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Combining Momentum, Value, and Quality for the Islamic Equity Portfolio: Multi-style Rotation Strategies using Augmented Black Litterman Factor Model

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  • Dewandaru, Ginanjar
  • Masih, Rumi
  • Bacha, Obiyathulla
  • Masih, A. Mansur M.

Abstract

This study constructs active Islamic portfolios using a multi-style rotation strategy, derived from the three prominent styles, namely, momentum, value, and quality investing. We use the stocks that are consistently listed in the U.S. Dow Jones Islamic index for a sample period from 1996 to 2012. We also include two macroeconomic mimicking portfolios to capture the premiums of industrial production growth and inflation innovation, accommodating the economic regime shifts. Based on the information coefficients, we find the six-month momentum and the fractal measure as momentum factors; the enterprise yield (gross profit/TEV) and the book to market ratio as valuation factors; the gross profit to total assets, the return on capital, and the scaled total accruals as quality factors. We further construct active portfolios using the augmented Black Litterman (ABL) factor model to avoid the factor alignment problem, with the factor views predicted using Markov Switching VAR, MIDAS, and Bayesian Model Averaging. The out-of-sample performance of our portfolios can produce information ratios of 0.7 – 0.8 over the composite indices, and information ratios of 0.42 – 0.48 over the style indices, with the annualized alphas of 10 – 11%. Even when we put the constrained tracking error of 1% over the benchmark, our portfolios still produce information ratios of 0.9 – 1.2 before transaction costs, and 0.6 – 0.8 after transaction costs. We provide intuitive explanations for each premium changing over time, and suggest the promising strategy for Islamic equity investors to outperform the market.

Suggested Citation

  • Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla & Masih, A. Mansur M., 2014. "Combining Momentum, Value, and Quality for the Islamic Equity Portfolio: Multi-style Rotation Strategies using Augmented Black Litterman Factor Model," MPRA Paper 56965, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:56965
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    Cited by:

    1. El Mehdi, Imen Khanchel & Mghaieth, Asma, 2017. "Volatility spillover and hedging strategies between Islamic and conventional stocks in the presence of asymmetry and long memory," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 595-611.
    2. 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.
    3. Ibrahim, Mansor H., 2015. "Issues in Islamic banking and finance: Islamic banks, Shari’ah-compliant investment and sukuk," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 185-191.
    4. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla Ismath & Masih, A. Mansur. M., 2015. "Developing trading strategies based on fractal finance: An application of MF-DFA in the context of Islamic equities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 223-235.
    5. repec:eee:ememar:v:34:y:2018:i:c:p:143-161 is not listed on IDEAS
    6. Makni, Rania & Benouda, Olfa & Delhoumi, Ezzedine, 2016. "International evidence on Islamic equity fund characteristics and performance persistence," Review of Financial Economics, Elsevier, vol. 31(C), pages 75-82.
    7. Li, Bob & Ee, Mong Shan & Rashid, Mamunur, 2016. "Is momentum trading profitable from Shari'ah compliant stocks?," Review of Financial Economics, Elsevier, vol. 31(C), pages 56-63.
    8. repec:taf:oaefxx:v:5:y:2017:i:1:p:1363355 is not listed on IDEAS

    More about this item

    Keywords

    Islamic equity; portfolio strategy; multi-style rotation; Black Litterman factor model; forecast;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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