IDEAS home Printed from https://ideas.repec.org/a/bit/bsrysr/v9y2018i2p8-17n2.html
   My bibliography  Save this article

CVaR in Measuring Sector's Risk on the Croatian Stock Exchange

Author

Listed:
  • Aljinović Zdravka
  • Trgo Andrea

    (Faculty of Economics, University of Split,Split, Croatia)

Abstract

Background: In this paper the well-known risk measurement method Conditional Value-at-Risk (CVaR) is applied to the Croatian stock market to estimate the risk for 8 sectors in Croatia. The method and an appropriate backtesting are applied to the sample of 29 stocks grouped into 8 sectors for the three different periods: the period of economic growth 2006-2007, the crisis period 2008-2009 and the post-crisis period 2013-2014, characterized by long-term economic stagnation in Croatia. Objectives: The objective of this paper is to estimate the risk of 8 sectors on the Croatian stock market in three different economic periods and to identify whether the sectors that are risky during the crisis period are the same sectors that are risky in the period of economic growth and economic stagnation. Methods/Approach: The Conditional Value-at-Risk method and an appropriate backtesting are applied. Results: Empirical findings indicate that sectors that are risky in the period of economic growth are not the same sectors that are risky during the period of economic crisis or stagnation. Conclusions: In all the three periods, the least risky sectors were Hotel-management, Tourism, Food, and Staples Retailing. The Construction sector in all the three periods was among the riskiest sectors

Suggested Citation

  • Aljinović Zdravka & Trgo Andrea, 2018. "CVaR in Measuring Sector's Risk on the Croatian Stock Exchange," Business Systems Research, Sciendo, vol. 9(2), pages 8-17, July.
  • Handle: RePEc:bit:bsrysr:v:9:y:2018:i:2:p:8-17:n:2
    DOI: 10.2478/bsrj-2018-0015
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/bsrj-2018-0015
    Download Restriction: no

    File URL: https://libkey.io/10.2478/bsrj-2018-0015?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
    ---><---

    References listed on IDEAS

    as
    1. Pérignon, Christophe & Smith, Daniel R., 2010. "The level and quality of Value-at-Risk disclosure by commercial banks," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 362-377, February.
    2. Acerbi, Carlo & Tasche, Dirk, 2002. "On the coherence of expected shortfall," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1487-1503, July.
    3. Houda Hafsa, 2015. "CVaR in Portfolio Optimization: An Essay on the French Market," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 6(2), pages 101-111, April.
    Full references (including those not matched with items on IDEAS)

    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. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2012. "When more is less: Using multiple constraints to reduce tail risk," Journal of Banking & Finance, Elsevier, vol. 36(10), pages 2693-2716.
    2. Peña, Juan Ignacio & Rodríguez, Rosa & Mayoral, Silvia, 2020. "Tail risk of electricity futures," Energy Economics, Elsevier, vol. 91(C).
    3. repec:hal:journl:hal-00880258 is not listed on IDEAS
    4. Righi, Marcelo Brutti & Borenstein, Denis, 2018. "A simulation comparison of risk measures for portfolio optimization," Finance Research Letters, Elsevier, vol. 24(C), pages 105-112.
    5. Kratz , Marie, 2013. "There is a VaR Beyond Usual Approximations," ESSEC Working Papers WP1317, ESSEC Research Center, ESSEC Business School.
    6. Marie Kratz, 2013. "There is a VaR Beyond Usual Approximations," Working Papers hal-00880258, HAL.
    7. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2015. "Shortfall Deviation Risk: An alternative to risk measurement," Papers 1501.02007, arXiv.org, revised May 2016.
    8. Fu, Tianwen & Zhuang, Xinkai & Hui, Yongchang & Liu, Jia, 2017. "Convex risk measures based on generalized lower deviation and their applications," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 27-37.
    9. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2015. "A comparison of Expected Shortfall estimation models," Journal of Economics and Business, Elsevier, vol. 78(C), pages 14-47.
    10. Sant’Anna, Leonardo Riegel & Righi, Marcelo Brutti & Müller, Fernanda Maria & Guedes, Pablo Cristini, 2022. "Risk measure index tracking model," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 361-383.
    11. Marcelo Brutti Righi & Fernanda Maria Muller & Marlon Ruoso Moresco, 2017. "On a robust risk measurement approach for capital determination errors minimization," Papers 1707.09829, arXiv.org, revised Oct 2020.
    12. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "Impact of multimodality of distributions on VaR and ES calculations," Documents de travail du Centre d'Economie de la Sorbonne 17019, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    13. Iulia Lupu & Ana Barbara Bobirca & Paul Gabriel Miclaus & Tudor Ciumara, 2020. "Risk Management of Companies Included in the EURO STOXX Sustainability Index. An Investors' Perception," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 22(55), pages 707-707, August.
    14. Juan Ignacio Pe~na & Rosa Rodriguez & Silvia Mayoral, 2022. "Tail Risk of Electricity Futures," Papers 2202.01732, arXiv.org.
    15. Müller, Fernanda Maria & Santos, Samuel Solgon & Righi, Marcelo Brutti, 2023. "A description of the COVID-19 outbreak role in financial risk forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    16. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "Impact of multimodality of distributions on VaR and ES calculations," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01491990, HAL.
    17. Marie Kratz, 2013. "There is a VaR beyond usual approximations," Papers 1311.0270, arXiv.org.
    18. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "Impact of multimodality of distributions on VaR and ES calculations," Post-Print halshs-01491990, HAL.
    19. Fernanda Maria Müller & Marcelo Brutti Righi, 2018. "Numerical comparison of multivariate models to forecasting risk measures," Risk Management, Palgrave Macmillan, vol. 20(1), pages 29-50, February.
    20. Chen, Zhiping & Yang, Li, 2011. "Nonlinearly weighted convex risk measure and its application," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1777-1793, July.
    21. Winter, Peter, 2007. "Managerial Risk Accounting and Control – A German perspective," MPRA Paper 8185, University Library of Munich, Germany.

    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:bit:bsrysr:v:9:y:2018:i:2:p:8-17:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    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.