IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v490y2018icp504-512.html
   My bibliography  Save this article

Cross-correlations and influence in world gold markets

Author

Listed:
  • Lin, Min
  • Wang, Gang-Jin
  • Xie, Chi
  • Stanley, H. Eugene

Abstract

Using the detrended cross-correlation analysis (DCCA) coefficient and the detrended partial cross-correlation analysis (DPCCA) coefficient, we investigate cross-correlations and net cross-correlations among five major world gold markets (London, New York, Shanghai, Tokyo, and Mumbai) at different time scales. We propose multiscale influence measures for examining the influence of individual markets on other markets and on the entire system. We find (i) that the cross-correlations, net cross-correlations, and net influences among the five gold markets vary across time scales, (ii) that the cross-market correlation between London and New York at each time scale is intense and inherent, meaning that the influence of other gold markets on the London–New York market is negligible, (iii) that the remaining cross-market correlations (i.e., those other than London–New York) are greatly affected by other gold markets, and (iv) that the London gold market significantly affects the other four gold markets and dominates the world-wide gold market. Our multiscale findings give market participants and market regulators new information on cross-market linkages in the world-wide gold market.

Suggested Citation

  • Lin, Min & Wang, Gang-Jin & Xie, Chi & Stanley, H. Eugene, 2018. "Cross-correlations and influence in world gold markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 504-512.
  • Handle: RePEc:eee:phsmap:v:490:y:2018:i:c:p:504-512
    DOI: 10.1016/j.physa.2017.08.045
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117307781
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2017.08.045?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Gang-Jin & Xie, Chi, 2013. "Cross-correlations between Renminbi and four major currencies in the Renminbi currency basket," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1418-1428.
    2. Ruan, Qingsong & Huang, Ying & Jiang, Wei, 2016. "The exceedance and cross-correlations between the gold spot and futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 139-151.
    3. 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.
    4. Fernandez, Viviana, 2015. "Influence in commodity markets: Measuring co‐movement globally," Resources Policy, Elsevier, vol. 45(C), pages 151-164.
    5. Zhi-Qiang Jiang & Wei-Xing Zhou, 2011. "Multifractal detrending moving average cross-correlation analysis," Papers 1103.2577, arXiv.org, revised Mar 2011.
    6. Brian M. Lucey & Charles Larkin & Fergal O'Connor, 2014. "Gold markets around the world - who spills over what, to whom, when?," Applied Economics Letters, Taylor & Francis Journals, vol. 21(13), pages 887-892, September.
    7. Brian M. Lucey & Charles Larkin & Fergal A. O'Connor, 2013. "London or New York: where and when does the gold price originate?," Applied Economics Letters, Taylor & Francis Journals, vol. 20(8), pages 813-817, May.
    8. Wang, Gang-Jin & Xie, Chi & He, Ling-Yun & Chen, Shou, 2014. "Detrended minimum-variance hedge ratio: A new method for hedge ratio at different time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 70-79.
    9. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    10. 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.
    11. Dror Y Kenett & Michele Tumminello & Asaf Madi & Gitit Gur-Gershgoren & Rosario N Mantegna & Eshel Ben-Jacob, 2010. "Dominating Clasp of the Financial Sector Revealed by Partial Correlation Analysis of the Stock Market," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-14, December.
    12. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    13. 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.
    14. 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.
    15. Xu, Xiaoqing Eleanor & Fung, Hung-Gay, 2005. "Cross-market linkages between U.S. and Japanese precious metals futures trading," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(2), pages 107-124, April.
    16. Martin Hauptfleisch & Tālis J. Putniņš & Brian Lucey, 2016. "Who Sets the Price of Gold? London or New York," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(6), pages 564-586, June.
    17. Jaroslaw Kwapien & Pawel Oswiecimka & Stanislaw Drozdz, 2015. "Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations," Papers 1506.08692, arXiv.org, revised Nov 2015.
    18. O'Connor, Fergal A. & Lucey, Brian M. & Batten, Jonathan A. & Baur, Dirk G., 2015. "The financial economics of gold — A survey," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 186-205.
    19. Wang, Gang-Jin & Xie, Chi & Lin, Min & Stanley, H. Eugene, 2017. "Stock market contagion during the global financial crisis: A multiscale approach," Finance Research Letters, Elsevier, vol. 22(C), pages 163-168.
    20. 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.
    21. Ruan, Qingsong & Jiang, Wei & Ma, Guofeng, 2016. "Cross-correlations between price and volume in Chinese gold markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 10-22.
    22. 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.
    23. Xian, Lu & He, Kaijian & Lai, Kin Keung, 2016. "Gold price analysis based on ensemble empirical model decomposition and independent component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 454(C), pages 11-23.
    24. Dror Y. Kenett & Xuqing Huang & Irena Vodenska & Shlomo Havlin & H. Eugene Stanley, 2015. "Partial correlation analysis: applications for financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 569-578, April.
    25. Gao-Feng Gu & Wei-Xing Zhou, 2010. "Detrending moving average algorithm for multifractals," Papers 1005.0877, arXiv.org, revised Jun 2010.
    26. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Bao-Gen & Ling, Dian-Yi & Yu, Zu-Guo, 2021. "Multifractal temporally weighted detrended partial cross-correlation analysis of two non-stationary time series affected by common external factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    2. Guo, Yaoqi & Yu, Zhuling & Yu, Chenxi & Cheng, Hui & Chen, Weixun & Zhang, Hongwei, 2021. "Asymmetric multifractal features of the price–volume correlation in China’s gold futures market based on MF-ADCCA," Research in International Business and Finance, Elsevier, vol. 58(C).
    3. Wang, Yan & Wang, Yue & Li, Ming-Xia, 2019. "Regional characteristics of sports industry profitability: Evidence from China’s province level data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 946-955.
    4. Fernandes, Leonardo H.S. & Araújo, Fernando H.A., 2020. "Taxonomy of commodities assets via complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    5. S. Maria Immanuvel & D. Lazar, 2023. "Does Information Spillover and Leverage Effect Exist in World Gold Markets?," Global Business Review, International Management Institute, vol. 24(3), pages 475-487, June.
    6. Tilfani, Oussama & Kristoufek, Ladislav & Ferreira, Paulo & El Boukfaoui, My Youssef, 2022. "Heterogeneity in economic relationships: Scale dependence through the multivariate fractal regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    7. Diniz-Maganini, Natalia & Diniz, Eduardo H. & Rasheed, Abdul A., 2021. "Bitcoin’s price efficiency and safe haven properties during the COVID-19 pandemic: A comparison," Research in International Business and Finance, Elsevier, vol. 58(C).
    8. Ge, Xinlei & Lin, Aijing, 2023. "Quantifying the direct and indirect interactions for EEG signals by using detrended permutation mutual information," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    9. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    10. Zeng, Sheng & Liu, Xinchun & Li, Xiafei & Wei, Qi & Shang, Yue, 2019. "Information dominance among hedging assets: Evidence from return and volatility directional spillovers in time and frequency domains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    11. Lima, Cristiane Rocha Albuquerque & de Melo, Gabriel Rivas & Stosic, Borko & Stosic, Tatijana, 2019. "Cross-correlations between Brazilian biofuel and food market: Ethanol versus sugar," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 687-693.
    12. Feng, Yun & Yang, Jie & Huang, Qian, 2023. "Multiscale correlation analysis of Sino-US corn futures markets and the impact of international crude oil price: A new perspective from the multifractal method," Finance Research Letters, Elsevier, vol. 53(C).
    13. Shen, Na & Chen, Jiayi, 2023. "Asymmetric multifractal spectrum distribution based on detrending moving average cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    14. Ferreira, Paulo & Pereira, Éder Johson de Area Leão & Silva, Marcus Fernandes da & Pereira, Hernane Borges, 2019. "Detrended correlation coefficients between oil and stock markets: The effect of the 2008 crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 86-96.
    15. Zhicheng Liang & Junwei Wang & Kin Keung Lai, 2020. "Dependence Structure Analysis and VaR Estimation Based on China’s and International Gold Price: A Copula Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 169-193, February.
    16. Chen, Hong & Zhu, Li & Jia, GuoZhu, 2020. "MF-DCCA between molecular properties and aqueous solubility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    17. Maria Immanuvel S & Daniel Lazar, 2022. "Does Volume of Gold Consumption Influence the World Gold Price?," JRFM, MDPI, vol. 15(7), pages 1-14, June.
    18. Bouazizi, Tarek & Galariotis, Emilios & Guesmi, Khaled & Makrychoriti, Panagiota, 2023. "Investigating the nature of interaction between crypto-currency and commodity markets," International Review of Financial Analysis, Elsevier, vol. 88(C).
    19. Wang, Lei & Liu, Lutao, 2020. "Long-range correlation and predictability of Chinese stock prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lu, Xinsheng & Sun, Xinxin & Ge, Jintian, 2017. "Dynamic relationship between Japanese Yen exchange rates and market anxiety: A new perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 144-161.
    2. Guo, Yaoqi & Yu, Zhuling & Yu, Chenxi & Cheng, Hui & Chen, Weixun & Zhang, Hongwei, 2021. "Asymmetric multifractal features of the price–volume correlation in China’s gold futures market based on MF-ADCCA," Research in International Business and Finance, Elsevier, vol. 58(C).
    3. Ruan, Qingsong & Bao, Junjie & Zhang, Manqian & Fan, Limin, 2019. "The effects of exchange rate regime reform on RMB markets: A new perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 122-134.
    4. Chatterjee, Sucharita & Ghosh, Dipak, 2021. "Impact of Global Warming on SENSEX fluctuations — A study based on Multifractal detrended cross correlation analysis between the temperature anomalies and the SENSEX fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    5. Chatterjee, Sucharita, 2020. "Analysis of the human gait rhythm in Neurodegenerative disease: A multifractal approach using Multifractal detrended cross correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    6. Li, Shuping & Li, Jianfeng & Lu, Xinsheng & Sun, Yihong, 2022. "Exploring the dynamic nonlinear relationship between crude oil price and implied volatility indices: A new perspective from MMV-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    7. Ruan, Qingsong & Zhang, Manqian & Lv, Dayong & Yang, Haiquan, 2018. "SAD and stock returns revisited: Nonlinear analysis based on MF-DCCA and Granger test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1009-1022.
    8. 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).
    9. Yao, Can-Zhong & Lin, Ji-Nan & Zheng, Xu-Zhou, 2017. "Coupling detrended fluctuation analysis for multiple warehouse-out behavioral sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 75-90.
    10. Shen, Chenhua, 2017. "A comparison of principal components using TPCA and nonstationary principal component analysis on daily air-pollutant concentration series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 453-464.
    11. Ruan, Qingsong & Zhou, Mi & Yin, Linsen & Lv, Dayong, 2021. "Hedging effectiveness of Chinese Treasury bond futures: New evidence based on nonlinear analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    12. Shen, Na & Chen, Jiayi, 2023. "Asymmetric multifractal spectrum distribution based on detrending moving average cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    13. Wang, Fang & Yang, Zhaohui & Wang, Lin, 2016. "Detecting and quantifying cross-correlations by analogous multifractal height cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 954-962.
    14. Shen, Chen-hua & Li, Cao-ling, 2016. "An analysis of the intrinsic cross-correlations between API and meteorological elements using DPCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 446(C), pages 100-109.
    15. Li, Tingyi & Xue, Leyang & Chen, Yu & Chen, Feier & Miao, Yuqi & Shao, Xinzeng & Zhang, Chenyi, 2018. "Insights from multifractality analysis of tanker freight market volatility with common external factor of crude oil price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 374-384.
    16. Sun, Xinxin & Lu, Xinsheng & Yue, Gongzheng & Li, Jianfeng, 2017. "Cross-correlations between the US monetary policy, US dollar index and crude oil market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 326-344.
    17. Li, Jianfeng & Lu, Xinsheng & Jiang, Wei & Petrova, Vanya S., 2021. "Multifractal Cross-correlations between foreign exchange rates and interest rate spreads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    18. Li, Wei & Lu, Xinsheng & Ren, Yongping & Zhou, Ying, 2018. "Dynamic relationship between RMB exchange rate index and stock market liquidity: A new perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 726-739.
    19. Wang, Fang & Wang, Lin & Chen, Yuming, 2018. "Quantifying the range of cross-correlated fluctuations using a q–L dependent AHXA coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 454-464.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:490:y:2018:i:c:p:504-512. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.