IDEAS home Printed from https://ideas.repec.org/a/eee/jimfin/v44y2014icp47-68.html
   My bibliography  Save this article

Downside risk and portfolio diversification in the euro-zone equity markets with special consideration of the crisis period

Author

Listed:
  • Liu, Tengdong
  • Hammoudeh, Shawkat
  • Santos, Paulo Araújo

Abstract

This study examines the Value-at-Risk for ten euro-zone equity markets individually and also divided into two groups: PIIGS (Portugal, Italy, Ireland, Greece and Spain) and the Core (Austria, Finland, France, Germany and the Netherlands), employing four VaR estimation and evaluation methods considered over the full period and the pre- and post-global crisis subperiods 1 and 2. The backtesting results are also evaluated according to the Basel capital requirements. The results demonstrate that the CEVT methods meet all the statistical criteria the best for most individual equity indices over the full period, but these results over the two subperiods for those two methods are mixed, compared to those the DPOT methods. Moreover, the two optimal group portfolios of the PIIGS and the Core as well as the grand portfolio that combines the ten indices do not show much diversification benefits. The PIIGS portfolio selects Spain's IBEX only, while that of the Core opts for Austria's ATX only in the full period and subperiod 1. However, Germany's DAX overwhelmingly dominates both the Core and the Grand portfolios in subperiod 2.

Suggested Citation

  • Liu, Tengdong & Hammoudeh, Shawkat & Santos, Paulo Araújo, 2014. "Downside risk and portfolio diversification in the euro-zone equity markets with special consideration of the crisis period," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 47-68.
    • Handle: RePEc:eee:jimfin:v:44:y:2014:i:c:p:47-68
    DOI: 10.1016/j.jimonfin.2014.01.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0261560614000163
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jimonfin.2014.01.006?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. Kpate ADJAOUTÉ, & Jean-Pierre DANTHINE, 2000. "EMU and Portfolio Diversification Opportunities," FAME Research Paper Series rp31, International Center for Financial Asset Management and Engineering.
    2. Adjaoute, K. & Danthine, J.P., 2001. "Portfolio Diversification: Alive and well In Euroland," Papers 32, Manitoba - Department of Economics.
    3. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    4. Jansen, Dennis W. & Koedijk, Kees G. & de Vries, Casper G., 2000. "Portfolio selection with limited downside risk," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 247-269, November.
    5. Moerman, Gerard A., 2008. "Diversification in euro area stock markets: Country versus industry," Journal of International Money and Finance, Elsevier, vol. 27(7), pages 1122-1134, November.
    6. Basak, Suleyman & Shapiro, Alexander, 2001. "Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
    7. Cotter, John, 2004. "Downside Risk for European Equity Markets," MPRA Paper 3537, University Library of Munich, Germany.
    8. Billio, Monica & Pelizzon, Loriana, 2000. "Value-at-Risk: a multivariate switching regime approach," Journal of Empirical Finance, Elsevier, vol. 7(5), pages 531-554, December.
    9. Campbell, Rachel & Huisman, Ronald & Koedijk, Kees, 2001. "Optimal portfolio selection in a Value-at-Risk framework," Journal of Banking & Finance, Elsevier, vol. 25(9), pages 1789-1804, September.
    10. Araújo Santos, P. & Fraga Alves, M.I., 2012. "A new class of independence tests for interval forecasts evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3366-3380.
    11. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    12. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    13. Michael Mcaleer & Bernardo da Veiga, 2008. "Forecasting value-at-risk with a parsimonious portfolio spillover GARCH (PS-GARCH) model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 1-19.
    14. Araújo Santos, P. & Fraga Alves, M.I., 2013. "Forecasting Value-at-Risk with a duration-based POT method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 295-309.
    15. Francesca Carrieri & Vihang Errunza & Sergei Sarkissian, 2004. "Industry Risk and Market Integration," Management Science, INFORMS, vol. 50(2), pages 207-221, February.
    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. Miralles-Quirós, José Luis & Miralles-Quirós, María del Mar, 2017. "The Copula ADCC-GARCH model can help PIIGS to fly," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 1-12.
    2. Alexander, Carol & Korovilas, Dimitris & Kapraun, Julia, 2016. "Diversification with volatility products," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 213-235.
    3. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Kang, Sang Hoon, 2016. "Global financial crisis and spillover effects among the U.S. and BRICS stock markets," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 257-276.

    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. Sarafrazi, Soodabeh & Hammoudeh, Shawkat & AraújoSantos, Paulo, 2014. "Downside risk, portfolio diversification and the financial crisis in the euro-zone," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 368-396.
    2. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    3. Timotheos Angelidis & Alexandros Benos, 2008. "Value-at-Risk for Greek Stocks," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 67-104, March-Jun.
    4. Stelios Bekiros & Nikolaos Loukeris & Iordanis Eleftheriadis & Christos Avdoulas, 2019. "Tail-Related Risk Measurement and Forecasting in Equity Markets," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 783-816, February.
    5. James M. O'Brien & Pawel J. Szerszen, 2014. "An Evaluation of Bank VaR Measures for Market Risk During and Before the Financial Crisis," Finance and Economics Discussion Series 2014-21, Board of Governors of the Federal Reserve System (U.S.).
    6. Maziar Sahamkhadam & Andreas Stephan, 2019. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for the financial crisis," Papers 1912.10328, arXiv.org.
    7. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
    8. O’Brien, James & Szerszeń, Paweł J., 2017. "An evaluation of bank measures for market risk before, during and after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 215-234.
    9. Jimenez-Martin, Juan-Angel & McAleer, Michael & Pérez-Amaral, Teodosio & Santos, Paulo Araújo, 2013. "GFC-robust risk management under the Basel Accord using extreme value methodologies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 223-237.
    10. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics.
    11. Krzysztof Echaust & Małgorzata Just, 2020. "Value at Risk Estimation Using the GARCH-EVT Approach with Optimal Tail Selection," Mathematics, MDPI, vol. 8(1), pages 1-24, January.
    12. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    13. Antonio Díaz & Gonzalo García-Donato & Andrés Mora-Valencia, 2017. "Risk quantification in turmoil markets," Risk Management, Palgrave Macmillan, vol. 19(3), pages 202-224, August.
    14. Wong, Woon K., 2010. "Backtesting value-at-risk based on tail losses," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 526-538, June.
    15. Farkas, Walter & Fringuellotti, Fulvia & Tunaru, Radu, 2020. "A cost-benefit analysis of capital requirements adjusted for model risk," Journal of Corporate Finance, Elsevier, vol. 65(C).
    16. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    17. Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2007. "A robust VaR model under different time periods and weighting schemes," Review of Quantitative Finance and Accounting, Springer, vol. 28(2), pages 187-201, February.
    18. Dias, Alexandra, 2014. "Semiparametric estimation of multi-asset portfolio tail risk," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 398-408.
    19. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    20. Angelidis, Timotheos & Degiannakis, Stavros, 2007. "Backtesting VaR Models: A Τwo-Stage Procedure," MPRA Paper 96327, University Library of Munich, Germany.

    More about this item

    Keywords

    Value at risk; Euro-zone equity markets; Augmented portfolios; Subperiods;
    All these keywords.

    JEL classification:

    • 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:eee:jimfin:v:44:y:2014:i:c:p:47-68. 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/inca/30443 .

    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.