IDEAS home Printed from https://ideas.repec.org/p/een/camaaa/2024-40.html
   My bibliography  Save this paper

Return and Volatility Spillovers between the Raw Material and Electric Vehicles Markets

Author

Listed:
  • Oleg Alekseev
  • Karel Janda
  • Mathieu Petit
  • David Zilberman

Abstract

This paper investigates the return and volatility spillovers between the upstream electric vehicles (EV) battery raw materials market and the individual downstream EV producers. The study uses the daily stock returns of two lithium producers and a new model in the GARCH family to capture the jump component of volatility in the EV battery raw materials market. Return and volatility spillovers are studied using an EGARCH(1,1) model including the excess stock returns of lithium producers in the mean equation and their jump component intensity in the variance equation. The results indicate that jumps exist in the EV battery raw materials market and that there exist significant return spillovers between lithium and EV producers. However, this paper didn’t find any strong evidence of the existence of volatility spillovers between these two markets through lithium unexpected news.

Suggested Citation

  • Oleg Alekseev & Karel Janda & Mathieu Petit & David Zilberman, 2024. "Return and Volatility Spillovers between the Raw Material and Electric Vehicles Markets," CAMA Working Papers 2024-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2024-40
    as

    Download full text from publisher

    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2024-06/40_2024_alekseev_janda_petit_zilberman_0.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    More about this item

    Keywords

    EVs; return spillovers; volatility spillovers; jump component; jump intensity; EGARCH-EARJI;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • L61 - Industrial Organization - - Industry Studies: Manufacturing - - - Metals and Metal Products; Cement; Glass; Ceramics
    • L62 - Industrial Organization - - Industry Studies: Manufacturing - - - Automobiles; Other Transportation Equipment; Related Parts and Equipment

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:een:camaaa:2024-40. 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: Cama Admin (email available below). General contact details of provider: https://edirc.repec.org/data/asanuau.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.