IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1608.01103.html
   My bibliography  Save this paper

Fluctuation of USA Gold Price - Revisited with Chaos-based Complex Network Method

Author

Listed:
  • Susmita Bhaduri
  • Dipak Ghosh
  • Subhadeep Ghosh

Abstract

We give emphasis on the use of chaos-based rigorous nonlinear technique called Visibility Graph Analysis, to study one economic time series - gold price of USA. This method can offer reliable results with fiinite data. This paper reports the result of such an analysis on the times series depicting the fluctuation of gold price of USA for the span of 25 years(1990 - 2013). This analysis reveals that a quantitative parameter from the theory can explain satisfactorily the real life nature of fluctuation of gold price of USA and hence building a strong database in terms of a quantitative parameter which can eventually be used for forecasting purpose.

Suggested Citation

  • Susmita Bhaduri & Dipak Ghosh & Subhadeep Ghosh, 2016. "Fluctuation of USA Gold Price - Revisited with Chaos-based Complex Network Method," Papers 1608.01103, arXiv.org.
    • Handle: RePEc:arx:papers:1608.01103
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1608.01103
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Long, Yu, 2013. "Visibility graph network analysis of gold price time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3374-3384.
    Full references (including those not matched with items on IDEAS)

    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. Sainaghi, Ruggero & Baggio, Rodolfo, 2017. "Complexity traits and dynamics of tourism destinations," Tourism Management, Elsevier, vol. 63(C), pages 368-382.
    2. Wang, Minggang & Tian, Lixin, 2016. "From time series to complex networks: The phase space coarse graining," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 456-468.
    3. Peng, Xiaoyi & Zhao, Yi & Small, Michael, 2020. "Identification and prediction of bifurcation tipping points using complex networks based on quasi-isometric mapping," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:1608.01103. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.