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Dynamic co-integration and portfolio diversification of Islamic and conventional indices: Global evidence

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  • Abu-Alkheil, Ahmad
  • Khan, Walayet A.
  • Parikh, Bhavik
  • Mohanty, Sunil K.

Abstract

A major issue in both Islamic and conventional finance is the performance of their respective stock indices. Using the stochastic dominance (SD) analysis, we examine whether Islamic stock indices outperform the conventional indices over the period from 2002 to 2014. We also examine the behavior of both risk averters and risk seekers with regard to the preference for Islamic or conventional indices. Moreover, employing the VARMAX procedure and Johansen’s co-integration approach we analyze the long term association of indices (co-integration), efficiency of Islamic indices, the existence of diversification benefits and portfolio optimization opportunities. Our sample consists of 32 conventional and 32 Islamic stock indices from FTSE, DJ, MSCI, S&Ps and Jakarta series. To capture the impact of the subprime global financial crisis of 2007 on indices performance, we split the overall sample period into pre crisis (2002–2006), crisis (2007–2009), and post crisis (2010–2014) periods.

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  • Abu-Alkheil, Ahmad & Khan, Walayet A. & Parikh, Bhavik & Mohanty, Sunil K., 2017. "Dynamic co-integration and portfolio diversification of Islamic and conventional indices: Global evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 212-224.
  • Handle: RePEc:eee:quaeco:v:66:y:2017:i:c:p:212-224
    DOI: 10.1016/j.qref.2017.02.005
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    More about this item

    Keywords

    Islamic finance; Islamic indices; Co-integration; Stochastic dominance;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • Z12 - Other Special Topics - - Cultural Economics - - - Religion
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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