IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v18y2016icp302-305.html
   My bibliography  Save this article

Exposing volatility spillovers: A comparative analysis based on vector autoregressive models

Author

Listed:
  • Philippas, Dionisis
  • Dragomirescu-Gaina, Catalin

Abstract

We present a comparative analysis of two empirical methods grounded on a common vector autoregressive framework. In this setting, we investigate the time-varying nature and direction of volatility spillovers between some major stock indexes spanning across Europe, China and US. We find evidence that drawing on partial Granger causality brings more robust results than relying on the information provided by generalized impulse responses, especially when there is uncertainty about what other relevant factors need to be modelled.

Suggested Citation

  • Philippas, Dionisis & Dragomirescu-Gaina, Catalin, 2016. "Exposing volatility spillovers: A comparative analysis based on vector autoregressive models," Finance Research Letters, Elsevier, vol. 18(C), pages 302-305.
    • Handle: RePEc:eee:finlet:v:18:y:2016:i:c:p:302-305
    DOI: 10.1016/j.frl.2016.05.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612316300782
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2016.05.002?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.

    References listed on IDEAS

    as
    1. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    2. Alter, Adrian & Beyer, Andreas, 2014. "The dynamics of spillover effects during the European sovereign debt turmoil," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 134-153.
    3. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    4. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Dragomirescu-Gaina, Catalin & Galariotis, Emilios & Philippas, Dionisis, 2021. "Chasing the ‘green bandwagon’ in times of uncertainty," Energy Policy, Elsevier, vol. 151(C).
    2. Dragomirescu-Gaina, Catalin & Philippas, Dionisis, 2022. "Local versus global factors weighing on stock market returns during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 46(PA).
    3. Maghyereh, Aktham & Awartani, Basel & Abdoh, Hussein, 2022. "Asymmetric risk transfer in global equity markets: An extended sample that includes the COVID pandemic period," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liow, Kim Hiang & Huang, Yuting, 2018. "The dynamics of volatility connectedness in international real estate investment trusts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 195-210.
    2. José Da Fonseca & Katrin Gottschalk, 2020. "The Co‐Movement of Credit Default Swap Spreads, Equity Returns and Volatility: Evidence from Asia‐Pacific Markets," International Review of Finance, International Review of Finance Ltd., vol. 20(3), pages 551-579, September.
    3. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    4. Collet, Jerome & Ielpo, Florian, 2018. "Sector spillovers in credit markets," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 267-278.
    5. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 1-26.
    6. Garcia-de-Andoain, Carlos & Kremer, Manfred, 2017. "Beyond spreads: Measuring sovereign market stress in the euro area," Economics Letters, Elsevier, vol. 159(C), pages 153-156.
    7. Hachmi Ben Ameur & Waël Louhichi, 2022. "The Brexit impact on European market co-movements," Annals of Operations Research, Springer, vol. 313(2), pages 1387-1403, June.
    8. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    9. Thomas Conefrey & David Cronin, 2015. "Spillover in Euro Area Sovereign Bond Markets," The Economic and Social Review, Economic and Social Studies, vol. 46(2), pages 197-231.
    10. Ozcan Ceylan, 2023. "Analysis of Dynamic Connectedness among Sovereign CDS Premia," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 9(1), pages 33-47, June.
    11. Zhang, Yulian & He, Xie & Nakajima, Tadahiro & Hamori, Shigeyuki, 2020. "Oil, Gas, or Financial Conditions-Which One Has a Stronger Link with Growth?," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    12. Julián Andrada-Félix & Adrian Fernandez-Perez & Simón Sosvilla-Rivero, 2018. "Fear connectedness among asset classes," Applied Economics, Taylor & Francis Journals, vol. 50(39), pages 4234-4249, August.
    13. Tom Pak Wing FongAuthor-Workplace-Name: Research Department, Hong Kong Monetary Authority & Ka Fai LiAuthor-Workplace-Name: Research Department, Hong Kong Monetary Authority & Angela Kin Wan Sze, 2016. "Measuring Spillovers between the US and Emerging Markets," Working Papers 082016, Hong Kong Institute for Monetary Research.
    14. He, Xie & Hamori, Shigeyuki, 2021. "Is volatility spillover enough for investor decisions? A new viewpoint from higher moments," Journal of International Money and Finance, Elsevier, vol. 116(C).
    15. Alexander Pütz & Pierre L. Siklos & Christoph Sulewski, 2019. "“Who pays the piper calls the tune” – Networks and transaction costs in commodity markets," CQE Working Papers 8819, Center for Quantitative Economics (CQE), University of Muenster.
    16. Umar, Zaghum & Aharon, David Y. & Esparcia, Carlos & AlWahedi, Wafa, 2022. "Spillovers between sovereign yield curve components and oil price shocks," Energy Economics, Elsevier, vol. 109(C).
    17. Prasad, Nalin & Grant, Andrew & Kim, Suk-Joong, 2018. "Time varying volatility indices and their determinants: Evidence from developed and emerging stock markets," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 115-126.
    18. Fernández-Rodríguez, Fernando & Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2015. "Volatility spillovers in EMU sovereign bond markets," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 337-352.
    19. Nishimura, Yusaku & Tsutsui, Yoshiro & Hirayama, Kenjiro, 2018. "Do international investors cause stock market spillovers? Comparing responses of cross-listed stocks between accessible and inaccessible markets," Economic Modelling, Elsevier, vol. 69(C), pages 237-248.
    20. Long, Shaobo & Li, Zixuan, 2023. "Dynamic spillover effects of global financial stress: Evidence from the quantile VAR network," International Review of Financial Analysis, Elsevier, vol. 90(C).

    More about this item

    Keywords

    Partial Granger causality; Volatility spillovers; GIRFs;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • 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:finlet:v:18:y:2016:i:c:p:302-305. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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/frl .

    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.