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Analysis of the gold fixing price fluctuation in different times based on the directed weighted networks

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  • Zhang, Guangyong
  • Jiang, Le
  • Tian, Lixin
  • Fu, Min

Abstract

According to the complex network theory, this paper constructs the gold fixing price fluctuation directed weighted network (GFPFDWN) at 10:30 a.m. (A.M.) and 15:00p.m. (P.M.) London Greenwich Mean Time, and studies the law of the gold fixing price fluctuation by analyzing the basic statistical data and characteristics of the GFPFDWN. The results show that the abnormal distribution of the gold fixing price (GFP) at A.M. and P.M. is confirmed by the statistics, the core fluctuation state of the GFPFDWN is reflected in the first 1.8% nodes, and most of the nodes have smaller strength, only a few nodes have larger strength, which has the characteristics of a typical scale-free network. Meanwhile, the nodes with a large strength are closely related among them, which must appear earlier, but the nodes appearing early are not necessarily the nodes with a large strength. The nodes of the GFPFDWN present a short-range correlation in different periods, and the cumulative time of the new nodes shows a high linear growth trend. In addition, the nodes of the GFPFDWN show the characteristics with a small betweenness, clustering coefficient and node strength in different periods, which are different from the characteristics of the random network and chaotic network. When these nodes with small strength appear, which means that this period is in a transitional period, then identifying and analyzing these nodes can effectively predict the fluctuation of the gold fixing price in the next period.

Suggested Citation

  • Zhang, Guangyong & Jiang, Le & Tian, Lixin & Fu, Min, 2021. "Analysis of the gold fixing price fluctuation in different times based on the directed weighted networks," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:ecofin:v:57:y:2021:i:c:s1062940821000668
    DOI: 10.1016/j.najef.2021.101437
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    References listed on IDEAS

    as
    1. Chang, Chia-Lin & Della Chang, Jui-Chuan & Huang, Yi-Wei, 2013. "Dynamic price integration in the global gold market," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 227-235.
    2. Dirk G. Baur & Brian M. Lucey, 2010. "Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold," The Financial Review, Eastern Finance Association, vol. 45(2), pages 217-229, May.
    3. Sephton, Peter & Mann, Janelle, 2018. "Gold and crude oil prices after the great moderation," Energy Economics, Elsevier, vol. 71(C), pages 273-281.
    4. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Stanley, H. Eugene, 2016. "Extreme risk spillover effects in world gold markets and the global financial crisis," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 55-77.
    5. Wang, Minggang & Chen, Ying & Tian, Lixin & Jiang, Shumin & Tian, Zihao & Du, Ruijin, 2016. "Fluctuation behavior analysis of international crude oil and gasoline price based on complex network perspective," Applied Energy, Elsevier, vol. 175(C), pages 109-127.
    6. Geng, Jiang-Bo & Ji, Qiang & Fan, Ying, 2014. "A dynamic analysis on global natural gas trade network," Applied Energy, Elsevier, vol. 132(C), pages 23-33.
    7. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    8. Baur, Dirk G. & McDermott, Thomas K., 2010. "Is gold a safe haven? International evidence," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1886-1898, August.
    9. Gupta, Rangan & Hammoudeh, Shawkat & Kim, Won Joong & Simo-Kengne, Beatrice D., 2014. "Forecasting China's foreign exchange reserves using dynamic model averaging: The roles of macroeconomic fundamentals, financial stress and economic uncertainty," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 170-189.
    10. Balcilar, Mehmet & Gupta, Rangan & Pierdzioch, Christian, 2016. "Does uncertainty move the gold price? New evidence from a nonparametric causality-in-quantiles test," Resources Policy, Elsevier, vol. 49(C), pages 74-80.
    11. Singhal, Shelly & Choudhary, Sangita & Biswal, Pratap Chandra, 2019. "Return and volatility linkages among International crude oil price, gold price, exchange rate and stock markets: Evidence from Mexico," Resources Policy, Elsevier, vol. 60(C), pages 255-261.
    12. Pho, Kim Hung & Ly, Sel & Lu, Richard & Hoang, Thi Hong Van & Wong, Wing-Keung, 2021. "Is Bitcoin a better portfolio diversifier than gold? A copula and sectoral analysis for China," International Review of Financial Analysis, Elsevier, vol. 74(C).
    13. Ntim, Collins G. & English, John & Nwachukwu, Jacinta & Wang, Yan, 2015. "On the efficiency of the global gold markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 218-236.
    14. Bouri, Elie & Gupta, Rangan & Lahiani, Amine & Shahbaz, Muhammad, 2018. "Testing for asymmetric nonlinear short- and long-run relationships between bitcoin, aggregate commodity and gold prices," Resources Policy, Elsevier, vol. 57(C), pages 224-235.
    15. Zhang, Hongwei & Wang, Peijin, 2021. "Does Bitcoin or gold react to financial stress alike? Evidence from the U.S. and China," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 629-648.
    16. 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.
    17. 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.
    18. Bilgin, Mehmet Huseyin & Gozgor, Giray & Lau, Chi Keung Marco & Sheng, Xin, 2018. "The effects of uncertainty measures on the price of gold," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 1-7.
    19. Gülin Vardar & Yener Coşkun & Tezer Yelkenci, 2018. "Shock transmission and volatility spillover in stock and commodity markets: evidence from advanced and emerging markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 8(2), pages 231-288, August.
    20. Bariviera, Aurelio F. & Font-Ferrer, Alejandro & Sorrosal-Forradellas, M. Teresa & Rosso, Osvaldo A., 2019. "An information theory perspective on the informational efficiency of gold price," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    21. Obryan Poyser, 2019. "Exploring the dynamics of Bitcoin’s price: a Bayesian structural time series approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 9(1), pages 29-60, March.
    22. Telli, Şahin & Chen, Hongzhuan, 2020. "Multifractal behavior in return and volatility series of Bitcoin and gold in comparison," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    23. Yang, Yu & Poon, Jessie P.H. & Liu, Yi & Bagchi-Sen, Sharmistha, 2015. "Small and flat worlds: A complex network analysis of international trade in crude oil," Energy, Elsevier, vol. 93(P1), pages 534-543.
    24. Mills, Terence C., 2004. "Statistical analysis of daily gold price data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(3), pages 559-566.
    25. Shafiee, Shahriar & Topal, Erkan, 2010. "An overview of global gold market and gold price forecasting," Resources Policy, Elsevier, vol. 35(3), pages 178-189, September.
    26. Lau, Marco Chi Keung & Vigne, Samuel A. & Wang, Shixuan & Yarovaya, Larisa, 2017. "Return spillovers between white precious metal ETFs: The role of oil, gold, and global equity," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 316-332.
    27. Dutta, Anupam & Das, Debojyoti & Jana, R.K. & Vo, Xuan Vinh, 2020. "COVID-19 and oil market crash: Revisiting the safe haven property of gold and Bitcoin," Resources Policy, Elsevier, vol. 69(C).
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    More about this item

    Keywords

    Gold fixing price; Time series; Strength; Betweenness; Clustering coefficient;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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