IDEAS home Printed from https://ideas.repec.org/a/mes/emfitr/v54y2018i9p2021-2039.html
   My bibliography  Save this article

Role of Algorithmic and Co-Location Trading on the Speed of Information Adjustments: Evidence from India

Author

Listed:
  • Mohammad Shameem Jawed
  • Prasenjit Chakrabarti

Abstract

We investigate whether increased Algorithmic Trading (AT) intensity caused by the introduction of Co-location trading (CLT) facilities improve the productive efficiency of the Indian stock indices. We measure the change in the speed of information adjustment and change of persistence before and after the introduction of CLT for Indian Indices. We report an improvement in the overall productive efficiency of the leading Indian Indices, Midcap and Smallcap indices being the prominent beneficiaries. Our work contributes to the empirical literature on the ongoing debate on the benefits of AT and its role in improving market efficiency, especially in the emerging markets context.

Suggested Citation

  • Mohammad Shameem Jawed & Prasenjit Chakrabarti, 2018. "Role of Algorithmic and Co-Location Trading on the Speed of Information Adjustments: Evidence from India," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(9), pages 2021-2039, July.
  • Handle: RePEc:mes:emfitr:v:54:y:2018:i:9:p:2021-2039
    DOI: 10.1080/1540496X.2017.1342243
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1540496X.2017.1342243
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/1540496X.2017.1342243?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. Ramos, Henrique Pinto & Perlin, Marcelo Scherer, 2020. "Does algorithmic trading harm liquidity? Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    2. Ersan, Oguz & Simsir, Serif Aziz & Simsek, Koray D. & Hasan, Afan, 2021. "The speed of stock price adjustment to corporate announcements: Insights from Turkey," Emerging Markets Review, Elsevier, vol. 47(C).

    More about this item

    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:mes:emfitr:v:54:y:2018:i:9:p:2021-2039. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/MREE20 .

    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.