IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v99y2017icp36-44.html
   My bibliography  Save this article

Causal relationship between the global foreign exchange market based on complex networks and entropy theory

Author

Listed:
  • Cao, Guangxi
  • Zhang, Qi
  • Li, Qingchen

Abstract

The foreign exchange (FX) market is a typical complex dynamic system under the background of exchange rate marketization reform and is an important part of the financial market. This study aims to generate an international FX network based on complex network theory. This study employs the mutual information method to judge the nonlinear characteristics of 54 major currencies in international FX markets. Through this method, we find that the FX network possesses a small average path length and a large clustering coefficient under different thresholds and that it exhibits small-world characteristics as a whole. Results show that the relationship between FX rates is close. Volatility can quickly transfer in the whole market, and the FX volatility of influential individual states transfers at a fast pace and a large scale. The period from July 21, 2005 to March 31, 2015 is subdivided into three sub-periods (i.e., before, during, and after the US sub-prime crisis) to analyze the topology evolution of FX markets using the maximum spanning tree approach. Results show that the USD gradually lost its core position, EUR remained a stable center, and the center of the Asian cluster became unstable. Liang's entropy theory is used to analyze the causal relationship between the four large clusters of the world.

Suggested Citation

  • Cao, Guangxi & Zhang, Qi & Li, Qingchen, 2017. "Causal relationship between the global foreign exchange market based on complex networks and entropy theory," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 36-44.
    • Handle: RePEc:eee:chsofr:v:99:y:2017:i:c:p:36-44
    DOI: 10.1016/j.chaos.2017.03.039
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077917300991
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2017.03.039?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. Gang-Jin Wang & Chi Xie & Peng Zhang & Feng Han & Shou Chen, 2014. "Dynamics of Foreign Exchange Networks: A Time-Varying Copula Approach," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-11, May.
    2. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    3. 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.
    4. Nobi, Ashadun & Maeng, Seong Eun & Ha, Gyeong Gyun & Lee, Jae Woo, 2014. "Effects of global financial crisis on network structure in a local stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 135-143.
    5. Yang, Chunxia & Chen, Yanhua & Niu, Lei & Li, Qian, 2014. "Cointegration analysis and influence rank—A network approach to global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 168-185.
    6. Huang, Wei-Qiang & Zhuang, Xin-Tian & Yao, Shuang, 2009. "A network analysis of the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2956-2964.
    7. Sensoy, Ahmet & Tabak, Benjamin M., 2014. "Dynamic spanning trees in stock market networks: The case of Asia-Pacific," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 387-402.
    8. Majapa, Mohamed & Gossel, Sean Joss, 2016. "Topology of the South African stock market network across the 2008 financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 35-47.
    9. Stošić, Darko & Stošić, Dusan & Stošić, Tatijana & Stanley, H. Eugene, 2015. "Multifractal analysis of managed and independent float exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 13-18.
    10. Riccetti, Luca & Russo, Alberto & Gallegati, Mauro, 2016. "Stock market dynamics, leveraged network-based financial accelerator and monetary policy," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 509-524.
    11. Jang, Wooseok & Lee, Junghoon & Chang, Woojin, 2011. "Currency crises and the evolution of foreign exchange market: Evidence from minimum spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 707-718.
    12. Cao, Guangxi & Xu, Wei, 2016. "Multifractal features of EUA and CER futures markets by using multifractal detrended fluctuation analysis based on empirical model decomposition," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 212-222.
    13. Richard J. Williams & Neo D. Martinez, 2000. "Simple rules yield complex food webs," Nature, Nature, vol. 404(6774), pages 180-183, March.
    14. Souza, Sergio Rubens Stancato de & Silva, Thiago Christiano & Tabak, Benjamin Miranda & Guerra, Solange Maria, 2016. "Evaluating systemic risk using bank default probabilities in financial networks," Journal of Economic Dynamics and Control, Elsevier, vol. 66(C), pages 54-75.
    15. Djauhari, Maman Abdurachman & Gan, Siew Lee, 2015. "Optimality problem of network topology in stocks market analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 108-114.
    16. Wang, Gang-Jin & Xie, Chi & Chen, Shou & Yang, Jiao-Jiao & Yang, Ming-Yan, 2013. "Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3715-3730.
    17. Yao, Can-Zhong & Lin, Ji-Nan & Zheng, Xu-Zhou & Liu, Xiao-Feng, 2015. "The study of RMB exchange rate complex networks based on fluctuation mode," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 359-376.
    18. Cao, Guangxi & Cao, Jie & Xu, Longbing, 2013. "Asymmetric multifractal scaling behavior in the Chinese stock market: Based on asymmetric MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 797-807.
    19. Cao, Guangxi & Xu, Longbing & Cao, Jie, 2012. "Multifractal detrended cross-correlations between the Chinese exchange market and stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4855-4866.
    20. Matsushita, Raul & Gleria, Iram & Figueiredo, Annibal & Da Silva, Sergio, 2007. "Are Pound and Euro the Same Currency? - Updated," MPRA Paper 1981, University Library of Munich, Germany.
    21. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    22. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    23. Caraiani, Petre, 2012. "Characterizing emerging European stock markets through complex networks: From local properties to self-similar characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(13), pages 3629-3637.
    24. Tu, Chengyi, 2014. "Cointegration-based financial networks study in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 245-254.
    25. Cao, Guangxi & Cao, Jie & Xu, Longbing & He, LingYun, 2014. "Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 460-469.
    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. Lahmiri, Salim & Bekiros, Stelios, 2017. "Disturbances and complexity in volatility time series," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 38-42.
    2. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    3. Zhang, Ditian & Zhuang, Yangyang & Tang, Pan & Han, Qingying, 2022. "The evolution of foreign exchange market: A network view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P2).
    4. Zhu, Pengfei & Tang, Yong & Wei, Yu & Dai, Yimin, 2019. "Portfolio strategy of International crude oil markets: A study based on multiwavelet denoising-integration MF-DCCA method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    5. Chuangxia Huang & Xian Zhao & Renli Su & Xiaoguang Yang & Xin Yang, 2022. "Dynamic network topology and market performance: A case of the Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1962-1978, April.
    6. Xin Yang & Shigang Wen & Zhifeng Liu & Cai Li & Chuangxia Huang, 2019. "Dynamic Properties of Foreign Exchange Complex Network," Mathematics, MDPI, vol. 7(9), pages 1-19, September.
    7. Zhaoyi Xu & Yuqing Zeng & Yangrong Xue & Shenggang Yang, 2022. "Early Warning of Chinese Yuan’s Exchange Rate Fluctuation and Value at Risk Measure Using Neural Network Joint Optimization Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1293-1315, December.
    8. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    9. Liu, Xueyong & Jiang, Cheng, 2020. "The dynamic volatility transmission in the multiscale spillover network of the international stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    10. Wang, Zhuo & Shang, Pengjian, 2021. "Generalized entropy plane based on multiscale weighted multivariate dispersion entropy for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 142(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. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    2. Li, Jianxuan & Shi, Yingying & Cao, Guangxi, 2018. "Topology structure based on detrended cross-correlation coefficient of exchange rate network of the belt and road countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1140-1151.
    3. 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.
    4. Coletti, Paolo, 2016. "Comparing minimum spanning trees of the Italian stock market using returns and volumes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 246-261.
    5. Chen, Yuwen & Zheng, Tingting, 2017. "Asymmetric joint multifractal analysis in Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 10-19.
    6. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    7. Zhong, Tao & Peng, Qinke & Wang, Xiao & Zhang, Jing, 2016. "Novel indexes based on network structure to indicate financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 583-594.
    8. Huang, Chuangxia & Wen, Shigang & Li, Mengge & Wen, Fenghua & Yang, Xin, 2021. "An empirical evaluation of the influential nodes for stock market network: Chinese A-shares case," Finance Research Letters, Elsevier, vol. 38(C).
    9. Deviren, Seyma Akkaya & Deviren, Bayram, 2016. "The relationship between carbon dioxide emission and economic growth: Hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 429-439.
    10. Bilal Ahmed Memon & Rabia Tahir, 2021. "Examining Network Structures and Dynamics of World Energy Companies in Stock Markets: A Complex Network Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 329-344.
    11. Hosseini, Seyed Soheil & Wormald, Nick & Tian, Tianhai, 2021. "A Weight-based Information Filtration Algorithm for Stock-correlation Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    12. Gajardo, Gabriel & Kristjanpoller, Werner, 2017. "Asymmetric multifractal cross-correlations and time varying features between Latin-American stock market indices and crude oil market," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 121-128.
    13. Yao, Hongxing & Memon, Bilal Ahmed, 2019. "Network topology of FTSE 100 Index companies: From the perspective of Brexit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1248-1262.
    14. Chuangxia Huang & Xian Zhao & Renli Su & Xiaoguang Yang & Xin Yang, 2022. "Dynamic network topology and market performance: A case of the Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1962-1978, April.
    15. Mbatha, Vusisizwe Moses & Alovokpinhou, Sedjro Aaron, 2022. "The structure of the South African stock market network during COVID-19 hard lockdown," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    16. Yu, Jia-Wei & Xie, Wen-Jie & Jiang, Zhi-Qiang, 2018. "Early warning model based on correlated networks in global crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1335-1343.
    17. khoojine, Arash Sioofy & Han, Dong, 2019. "Network analysis of the Chinese stock market during the turbulence of 2015–2016 using log-returns, volumes and mutual information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1091-1109.
    18. Kartikay Gupta & Niladri Chatterjee, 2020. "Examining Lead-Lag Relationships In-Depth, With Focus On FX Market As Covid-19 Crises Unfolds," Papers 2004.10560, arXiv.org, revised May 2020.
    19. Huang, Chuangxia & Deng, Yunke & Yang, Xiaoguang & Cao, Jinde & Yang, Xin, 2021. "A network perspective of comovement and structural change: Evidence from the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 76(C).
    20. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.

    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:chsofr:v:99:y:2017:i:c:p:36-44. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.