IDEAS home Printed from https://ideas.repec.org/a/eee/poleco/v90y2025ipbs0176268025001314.html

Buy when there’s blood in the streets: How geopolitical adverse events can push defense stock returns to the extreme

Author

Listed:
  • Neto, David

Abstract

In this paper, we address the controversial question of whether the defense sector can benefit from adverse geopolitical events. To this end, we employ the Tail Index Regression (TIR) methodology proposed by Wang and Tsai (2009) and recently extended by Nicolau et al. (2023) to assess whether adverse geopolitical events drive extreme right-tail returns for ten major European and U.S. defense companies. Our results show that such shocks significantly amplify positive returns, but only for a subset of firms specializing in high-demand segments such as combat aviation, land-based military systems, and cybersecurity. Moreover, we find that geopolitical acts exert a stronger influence than threats, and that the impact is persistent over time for certain companies. Overall, while our findings highlight the heterogeneous exposure of defense firms to geopolitical risk, they also suggest that defense stocks may serve as effective hedging instruments during periods of elevated geopolitical tension, offering valuable insights for both policymakers and investors.

Suggested Citation

  • Neto, David, 2025. "Buy when there’s blood in the streets: How geopolitical adverse events can push defense stock returns to the extreme," European Journal of Political Economy, Elsevier, vol. 90(PB).
  • Handle: RePEc:eee:poleco:v:90:y:2025:i:pb:s0176268025001314
    DOI: 10.1016/j.ejpoleco.2025.102771
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0176268025001314
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejpoleco.2025.102771?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:eee:poleco:v:90:y:2025:i:pb:s0176268025001314. 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.elsevier.com/locate/inca/505544 .

    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.