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Research Article

Robust portfolio optimization: a stochastic evaluation of worst-case scenarios

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Article: 2165525 | Received 13 May 2022, Accepted 02 Jan 2023, Published online: 17 May 2023

References

  • Adam, L., & Branda, M. (2020). Risk-aversion in data envelopment analysis models with diversification. Omega, 102, 102338. https://doi.org/10.1016/j.omega.2020.102338
  • Ali, S., Zhang, J., Abbas, M., Draz, M. U., & Ahmad, F. (2019). Symmetric and asymmetric GARCH estimations and portfolio optimization: Evidence from G7 stock markets. SAGE Open, 9(2), 215824401985024. https://doi.org/10.1177/2158244019850243
  • Amin, G. R., & Hajjami, M. (2020). Improving DEA cross-efficiency optimization in portfolio selection. Expert Systems with Applications, 114280. https://doi.org/10.1016/j.eswa.2020.114280
  • Ashrafi, H., & Thiele, C. (2021). A study of robust portfolio optimization with European options using polyhedral uncertainty sets. Operations Research Perspectives, 8, 100178. https://doi.org/10.1016/j.orp.2021.100178
  • Atta Mills, E. F. E., & Anyomi, S. K. (2022). A hybrid two-stage robustness approach to portfolio construction under uncertainty. Journal of King Saud University - Computer and Information Sciences, 34(9), 7735–7750. https://doi.org/10.1016/j.jksuci.2022.06.016
  • Azadi, M., Jafarian, M., Saen, R. F., & Mirhedayatian, S. M. (2015). A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Computers & Operations Research, 54, 274–285. https://doi.org/10.1016/j.cor.2014.03.002
  • Azadi, M., & Saen, R. F. (2012). Developing a new chance-constrained DEA model for suppliers selection in the presence of undesirable outputs. International Journal of Operational Research, 13(1), 44–66. https://doi.org/10.1504/IJOR.2012.044027
  • Azadi, M., Saen, R. F., & Tavana, M. (2012). Supplier selection using chance-constrained data envelopment analysis with non-discretionary factors and stochastic data. International Journal of Industrial and Systems Engineering, 10(2), 167–196. https://doi.org/10.1504/IJISE.2012.045179
  • Baltas, I., & Yannacopoulos, A. N. (2019). Portfolio management in a stochastic factor model under the existence of private information. IMA Journal of Management Mathematics, 30(1), 77–103. https://doi.org/10.1093/imaman/dpx012
  • Black, F., & Litterman, R. (1992). Global portfolio optimization. Financial Analysts Journal, 48(5), 28–43. https://doi.org/10.2469/faj.v48.n5.28
  • Bouaddi, M., & Moutanabbir, K. (2023). Rational distorted beliefs investor; which risk matters? Finance Research Letters, 51, 103431. https://doi.org/10.1016/j.frl.2022.103431
  • Brito, I. (2023). A portfolio stock selection model based on expected utility, entropy and variance. Expert Systems with Applications, 213, 118896. https://doi.org/10.1016/j.eswa.2022.118896
  • Chakrabarti, D. (2021). Parameter-free robust optimization for the maximum-sharpe portfolio problem. European Journal of Operational Research, 293(1), 388–399. https://doi.org/10.1016/j.ejor.2020.11.052
  • Charnes, A., & Cooper, W. W. (1959). Chance-constrained programming. Management Science, 6(1), 73–79.
  • Charnes, A., & Cooper, W. W. (1963). Deterministic equivalents for optimizing and satisficing under chance constraints. Operations Research, 11(1), 18–39. https://doi.org/10.1287/opre.11.1.18
  • Charnes, A., Cooper, W., Lewin, A., & Seiford, L. (1994). Data envelopment analysis: Theory, methodology, and application. Springer Science + Business Media, LLC. https://doi.org/10.1007/978-94-011-0637-5
  • Chen, C., Liu, D., Xian, L., Pan, L., Wang, L., Yang, M., & Quan, L. (2020). Best-case scenario robust portfolio for energy stock market. Energy, 213, 118664. https://doi.org/10.1016/j.energy.2020.118664
  • Choi, H. S., & Min, D. (2017). Efficiency of well-diversified portfolios: Evidence from data envelopment analysis. Omega (United Kingdom), 73, 104–113. https://doi.org/10.1016/j.omega.2016.12.008
  • Cook, W., & Zhu, J. (2014). Data envelopment analysis – A handbook on the modeling of internal structures and networks. Springer International Publishing.
  • Cooper, W. W., Huang, Z., & Li, S. X. (1996). Satisficing DEA models under chance constraints. Annals of Operations Research, 66(4), 279–295. https://doi.org/10.1007/BF02187302
  • Cooper, W. W., Seiford, L., & Tone, K. (2007). Data envelopment analysis: a comprehensive text with models, application, references and DEA-Solver Software. Springer International Publishing.
  • Economatica. (2022). Formulas for indicators. http://confluence.economatica.com/display/FE/Formulas+for+indicators
  • Edirisinghe, N. C. P., & Zhang, X. (2010). Input/output selection in DEA under expert information, with application to financial markets. European Journal of Operational Research, 207(3), 1669–1678. https://doi.org/10.1016/j.ejor.2010.06.027
  • Emrouznejad, A., & Tavana, M. (2014). Peformance measurement with fuzzy data envelopment analysis. Springer International Publishing.
  • Fabozzi, F. J., Huang, D., & Zhou, G. (2010). Robust portfolios: Contributions from operations research and finance. Annals of Operations Research, 176(1), 191–220. https://doi.org/10.1007/s10479-009-0515-6
  • Fabozzi, F. J., Kolm, P. N., Pachamanova, D. A., & Focardi, S. M. (2007). Robust portfolio optimization. The Journal of Portfolio Management, 33(3), 40–48. https://doi.org/10.3905/jpm.2007.684751
  • Ghahtarani, A., Saif, A., & Ghasemi, A. (2022). Robust portfolio selection problems: a comprehensive review. Operational Research, 22(4), 3203–3264. https://doi.org/10.1007/s12351-022-00690-5
  • Gonçalves, G., Wanke, P., & Tan, Y. (2022). A higher order portfolio optimization model incorporating information entropy. Intelligent Systems with Applications, 15, 200101. https://doi.org/10.1016/j.iswa.2022.200101
  • Gong, X., Yu, C., Min, L., & Ge, Z. (2021). Regret theory-based fuzzy multi-objective portfolio selection model involving DEA cross-efficiency and higher moments. Applied Soft Computing, 100, 106958. 106958. https://doi.org/10.1016/j.asoc.2020.106958
  • Homm, U., & Pigorsch, C. (2012). Beyond the Sharpe ratio: An application of the Aumann-Serrano index to performance measurement. Journal of Banking & Finance, 36(8), 2274–2284. https://doi.org/10.1016/j.jbankfin.2012.04.005
  • Jalota, H., Mandal, P. K., Thakur, M., & Mittal, G. (2023). A novel approach to incorporate investor’s preference in fuzzy multi-objective portfolio selection problem using credibility measure. Expert Systems with Applications, 212, 118583. https://doi.org/10.1016/j.eswa.2022.118583
  • Jin, J., Zhou, D., & Zhou, P. (2014). Measuring environmental performance with stochastic environmental DEA: The case of APEC economies. Economic Modelling, 38, 80–86. https://doi.org/10.1016/j.econmod.2013.12.017
  • Kim, J. H., Kim, W. C., & Fabozzi, F. J. (2014). Recent developments in robust portfolios with a worst-case approach. Journal of Optimization Theory and Applications, 161(1), 103–121. https://doi.org/10.1007/s10957-013-0329-1
  • Kim, J. H., Kim, W. C., & Fabozzi, F. J. (2018). Recent advancements in robust optimization for investment management. Annals of Operations Research, 266(1–2), 183–198. https://doi.org/10.1007/s10479-017-2573-5
  • Kim, W. C., Kim, J. H., Mulvey, J. M., & Fabozzi, F. J. (2015). Focusing on the worst state for robust investing. International Review of Financial Analysis, 39, 19–31. https://doi.org/10.1016/j.irfa.2015.02.001
  • Kourtis, A. (2016). The Sharpe ratio of estimated efficient portfolios. Finance Research Letters, 17, 72–78. https://doi.org/10.1016/j.frl.2016.01.009
  • Leung, P.-L., Ng, H.-Y., & Wong, W.-K. (2012). An improved estimation to make Markowitz’s portfolio optimization theory users friendly and estimation accurate with application on the US stock market investment. European Journal of Operational Research, 222(1), 85–95. https://doi.org/10.1016/j.ejor.2012.04.003
  • Lim, S., Oh, K. W., & Zhu, J. (2014). Use of DEA cross-efficiency evaluation in portfolio selection: An application to Korean stock market. European Journal of Operational Research, 236(1), 361–368. https://doi.org/10.1016/j.ejor.2013.12.002
  • López Prol, J., & Kim, K. (2022). Risk-return performance of optimized ESG equity portfolios in the NYSE. Finance Research Letters, 50, 103312. https://doi.org/10.1016/j.frl.2022.103312
  • Maciel, L. (2021). A new approach to portfolio management in the Brazilian equity market: Does assets efficiency level improve performance? The Quarterly Review of Economics and Finance, 81, 38–56. https://doi.org/10.1016/j.qref.2021.04.017
  • Markowitz, H. (1952). Portfolio selection*. The Journal of Finance, 7(1), 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
  • Markowitz, H. (2014). Mean–variance approximations to expected utility. European Journal of Operational Research, 234(2), 346–355. https://doi.org/10.1016/j.ejor.2012.08.023
  • Powers, J., & Mcmullen, P. (2002). No Title. Journal of Business and Management, 7(2), 31–42.
  • Rotela Junior, P., de Oliveira Pamplona, E., Rocha, L. C. S., de Mello Valerio, V. E., & Paiva, A. P. (2015). Stochastic portfolio optimization using efficiency evaluation. Management Decision, 53(8), 1698–1713. https://doi.org/10.1108/MD-11-2014-0644
  • Rotela Junior, P., Pamplona, E. O., & Salomon, F. R. (2014). Otimização de portfólios: análise de eficiência. Revista de Administração de Empresas, 54(4), 405–413. https://doi.org/10.1590/S0034-759020140406
  • Saen, R. F., & Azadi, M. (2011). A chance‐constrained data envelopment analysis approach for strategy selection. Journal of Modelling in Management, 6(2), 200–214. https://doi.org/10.1108/17465661111149584
  • Sehgal, R., & Mehra, A. (2020, January). Robust portfolio optimization with second order stochastic dominance constraints. Computers & Industrial Engineering, 144, 106396. https://doi.org/10.1016/j.cie.2020.106396
  • Sengupta, J. K. (1987). Data envelopment analysis for efficiency measurement in the stochastic case. Computers & Operations Research, 14(2), 117–129. https://doi.org/10.1016/0305-0548(87)90004-9
  • Sharpe, W. F. (1963). A simplified model for portfolio analysis. Management Science, 9(2), 277–293. https://doi.org/10.1287/mnsc.9.2.277
  • Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425–442. https://doi.org/10.1111/j.1540-6261.1964.tb02865.x
  • Shi, H. L., & Wang, Y. M. (2020). A merger and acquisition matching method that considers irrational behavior from a performance perspective. IEEE Access 8, 45726–45737. https://doi.org/10.1109/ACCESS.2020.2976608
  • Siriopoulos, C., & Tziogkidis, P. (2010). How do Greek banking institutions react after significant events?-A DEA approach. Omega, 38(5), 294–308. https://doi.org/10.1016/j.omega.2009.06.001
  • Smętek, K., Zawadzka, D., & Strzelecka, A. (2022). Examples of the use of Data Envelopment Analysis (DEA) to assess the financial effectiveness of insurance companies. Procedia Computer Science, 207, 3924–3930. https://doi.org/10.1016/j.procs.2022.09.454
  • Won, J.-H., & Kim, S.-J. (2020). Robust trade-off portfolio selection. Optimization and Engineering, 21(3), 867–904. https://doi.org/10.1007/s11081-020-09485-z
  • Xidonas, P., Mavrotas, G., Hassapis, C., & Zopounidis, C. (2017). Robust multiobjective portfolio optimization: A minimax regret approach. European Journal of Operational Research, 262(1), 299–305. https://doi.org/10.1016/j.ejor.2017.03.041
  • Xidonas, P., Steuer, R., & Hassapis, C. (2020). Robust portfolio optimization: A categorized bibliographic review. Annals of Operations Research, 292(1), 533–552. https://doi.org/10.1007/s10479-020-03630-8
  • Yu, J.-R., Chiou, W.-J P., Lee, W.-Y., & Chuang, T.-Y. (2019). Realized performance of robust portfolios: Worst-case Omega vs. CVaR-related models. Computers & Operations Research, 104, 239–255. https://doi.org/10.1016/j.cor.2018.12.004