IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-4-431-28915-9_7.html
   My bibliography  Save this book chapter

Scaling and Memory in Return Loss Intervals: Application to Risk Estimation

In: Practical Fruits of Econophysics

Author

Listed:
  • Kazuko Yamasaki

    (Center for Polymer Studies and Department of Physics Boston University
    Tokyo University of Information Sciences)

  • Lev Muchnik

    (Bar-Ilan University)

  • Shlomo Havlin

    (Bar-Ilan University)

  • Armin Bunde

    (Justus-Liebig-Universität)

  • H. Eugene Stanley

    (Center for Polymer Studies and Department of Physics Boston University)

Abstract

Summary We study the statistics of the return intervals τ q between two consecutive return losses below a threshold −q, in various stocks, currencies and commodities. We find the probability distribution function (pdf) of τ q scales with the mean return interval τ q in a quite universal way, which may enable us to extrapolate rare events from the behavior of more frequent events with better statistics. The functional form of the pdf shows deviation from a simple exponential behavior, suggesting memory effects in losses. The memory shows up strongly in the conditional mean loss return intervals which depend significantly on the previous interval. This dependence can be used to improve the estimate of the risk level.

Suggested Citation

  • Kazuko Yamasaki & Lev Muchnik & Shlomo Havlin & Armin Bunde & H. Eugene Stanley, 2006. "Scaling and Memory in Return Loss Intervals: Application to Risk Estimation," Springer Books, in: Hideki Takayasu (ed.), Practical Fruits of Econophysics, pages 43-51, Springer.
    • Handle: RePEc:spr:sprchp:978-4-431-28915-9_7
    DOI: 10.1007/4-431-28915-1_7
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Hao Meng & Fei Ren & Gao-Feng Gu & Xiong Xiong & Yong-Jie Zhang & Wei-Xing Zhou & Wei Zhang, 2012. "Effects of long memory in the order submission process on the properties of recurrence intervals of large price fluctuations," Papers 1201.2825, arXiv.org.
    2. Zhi-Qiang Jiang & Askery Canabarro & Boris Podobnik & H. Eugene Stanley & Wei-Xing Zhou, 2016. "Early warning of large volatilities based on recurrence interval analysis in Chinese stock markets," Quantitative Finance, Taylor & Francis Journals, vol. 16(11), pages 1713-1724, November.
    3. Xie, Wen-Jie & Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2014. "Extreme value statistics and recurrence intervals of NYMEX energy futures volatility," Economic Modelling, Elsevier, vol. 36(C), pages 8-17.
    4. Ni, Xiao-Hui & Jiang, Zhi-Qiang & Gu, Gao-Feng & Ren, Fei & Chen, Wei & Zhou, Wei-Xing, 2010. "Scaling and memory in the non-Poisson process of limit order cancelation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2751-2761.

    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:spr:sprchp:978-4-431-28915-9_7. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.