IDEAS home Printed from https://ideas.repec.org/a/wly/japmet/v34y2019i1p129-148.html
   My bibliography  Save this article

Information flows and stock market volatility

Author

Listed:
  • Chew Lian Chua
  • Sarantis Tsiaplias

Abstract

This study examines how news is distributed across stocks. A model is developed that categorizes a stock's latent news into normal and nonnormal news, and allows both types of news to be filtered through to other stocks. This is achieved by formulating a model that jointly incorporates a multivariate lognormal‐Poisson jump process (for nonnormal news) and a multivariate GARCH process (for normal news), in addition to a news (or shock) transmission mechanism that allows the shocks from both processes to impact intertemporally on all stocks in the system. The relationship between news and the expected volatility surface is explored and a unique news impact surface is derived that depends on time, news magnitude, and news type. We find that the effect of nonnormal news on volatility expectations typically builds up before dissipating, with the news transmission mechanism effectively crowding‐out normal news and crowding‐in nonnormal news. Moreover, in contrast to the standard approach for measuring leverage effects using asymmetric generalized autoregressive conditional heteroskedasticity models, we find that leverage effects stem predominantly from nonnormal news. Finally, we find that the capacity to identify positively or negatively correlated stock returns is ambiguous in the short term, and depends heavily on the behavior of the nonnormal news component.

Suggested Citation

  • Chew Lian Chua & Sarantis Tsiaplias, 2019. "Information flows and stock market volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(1), pages 129-148, January.
    • Handle: RePEc:wly:japmet:v:34:y:2019:i:1:p:129-148
    DOI: 10.1002/jae.2649
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/jae.2649
    Download Restriction: no
    File URL: https://libkey.io/10.1002/jae.2649?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
    ---><---

    Citations

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


    Cited by:

    1. Shamrez Ali, Sundus Waqar, Muhammad Haris, 2019. "The Nexus between Political & Institutional Corruption Events with the Stock Market: A Study of Pakistan," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 4(1), pages 59-71, March.
    2. Li, Chenxing & Maheu, John M, 2020. "A Multivariate GARCH-Jump Mixture Model," MPRA Paper 104770, University Library of Munich, Germany.
    3. Nappo, Giovanna & Marchetti, Fabio Massimo & Vagnani, Gianluca, 2023. "Traders’ heterogeneous beliefs about stock volatility and the implied volatility skew in financial options markets," Finance Research Letters, Elsevier, vol. 53(C).
    4. Hong, Ziyang & Liu, Qingfu & Tse, Yiuman & Wang, Zilu, 2023. "Black mouth, investor attention, and stock return," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    6. Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(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:wly:japmet:v:34:y:2019:i:1:p:129-148. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0883-7252/ .

    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.