IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v27y2022i1p1321-1339.html
   My bibliography  Save this article

Islamic portfolio optimization under systemic risk: Vine Copula‐CoVaR based model

Author

Listed:
  • Sana Braiek
  • Rihab Bedoui
  • Lotfi Belkacem

Abstract

We propose a new methodology based on CoVaR to optimize Islamic portfolio. First, we generate the return distribution using the ARMA‐FIAPARCH and ARMA‐FIGARCH model. Then, we transform the standardized residuals onto copula scale using the empirical cumulative distribution function. Thereafter, using the best vine‐copula fits, we computed downside and upside risk. We obtained CoVaR of the market (sectors), conditional on the VaR for sectors (market) returns. We find the optimized portfolio wt through mean‐CoVaR optimization. The empirical results of Islamic industry show that the optimal allocation is influenced by the existence of systemic risk. Thus, when comparing the mean‐CoVaR model with the mean–Variance model we find that mean‐CoVaR more performant in optimization. The minimum risk portfolio allocation is influenced by the existence of systemic risk, the interdependence structure between sectors and the optimization model. Our findings offer a better understanding of the allocation during the crisis period which is very valuable for the international investors, multinational corporations and portfolio managers.

Suggested Citation

  • Sana Braiek & Rihab Bedoui & Lotfi Belkacem, 2022. "Islamic portfolio optimization under systemic risk: Vine Copula‐CoVaR based model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1321-1339, January.
  • Handle: RePEc:wly:ijfiec:v:27:y:2022:i:1:p:1321-1339
    DOI: 10.1002/ijfe.2217
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.2217
    Download Restriction: no

    File URL: https://libkey.io/10.1002/ijfe.2217?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. Hua, Lei & Joe, Harry, 2011. "Second order regular variation and conditional tail expectation of multiple risks," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 537-546.
    2. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    3. Merton, Robert C., 1971. "Optimum consumption and portfolio rules in a continuous-time model," Journal of Economic Theory, Elsevier, vol. 3(4), pages 373-413, December.
    4. Umar, Zaghum, 2017. "Islamic vs conventional equities in a strategic asset allocation framework," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 1-10.
    5. Duan Li & Wan‐Lung Ng, 2000. "Optimal Dynamic Portfolio Selection: Multiperiod Mean‐Variance Formulation," Mathematical Finance, Wiley Blackwell, vol. 10(3), pages 387-406, July.
    6. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Systemic risk in European sovereign debt markets: A CoVaR-copula approach," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 214-244.
    7. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    8. Mossin, Jan, 1969. "Security Pricing and Investment Criteria in Competitive Markets," American Economic Review, American Economic Association, vol. 59(5), pages 749-756, December.
    9. Girardi, Giulio & Tolga Ergün, A., 2013. "Systemic risk measurement: Multivariate GARCH estimation of CoVaR," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3169-3180.
    10. Georgios E. Chortareas & Claudia Girardone & Alexia Ventouri, 2011. "Financial Frictions, Bank Efficiency and Risk: Evidence from the Eurozone," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(1-2), pages 259-287, January.
    11. Rahim, Adam Mohamed & Masih, Mansur, 2016. "Portfolio diversification benefits of Islamic investors with their major trading partners: Evidence from Malaysia based on MGARCH-DCC and wavelet approaches," Economic Modelling, Elsevier, vol. 54(C), pages 425-438.
    12. Kakouris, Iakovos & Rustem, Berç, 2014. "Robust portfolio optimization with copulas," European Journal of Operational Research, Elsevier, vol. 235(1), pages 28-37.
    13. Cumova, Denisa & Nawrocki, David, 2014. "Portfolio optimization in an upside potential and downside risk framework," Journal of Economics and Business, Elsevier, vol. 71(C), pages 68-89.
    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. Pejman Peykani & Mostafa Sargolzaei & Mohammad Hashem Botshekan & Camelia Oprean-Stan & Amir Takaloo, 2023. "Optimization of Asset and Liability Management of Banks with Minimum Possible Changes," Mathematics, MDPI, vol. 11(12), pages 1-24, June.

    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. He, Xue-Zhong & Li, Youwei, 2015. "Testing of a market fraction model and power-law behaviour in the DAX 30," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 1-17.
    2. Cvitanic, Jaksa & Lazrak, Ali & Wang, Tan, 2008. "Implications of the Sharpe ratio as a performance measure in multi-period settings," Journal of Economic Dynamics and Control, Elsevier, vol. 32(5), pages 1622-1649, May.
    3. Wan-Kai Pang & Yuan-Hua Ni & Xun Li & Ka-Fai Cedric Yiu, 2013. "Continuous-time Mean-Variance Portfolio Selection with Stochastic Parameters," Papers 1302.6669, arXiv.org.
    4. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Al-Yahyaee, Khamis Hamed & Shahbaz, Muhammad, 2017. "Oil and foreign exchange market tail dependence and risk spillovers for MENA, emerging and developed countries: VMD decomposition based copulas," Energy Economics, Elsevier, vol. 67(C), pages 476-495.
    5. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Risk spillovers and diversification between oil and non-ferrous metals during bear and bull market states," Resources Policy, Elsevier, vol. 72(C).
    6. Shahzad, Syed Jawad Hussain & Arreola-Hernandez, Jose & Bekiros, Stelios & Shahbaz, Muhammad & Kayani, Ghulam Mujtaba, 2018. "A systemic risk analysis of Islamic equity markets using vine copula and delta CoVaR modeling," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 104-127.
    7. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Shahbaz, Muhammad, 2017. "Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 258-279.
    8. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2008. "Heterogeneity, Market Mechanisms, and Asset Price Dynamics," Research Paper Series 231, Quantitative Finance Research Centre, University of Technology, Sydney.
    9. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    10. Sanchez-Romero, Miguel, 2006. "“Demand for Private Annuities and Social Security: Consequences to Individual Wealth”," Working Papers in Economic Theory 2006/07, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
    11. Orszag, J. Michael & Yang, Hong, 1995. "Portfolio choice with Knightian uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 19(5-7), pages 873-900.
    12. Reboredo, Juan C. & Ugolini, Andrea, 2015. "A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 98-123.
    13. Warshaw, Evan, 2019. "Extreme dependence and risk spillovers across north american equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 237-251.
    14. Baillie, Richard T. & Cho, Dooyeon, 2016. "Assessing Euro crises from a time varying international CAPM approach," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 197-208.
    15. Hafner, Christian M. & Herwartz, Helmut, 1999. "Time-varying market price of risk in the CAPM: Approaches, empirical evidence and implications," SFB 373 Discussion Papers 1999,22, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    16. Jun Yu, 2014. "Optimal Asset-Liability Management for an Insurer Under Markov Regime Switching Jump-Diffusion Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 21(4), pages 317-330, November.
    17. Rehman, Mobeen Ur, 2020. "Do bitcoin and precious metals do any good together? An extreme dependence and risk spillover analysis," Resources Policy, Elsevier, vol. 68(C).
    18. Mościbrodzka Monika & Homa Magdalena, 2019. "The efficiency of an investing in investment funds in the context of a longevity," Journal of Economics and Management, Sciendo, vol. 38(4), pages 107-128, December.
    19. Malevergne, Y. & Sornette, D., 2007. "Self-consistent asset pricing models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 149-171.
    20. Shimizu, Katsutoshi & Ly, Kim Cuong, 2017. "Were regulatory interventions effective in lowering systemic risk during the financial crisis in Japan?," Journal of Multinational Financial Management, Elsevier, vol. 41(C), pages 80-91.

    More about this item

    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:wly:ijfiec:v:27:y:2022:i:1:p:1321-1339. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.