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Combining equilibrium, resampling, and analyst’s views in portfolio optimization

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  • Barros Fernandes, José Luiz
  • Haas Ornelas, José Renato
  • Martínez Cusicanqui, Oscar Augusto

Abstract

This paper proposes the use of a portfolio optimization methodology which combines features of equilibrium models and investor’s views as in Black and Litterman (1992), and also deals with estimation risk as in Michaud (1998). In this way, our combined methodology is able to meet the needs of practitioners for stable and diversified portfolio allocations, while it is theoretically grounded on an equilibrium framework. We empirically test the methodology using a comprehensive sample of developed countries fixed income and equity indices, as well as sub-samples stratified by geographical region, time period, asset class and risk level. In general, our proposed combined methodology generates very competitive portfolios when compared to other methodologies, considering three evaluation dimensions: financial efficiency, diversification, and allocation stability. By generating financially efficient, stable, and diversified portfolio allocations, our methodology is suitable for long-term investors such as Central Banks and Sovereign Wealth Funds.

Suggested Citation

  • Barros Fernandes, José Luiz & Haas Ornelas, José Renato & Martínez Cusicanqui, Oscar Augusto, 2012. "Combining equilibrium, resampling, and analyst’s views in portfolio optimization," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1354-1361.
    • Handle: RePEc:eee:jbfina:v:36:y:2012:i:5:p:1354-1361
    DOI: 10.1016/j.jbankfin.2011.11.023
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Farinelli, Simone & Ferreira, Manuel & Rossello, Damiano & Thoeny, Markus & Tibiletti, Luisa, 2008. "Beyond Sharpe ratio: Optimal asset allocation using different performance ratios," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2057-2063, October.
    3. Fajardo, José & Farias, Aquiles, 2009. "Multivariate affine generalized hyperbolic distributions: An empirical investigation," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 174-184, September.
    4. Michael Wolf, 2006. "Resampling vs. Shrinkage for Benchmarked Managers," IEW - Working Papers 263, Institute for Empirical Research in Economics - University of Zurich.
    5. Jorion, Philippe, 1991. "Bayesian and CAPM estimators of the means: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 15(3), pages 717-727, June.
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    Citations

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    Cited by:

    1. I-Chen Lu & Kai-Hong Tee & Baibing Li, 2019. "Asset allocation with multiple analysts’ views: a robust approach," Journal of Asset Management, Palgrave Macmillan, vol. 20(3), pages 215-228, May.
    2. Harris, Richard D.F. & Stoja, Evarist & Tan, Linzhi, 2017. "The dynamic Black–Litterman approach to asset allocation," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1085-1096.
    3. Barua, Ronil & Sharma, Anil K., 2022. "Dynamic Black Litterman portfolios with views derived via CNN-BiLSTM predictions," Finance Research Letters, Elsevier, vol. 49(C).
    4. Zhang, Zhichao & Chau, Frankie & Xie, Li, 2012. "Strategic Asset Allocation for Central Bank’s Management of Foreign Reserves: A new approach," MPRA Paper 43654, University Library of Munich, Germany.
    5. Barua, Ronil & Sharma, Anil K., 2023. "Using fear, greed and machine learning for optimizing global portfolios: A Black-Litterman approach," Finance Research Letters, Elsevier, vol. 58(PC).
    6. Erdinc Akyildirim & Matteo Gambara & Josef Teichmann & Syang Zhou, 2023. "Randomized Signature Methods in Optimal Portfolio Selection," Papers 2312.16448, arXiv.org.

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    More about this item

    Keywords

    Portfolio optimization; Estimation risk; Equilibrium;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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