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Dependence Analysis of the ISE100 Banking Sector Using Vine Copula

Author

Listed:
  • Bukre Yildirim Kulekci

    (Technical University of Kaiserslautern, Department of Mathematics, Kaiserslautern, Germany)

  • Gulden Poyraz

    (Bandirma Onyedi Eylul University, Foreign Department of Commerce, Balikesir, Turkiye)

  • Ismail Gur

    (Dr. Student, Hacettepe University, Actuary Department of Sciences, Ankara, Turkiye)

  • Ozan Evkaya

    (Edinburgh, University of Edinburgh, Department of Mathematics, Edinburgh, England)

Abstract

The frequently observed time-varying trends and dependence in recent years within financial markets have been essential for modeling and pricing. This study aims to analyze the dependence structure of banking sector stocks traded on the ISE100 index using time series and regular vine (R-vine) copula models. The study calculates the risk measures of value-at-risk (VaR) and expected shortfall (ES) and tests with backtesting methods for the portfolio that are constructed by equally weighting the banking stocks. This study’s findings on banking stocks specifically indicate that the application of the R-vine copula combined with the generalized auto-regressive conditional heteroskedasticity (GARCH) model improved the VaR and ES estimates compared to traditional GARCH-based approaches..

Suggested Citation

  • Bukre Yildirim Kulekci & Gulden Poyraz & Ismail Gur & Ozan Evkaya, 2023. "Dependence Analysis of the ISE100 Banking Sector Using Vine Copula," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 73(73-1), pages 55-81, June.
    • Handle: RePEc:ist:journl:v:73:y:2023:i:1:p:55-81
    DOI: 10.26650/ISTJECON2022-1229039
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    References listed on IDEAS

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    1. David E. Allen & Mohammad A. Ashraf & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2013. "Financial dependence analysis: applications of vine copulas," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(4), pages 403-435, November.
    2. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    3. Prince Osei Mensah & Anokye M. Adam, 2020. "Copula-Based Assessment of Co-Movement and Tail Dependence Structure Among Major Trading Foreign Currencies in Ghana," Risks, MDPI, vol. 8(2), pages 1-20, June.
    4. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00492124, HAL.
    5. Marco Geidosch & Matthias Fischer, 2016. "Application of Vine Copulas to Credit Portfolio Risk Modeling," JRFM, MDPI, vol. 9(2), pages 1-15, June.
    6. 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.).
    7. Pourkhanali, Armin & Kim, Jong-Min & Tafakori, Laleh & Fard, Farzad Alavi, 2016. "Measuring systemic risk using vine-copula," Economic Modelling, Elsevier, vol. 53(C), pages 63-74.
    8. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 130-168.
    9. Andrew J. Patton, 2008. "Copula-Based Models for Financial Time Series," OFRC Working Papers Series 2008fe21, Oxford Financial Research Centre.
    10. Michael Rockinger & Eric Jondeau, 2001. "Conditional Dependency of Financial Series: An Application of Copulas," Working papers 82, Banque de France.
    11. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Post-Print halshs-00492124, HAL.
    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. Mahir Binici & Bulent Koksal & Cuneyt Orman, 2013. "Stock Return Co-movement and Systemic Risk in the Turkish Banking System," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 13(Special I), pages 41-63.
    14. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    15. Aleksey Min & Claudia Czado, 2010. "Bayesian Inference for Multivariate Copulas Using Pair-Copula Constructions," Journal of Financial Econometrics, Oxford University Press, vol. 8(4), pages 511-546, Fall.
    16. Aloui, Riadh & Ben Aïssa, Mohamed Safouane & Nguyen, Duc Khuong, 2013. "Conditional dependence structure between oil prices and exchange rates: A copula-GARCH approach," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 719-738.
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    Keywords

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    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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