IDEAS home Printed from https://ideas.repec.org/a/ris/qjatoe/0181.html
   My bibliography  Save this article

Investigation of the volatility spillover effect and dynamic conditional correlations in Tehran Stock Exchange using wavelet-based Bayesian conditional variance heteroscedasticity

Author

Listed:
  • Hoseeini Ebrahimabad, S.A

    (Ph.D. Student in Economics, Urmia University)

  • Jahangiri, Kh

    (Assistant Professor of Financial Economics, Urmia University)

  • Ghaemi Asl, M

    (Assistant Professor of Islamic Economics and Banking, Kharazmi University)

  • Heydari, H

    (Professor of Economics, Urmia University)

Abstract

Skewness, fat tails and frequency dimension are important features of financial time series that have not been taken into account in classical econometric models. Therefore, in this study, the Bayesian method for conditional variance heteroscedasticity based on wavelet analysis has been used to investigate the volatility spillover effect and dynamic conditional correlations in three sub-periods between the daily return data of selected Tehran Stock Exchange (TSE) indices during the period from December 14, 2008 to April 20, 2019. Sub-periods are defined according to the Iran nuclear deal and agreement between Iran and the P5+1, known as Joint Comprehensive Plan of Action (JCPOA), which includes the pre-JCPOA period, JCPOA period, and the period after United States withdrawal from the JCPOA. The results of the Bayesian DCC GARCH (1,1) model, with the rejection of the constant conditional correlation hypothesis versus the dynamic conditional correlation hypothesis based on posterior marginal distribution in all subsections, indicates that the impact of shocks on the volatility of stock returns in wavelets and sub-periods are not the same. Also, Bayesian dynamic conditional correlation graphs are recommended for each sub-periods and in each wavelet, a different stock for a suitable investment

Suggested Citation

  • Hoseeini Ebrahimabad, S.A & Jahangiri, Kh & Ghaemi Asl, M & Heydari, H, 2020. "Investigation of the volatility spillover effect and dynamic conditional correlations in Tehran Stock Exchange using wavelet-based Bayesian conditional variance heteroscedasticity," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 7(1), pages 149-184, May.
    • Handle: RePEc:ris:qjatoe:0181
    as

    Download full text from publisher

    File URL: https://ecoj.tabrizu.ac.ir/article_10724_1c58c1467871cd786d1184f7f2513b94.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Spillovers Effect; Conditional Variance; Bayesian Approach; Selected Indices of the Tehran Stock Exchange;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:ris:qjatoe:0181. 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: Sakineh Sojoodi (email available below). General contact details of provider: https://edirc.repec.org/data/fetabir.html .

    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.