003. "Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(1), pages 240-245.
    9. Stanislaw Drozdz & Jaroslaw Kwapien & Pawel Oswiecimka & Rafal Rak, 2010. "The foreign exchange market: return distributions, multifractality, anomalous multifractality and Epps effect," Papers 1011.2385, arXiv.org.
    10. Drożdż, S. & Forczek, M. & Kwapień, J. & Oświe¸cimka, P. & Rak, R., 2007. "Stock market return distributions: From past to present," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 59-64.
    11. repec:cup:cbooks:9780521039871 is not listed on IDEAS
    12. Kaushik Matia & Yosef Ashkenazy & H. Eugene Stanley, 2003. "Multifractal Properties of Price Fluctuations of Stocks and Commodities," Papers cond-mat/0308012, arXiv.org.
    13. S. Drozdz & J. Kwapien & F. Gruemmer & F. Ruf & J. Speth, 2002. "Are the contemporary financial fluctuations sooner converging to normal?," Papers cond-mat/0208240, arXiv.org, revised Jul 2003.
    14. 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.
    15. repec:cup:cbooks:9780521620086 is not listed on IDEAS
    16. 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.
    17. 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.
    18. Rafal Rak & Stanislaw Drozdz & Jaroslaw Kwapien & Pawel Oswiecimka, 2013. "Stock returns versus trading volume: is the correspondence more general?," Papers 1310.7018, arXiv.org.
    19. S. Drozdz & M. Forczek & J. Kwapien & P. Oswiecimka & R. Rak, 2007. "Stock market return distributions: from past to present," Papers 0704.0664, arXiv.org.
    20. 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.
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    Cited by:

    1. Lahmiri, Salim, 2017. "Multifractal analysis of Moroccan family business stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 183-191.
    2. Chen, Feier & Tian, Kang & Ding, Xiaoxu & Miao, Yuqi & Lu, Chunxia, 2016. "Finite-size effect and the components of multifractality in transport economics volatility based on multifractal detrending moving average method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1058-1066.
    3. Han, Chenyu & Wang, Yiming & Ning, Ye, 2019. "Analysis and comparison of the multifractality and efficiency of Chinese stock market: Evidence from dynamics of major indexes in different boards," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C), pages 1-1.
    4. Tetsuya Takaishi, 2017. "Statistical properties and multifractality of Bitcoin," Papers 1707.07618, arXiv.org, revised May 2018.
    5. Zhao, Zhen-yu & Zhu, Jiang & Xia, Bo, 2016. "Multi-fractal fluctuation features of thermal power coal price in China," Energy, Elsevier, vol. 117(P1), pages 10-18.
    6. Mali, P. & Sarkar, S. & Ghosh, S. & Mukhopadhyay, A. & Singh, G., 2015. "Multifractal detrended fluctuation analysis of particle density fluctuations in high-energy nuclear collisions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 25-33.
    7. Delbianco, Fernando & Tohmé, Fernando & Stosic, Tatijana & Stosic, Borko, 2016. "Multifractal behavior of commodity markets: Fuel versus non-fuel products," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 573-580.
    8. Takaishi, Tetsuya, 2018. "Statistical properties and multifractality of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 507-519.
    9. Chen, Feier & Miao, Yuqi & Tian, Kang & Ding, Xiaoxu & Li, Tingyi, 2017. "Multifractal cross-correlations between crude oil and tanker freight rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 344-354.

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