IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v527y2019ics0378437119306521.html
   My bibliography  Save this article

High-frequency trading: Inverse relationship of the financial markets

Author

Listed:
  • Shafi, Khuram
  • Latif, Natasha
  • Shad, Shafqat Ali
  • Idrees, Zahra

Abstract

Integration of financial markets due to globalization generates new paradigms of financialization. And with HFT i.e. the high-frequency trading, financialization has distorted the relations of financial markets. HFT is based on highly complex financial products such as Index Options which are linked with volatility and it‘s forecasting. After the introduction of Volatility, VIX Index of Chicago Board of Options Exchange becomes the effective benchmark for stock market volatility now a day. Although VIX Index is a volatility measure derived from Standard and Poor 500 Index (SPX) option prices, traders are unaware of the inverse relationship between these markets. This study purpose is to understand the relationship between the two trading vehicles and increase the market awareness based on high order moment models which are used to mimic the behavior of these index options. It also explains the logic versus perception perspective in option pricing theory to develop theoretical foundations and consider it in future theory erection. Finding shows that SPX index is negatively correlated with VIX Index and financial markets have an inverse relationship between them.

Suggested Citation

  • Shafi, Khuram & Latif, Natasha & Shad, Shafqat Ali & Idrees, Zahra, 2019. "High-frequency trading: Inverse relationship of the financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
  • Handle: RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119306521
    DOI: 10.1016/j.physa.2019.121067
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119306521
    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.2019.121067?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.

    Citations

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


    Cited by:

    1. Chih-Chen Hsu & Chung-Gee Lin & Tsung-Jung Kuo, 2020. "Pricing of Arithmetic Asian Options under Stochastic Volatility Dynamics: Overcoming the Risks of High-Frequency Trading," Mathematics, MDPI, vol. 8(12), pages 1-16, December.

    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:527:y:2019:i:c:s0378437119306521. 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: 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.