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Optimal and investable portfolios: An empirical analysis with scenario optimization algorithms under crisis market prospects

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  • Al Janabi, Mazin A.M.

Abstract

This paper develops scenario optimization algorithms for the assessment of investable financial portfolios under crisis market outlooks. To this end, this research study examines from portfolio managers' standpoint the performance of optimum and investable portfolios subject to applying meaningful financial and operational constraints as a result of a financial turmoil. Specifically, the paper tests a number of alternative scenarios considering both long-only and long and short-sales positions subject to minimizing the Liquidity-Adjusted Value-at-Risk (LVaR) and various financial and operational constraints such as target expected return, portfolio trading volume, close-out periods and portfolio weights. Robust optimization algorithms to set coherent asset allocations for investment management industries in emerging markets and particularly in Gulf Cooperation Council (GCC) financial markets are developed. The results show that the obtained investable portfolios lie off the efficient frontier, but that long-only portfolios appear to lie much closer to the frontier than portfolios including both long and short-sales positions. The proposed optimization algorithms can be useful in developing enterprise-wide portfolio management models in light of the aftermaths of the most-recent financial crisis. The developed methodology and risk optimization algorithms can aid in advancing portfolio management practices in emerging markets and predominantly in the wake of the latest credit crunch.

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  • Al Janabi, Mazin A.M., 2014. "Optimal and investable portfolios: An empirical analysis with scenario optimization algorithms under crisis market prospects," Economic Modelling, Elsevier, vol. 40(C), pages 369-381.
    • Handle: RePEc:eee:ecmode:v:40:y:2014:i:c:p:369-381
    DOI: 10.1016/j.econmod.2013.11.021
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    Cited by:

    1. Al Janabi, Mazin A.M. & Ferrer, Román & Shahzad, Syed Jawad Hussain, 2019. "Liquidity-adjusted value-at-risk optimization of a multi-asset portfolio using a vine copula approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    2. Al Janabi, Mazin A.M. & Arreola Hernandez, Jose & Berger, Theo & Nguyen, Duc Khuong, 2017. "Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1121-1131.
    3. Jose Arreola Hernandez & Mazin A.M. Al Janabi, 2020. "Forecasting of dependence, market, and investment risks of a global index portfolio," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 512-532, April.
    4. Mazin A.M. Al Janabi, 2021. "Is optimum always optimal? A revisit of the mean‐variance method under nonlinear measures of dependence and non‐normal liquidity constraints," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 387-415, April.

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    More about this item

    Keywords

    Emerging markets; Financial engineering; Financial risk management; GCC financial markets; Liquidity-Adjusted Value-at-Risk; Optimization; Portfolio management; Stress testing;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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