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The Dynamic and Dependence of Takaful and Conventional Stock Return Behaviours: Evidence from the Insurance Industry in Saudi Arabia

Author

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  • Noureddine Benlagha

    (Qatar University)

  • Wael Hemrit

    (Al Imam Mohammad Ibn Saud Islamic University (IMSIU))

Abstract

This paper investigates the dynamics of volatility in the stock market using competing univariate GARCH specifications. Moreover, it provides a study of the pairwise correlation pattern of stock returns for a wide range of Saudi Arabian insurance business lines by using a dynamic DCC-GARCH model. Our results show that volatility responds asymmetrically to shocks with a persistence of variance in the stock return data, supporting the presence of irrational behaviour as well as the effectiveness of a cross-market diversification strategy. Finally, we reach a point at which, between every two-business line stock returns, there is a dynamic conditional correlation.

Suggested Citation

  • Noureddine Benlagha & Wael Hemrit, 2018. "The Dynamic and Dependence of Takaful and Conventional Stock Return Behaviours: Evidence from the Insurance Industry in Saudi Arabia," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(4), pages 285-323, December.
    • Handle: RePEc:kap:apfinm:v:25:y:2018:i:4:d:10.1007_s10690-018-9249-2
    DOI: 10.1007/s10690-018-9249-2
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    1. Hammoudeh, Shawkat & Mensi, Walid & Reboredo, Juan Carlos & Nguyen, Duc Khuong, 2014. "Dynamic dependence of the global Islamic equity index with global conventional equity market indices and risk factors," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 189-206.
    2. Naifar, Nader & Hammoudeh, Shawkat & Al dohaiman, Mohamed S., 2016. "Dependence structure between sukuk (Islamic bonds) and stock market conditions: An empirical analysis with Archimedean copulas," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 148-165.
    3. Alexis Guyot, 2011. "Efficiency and Dynamics of Islamic Investment: Evidence of Geopolitical Effects on Dow Jones Islamic Market Indexes," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 24-45, November.
    4. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    5. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    6. Shahzad, Syed Jawad Hussain & Ferrer, Román & Ballester, Laura & Umar, Zaghum, 2017. "Risk transmission between Islamic and conventional stock markets: A return and volatility spillover analysis," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 9-26.
    7. Alexis Guyot, 2011. "Efficiency and Dynamics of Islamic Investment: Evidence of Geopolitical Effects on Dow Jones Islamic Market Indexes," Post-Print hal-00841074, HAL.
    8. repec:cii:cepiei:2014-q1-137-5 is not listed on IDEAS
    9. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2002. "Dynamic Volume-Return Relation of Individual Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1005-1047.
    10. Mills,Terence C. & Markellos,Raphael N., 2008. "The Econometric Modelling of Financial Time Series," Cambridge Books, Cambridge University Press, number 9780521710091, September.
    11. Yilmaz, Mustafa K. & Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2015. "Cross-sectoral interactions in Islamic equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 32(C), pages 1-20.
    12. Mensi, Walid & Beljid, Makram & Boubaker, Adel & Managi, Shunsuke, 2013. "Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold," Economic Modelling, Elsevier, vol. 32(C), pages 15-22.
    13. Alam, Nafis & Arshad, Shaista & Rizvi, Syed Aun R., 2016. "Do Islamic stock indices perform better than conventional counterparts? An empirical investigation of sectoral efficiency," Review of Financial Economics, Elsevier, vol. 31(C), pages 108-114.
    14. Buerhan Saiti & Obiyathulla I. Bacha & Mansur Masih, 2014. "The diversification benefits from Islamic investment during the financial turmoil: The case for the US-based equity investors," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 14(4), pages 196-211, December.
    15. Majdoub, Jihed & Mansour, Walid & Jouini, Jamel, 2016. "Market integration between conventional and Islamic stock prices," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 436-457.
    16. Liang Peng, 2003. "Least absolute deviations estimation for ARCH and GARCH models," Biometrika, Biometrika Trust, vol. 90(4), pages 967-975, December.
    17. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    18. Peng, Liang & Yao, Qiwei, 2003. "Least absolute deviations estimation for ARCH and GARCH models," LSE Research Online Documents on Economics 5828, London School of Economics and Political Science, LSE Library.
    19. Akhter, Waheed & Pappas, Vasileios & Khan, Saad Ullah, 2017. "A comparison of Islamic and conventional insurance demand: Worldwide evidence during the Global Financial Crisis," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1401-1412.
    20. Engle, Robert & Colacito, Riccardo, 2006. "Testing and Valuing Dynamic Correlations for Asset Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 238-253, April.
    21. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    22. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    23. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    24. Godlewski, Christophe J. & Turk-Ariss, Rima & Weill, Laurent, 2013. "Sukuk vs. conventional bonds: A stock market perspective," Journal of Comparative Economics, Elsevier, vol. 41(3), pages 745-761.
    25. Walid M.A. Ahmed, 2012. "On the interdependence structure of market sector indices: the case of Qatar Exchange," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 11(4), pages 468-488, October.
    26. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    27. Fredj Jawadi & Nabila Jawadi & Waël Louhichi, 2014. "Conventional and Islamic stock price performance: An empirical investigation," International Economics, CEPII research center, issue 137, pages 73-87.
    28. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    29. R. F. Engle & A. J. Patton, 2001. "What good is a volatility model?," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 237-245.
    30. Jose Arreola Hernandez & Shawkat Hammoudeh & Duc Khuong Nguyen & Mazin A. M. Al Janabi & Juan Carlos Reboredo, 2017. "Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach," Applied Economics, Taylor & Francis Journals, vol. 49(25), pages 2409-2427, May.
    31. Dima Alberg & Haim Shalit & Rami Yosef, 2008. "Estimating stock market volatility using asymmetric GARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 18(15), pages 1201-1208.
    32. 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.
    33. S. J. Fowler & C. Hope, 2007. "Incorporating sustainable business practices into company strategy," Business Strategy and the Environment, Wiley Blackwell, vol. 16(1), pages 26-38, January.
    34. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
    35. Dutt, Tanuj & Humphery-Jenner, Mark, 2013. "Stock return volatility, operating performance and stock returns: International evidence on drivers of the ‘low volatility’ anomaly," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 999-1017.
    36. Mills,Terence C. & Markellos,Raphael N., 2008. "The Econometric Modelling of Financial Time Series," Cambridge Books, Cambridge University Press, number 9780521883818.
    37. Hirshleifer, David & Subrahmanyam, Avanidhar & Titman, Sheridan, 2006. "Feedback and the success of irrational investors," Journal of Financial Economics, Elsevier, vol. 81(2), pages 311-338, August.
    38. Noureddine Benlagha, 2014. "Dependence structure between nominal and index-linked bond returns: a bivariate copula and DCC-GARCH approach," Applied Economics, Taylor & Francis Journals, vol. 46(31), pages 3849-3860, November.
    39. Zaghum Umar & Tahir Suleman, 2017. "Asymmetric Return and Volatility Transmission in Conventional and Islamic Equities," Risks, MDPI, vol. 5(2), pages 1-18, March.
    40. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    41. Takaishi, Tetsuya, 2017. "Rational GARCH model: An empirical test for stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 451-460.
    42. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Ahmed, Walid M.A., 2019. "Islamic and conventional equity markets: Two sides of the same coin, or not?," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 191-205.
    2. Benlagha, Noureddine, 2020. "Stock market dependence in crisis periods: Evidence from oil price shocks and the Qatar blockade," Research in International Business and Finance, Elsevier, vol. 54(C).

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    More about this item

    Keywords

    Volatility; Stock returns; Insurance; Saudi Arabia; AR (1)-GJR–GARCH (1; 1); DCC-GARCH;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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