How to cite this paper
Khosravi, A., Sadjadi, S & Ghanbari, H. (2024). A bibliometric analysis and visualization of the scientific publications on multi-period portfolio optimization: From the current status to future directions.Accounting, 10(3), 107-120.
Refrences
Alhnaity, B., & Abbod, M. (2020). A new hybrid financial time series prediction model. Engineering Applications of Artificial Intelligence, 95, 103873. https://doi.org/10.1016/J.ENGAPPAI.2020.103873
Almahdi, S., & Yang, S. Y. (2017). An adaptive portfolio trading system: A risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown. Expert Systems with Applications, 87, 267–279. https://doi.org/10.1016/J.ESWA.2017.06.023
Eichhorn, A., & Römisch, W. (2006). Polyhedral Risk Measures in Stochastic Programming. Https://Doi.Org/10.1137/040605217, 16(1), 69–95. https://doi.org/10.1137/040605217
Ejaz, H., Zeeshan, H. M., Ahmad, F., Bukhari, S. N. A., Anwar, N., Alanazi, A., Sadiq, A., Junaid, K., Atif, M., Abosalif, K. O. A., Iqbal, A., Hamza, M. A., & Younas, S. (2022). Bibliometric Analysis of Publications on the Omicron Variant from 2020 to 2022 in the Scopus Database Using R and VOSviewer. International Journal of Environmental Research and Public Health 2022, Vol. 19, Page 12407, 19(19), 12407. https://doi.org/10.3390/IJERPH191912407
Eskorouchi, A., Ghanbari, H., & Mohammadi, E. (2023). A Scientometric Analysis of Robust Portfolio Optimization. Iranian Journal of Accounting, Auditing and Finance. https://doi.org/10.22067/IJAAF.2023.84137.1402
Fishburn, P. C., Fishburn, & C, P. (1977). Mean-Risk Analysis with Risk Associated with Below-Target Returns. American Economic Review, 67(2), 116–126. https://EconPapers.repec.org/RePEc:aea:aecrev:v:67:y:1977:i:2:p:116-26
Fontanills, G., & Gentile, T. (2001). The stock market course. 442.
Fooeik, A. M. L., Ghanbari, H., Bagheriyan, M., & Mohammadi, E. (2022). Analyzing the effects of global oil, gold and palladium markets: Evidence from the Nasdaq composite index. Journal of Future Sustainability, 2(3), 105–112. https://doi.org/10.5267/J.JFS.2022.9.010
Ghanbari, H., Fooeik, A. M. L., Eskorouchi, A., & Mohammadi, E. (2022). Investigating the effect of US dollar, gold and oil prices on the stock market. Journal of Future Sustainability, 2(3), 97–104. https://doi.org/10.5267/J.JFS.2022.9.009
Ghanbari, H., Safari, M., Ghousi, R., Mohammadi, E., & Nakharutai, N. (2023). Bibliometric analysis of risk measures for portfolio optimization. Accounting, 9(2), 95–108. https://doi.org/10.5267/J.AC.2022.12.003
Ghanbari, H., Shabani, M., & Mohammadi, E. (2023). Portfolio Optimization with Conditional Drawdown at Risk for the Automotive Industry. Automotive Science and Engineering, 13(4), 4236–4242. https://doi.org/10.22068/ASE.2023.647
Hoseinzade, E., & Haratizadeh, S. (2019). CNNpred: CNN-based stock market prediction using a diverse set of variables. Expert Systems with Applications, 129, 273–285. https://doi.org/10.1016/J.ESWA.2019.03.029
Javadi, R., Ghanbari, H., & Seiti, H. (2025). A bibliometric analysis on supply chain disruptions: Current status, development, and future directions. Journal of Future Sustainability, 107–126. https://doi.org/10.5267/J.JFS.2025.4.002
Jezeie, F. V., Sadjadi, S. J., & Makui, A. (2022). Constrained portfolio optimization with discrete variables: An algorithmic method based on dynamic programming. PLoS ONE, 17(7 July). https://doi.org/10.1371/JOURNAL.PONE.0271811
Khan, A. Z., & Mehlawat, M. K. (2022). Dynamic portfolio optimization using technical analysis-based clustering. International Journal of Intelligent Systems, 37(10), 6978–7057. https://doi.org/10.1002/INT.22870
Khan, K. I., Naqvi, S. M. W. A., Ghafoor, M. M., & Akash, R. S. I. (2020). Sustainable Portfolio Optimization with Higher-Order Moments of Risk. Sustainability 2020, Vol. 12, Page 2006, 12(5), 2006. https://doi.org/10.3390/SU12052006
Konno, H., & Yamazaki, H. (1991). Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market. Https://Doi.Org/10.1287/Mnsc.37.5.519, 37(5), 519–531. https://doi.org/10.1287/MNSC.37.5.519
Krzemienowski, A., & Ogryczak, W. (2005). On extending the LP computable risk measures to account downside risk. Computational Optimization and Applications, 32(1–2), 133–160. https://doi.org/10.1007/S10589-005-2057-4
Kumar, R. R., Stauvermann, P. J., & Samitas, A. (2022). An Application of Portfolio Mean-Variance and Semi-Variance Optimization Techniques: A Case of Fiji. Journal of Risk and Financial Management 2022, Vol. 15, Page 190, 15(5), 190. https://doi.org/10.3390/JRFM15050190
Larni-Fooeik, A., Ghanbari, H., Sadjadi, S. J., & Mohammadi, E. (2024). Behavioral Finance biases: A Comprehensive Review on regret approach studies in portfolio optimization. International Journal of Industrial Engineering & Production Research, 35(1), 1–23. https://doi.org/10.22068/IJIEPR.35.1.1909
Larni-Fooeik, A. M., Ghanbari, H., Shabani, M., & Mohammadi, E. (2024). Bi-Objective Portfolio Optimization with Mean-CVaR Model: An Ideal and Anti-Ideal Compromise Programming Approach. Studies in Systems, Decision and Control, 518, 69–79. https://doi.org/10.1007/978-3-031-51719-8_5
Leković, M. (2018). Investment diversification as a strategy for reducing investment risk. Ekonomski Horizonti, 20(2), 173–187. https://doi.org/10.5937/EKONHOR1802173L
Liu, Y. J., Zhang, W. G., & Zhang, P. (2013). A multi-period portfolio selection optimization model by using interval analysis. Economic Modelling, 33, 113–119. https://doi.org/10.1016/j.econmod.2013.03.006
Lwin, K. T., Qu, R., & MacCarthy, B. L. (2017). Mean-VaR portfolio optimization: A nonparametric approach. European Journal of Operational Research, 260(2), 751–766. https://doi.org/10.1016/j.ejor.2017.01.005
Manganelli, S., & Engle, R. F. (2001). Value at Risk Models in Finance. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.356220
Mansini, R., Ogryczak, W., & Speranza, M. G. (2014). Twenty years of linear programming based portfolio optimization. European Journal of Operational Research, 234(2), 518–535. https://doi.org/10.1016/j.ejor.2013.08.035
Marín-Rodríguez, N. J., González-Ruiz, J. D., & Botero Botero, S. (2022). Dynamic Co-Movements among Oil Prices and Financial Assets: A Scientometric Analysis. Sustainability 2022, Vol. 14, Page 12796, 14(19), 12796. https://doi.org/10.3390/SU141912796
Markowitz, H. (1952). The Utility of Wealth. Https://Doi.Org/10.1086/257177, 43–50. https://doi.org/10.1086/257177
Michalowski, W., & Ogryczak, W. (2001). Extending the MAD portfolio optimization model to incorporate downside risk aversion. Naval Research Logistics (NRL), 48(3), 185–200. https://doi.org/10.1002/NAV.1
Ngoc, L. T. B. (2013). Behavior Pattern of Individual Investors in Stock Market. International Journal of Business and Management, 9(1). https://doi.org/10.5539/IJBM.V9N1P1
Ogryczak, W., Przyłuski, M., & Śliwiński, T. (2017). Efficient optimization of the reward-risk ratio with polyhedral risk measures. Mathematical Methods of Operations Research, 86(3), 625–653. https://doi.org/10.1007/S00186-017-0613-1/TABLES/1
Rockafellar, R. T., & Uryasev, S. (2000). Optimization of conditional value-at risk. Journal of Risk, 2(3), 21–41. https://doi.org/10.21314/JOR.2000.038
Rockafellar, R. T., & Uryasev, S. (2002). Conditional value-at-risk for general loss distributions. Journal of Banking & Finance, 26(7), 1443–1471. https://doi.org/10.1016/S0378-4266(02)00271-6
Steinbach, M. (1999). Markowitz Revisited: Single-Period and Multi-Period Mean-Variance Models.
Surtee, T. G. H., & Alagidede, I. P. (2023). A novel approach to using modern portfolio theory. Borsa Istanbul Review, 23(3), 527–540. https://doi.org/10.1016/J.BIR.2022.12.005
Tsinaslanidis, P. E. (2018). Subsequence dynamic time warping for charting: Bullish and bearish class predictions for NYSE stocks. Expert Systems with Applications, 94, 193–204. https://doi.org/10.1016/J.ESWA.2017.10.055
Yeo, L. L. X., Cao, Q., & Quek, C. (2023). Dynamic portfolio rebalancing with lag-optimised trading indicators using SeroFAM and genetic algorithms. Expert Systems with Applications, 216. https://doi.org/10.1016/J.ESWA.2022.119440
Yitzhaki, S., Yitzhaki, & Shlomo. (1982). Stochastic Dominance, Mean Variance, and Gini’s Mean Difference. American Economic Review, 72(1), 178–185. https://EconPapers.repec.org/RePEc:aea:aecrev:v:72:y:1982:i:1:p:178-85
Young, M. R. (1998). A Minimax Portfolio Selection Rule with Linear Programming Solution. Https://Doi.Org/10.1287/Mnsc.44.5.673, 44(5), 673–683. https://doi.org/10.1287/MNSC.44.5.673
Almahdi, S., & Yang, S. Y. (2017). An adaptive portfolio trading system: A risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown. Expert Systems with Applications, 87, 267–279. https://doi.org/10.1016/J.ESWA.2017.06.023
Eichhorn, A., & Römisch, W. (2006). Polyhedral Risk Measures in Stochastic Programming. Https://Doi.Org/10.1137/040605217, 16(1), 69–95. https://doi.org/10.1137/040605217
Ejaz, H., Zeeshan, H. M., Ahmad, F., Bukhari, S. N. A., Anwar, N., Alanazi, A., Sadiq, A., Junaid, K., Atif, M., Abosalif, K. O. A., Iqbal, A., Hamza, M. A., & Younas, S. (2022). Bibliometric Analysis of Publications on the Omicron Variant from 2020 to 2022 in the Scopus Database Using R and VOSviewer. International Journal of Environmental Research and Public Health 2022, Vol. 19, Page 12407, 19(19), 12407. https://doi.org/10.3390/IJERPH191912407
Eskorouchi, A., Ghanbari, H., & Mohammadi, E. (2023). A Scientometric Analysis of Robust Portfolio Optimization. Iranian Journal of Accounting, Auditing and Finance. https://doi.org/10.22067/IJAAF.2023.84137.1402
Fishburn, P. C., Fishburn, & C, P. (1977). Mean-Risk Analysis with Risk Associated with Below-Target Returns. American Economic Review, 67(2), 116–126. https://EconPapers.repec.org/RePEc:aea:aecrev:v:67:y:1977:i:2:p:116-26
Fontanills, G., & Gentile, T. (2001). The stock market course. 442.
Fooeik, A. M. L., Ghanbari, H., Bagheriyan, M., & Mohammadi, E. (2022). Analyzing the effects of global oil, gold and palladium markets: Evidence from the Nasdaq composite index. Journal of Future Sustainability, 2(3), 105–112. https://doi.org/10.5267/J.JFS.2022.9.010
Ghanbari, H., Fooeik, A. M. L., Eskorouchi, A., & Mohammadi, E. (2022). Investigating the effect of US dollar, gold and oil prices on the stock market. Journal of Future Sustainability, 2(3), 97–104. https://doi.org/10.5267/J.JFS.2022.9.009
Ghanbari, H., Safari, M., Ghousi, R., Mohammadi, E., & Nakharutai, N. (2023). Bibliometric analysis of risk measures for portfolio optimization. Accounting, 9(2), 95–108. https://doi.org/10.5267/J.AC.2022.12.003
Ghanbari, H., Shabani, M., & Mohammadi, E. (2023). Portfolio Optimization with Conditional Drawdown at Risk for the Automotive Industry. Automotive Science and Engineering, 13(4), 4236–4242. https://doi.org/10.22068/ASE.2023.647
Hoseinzade, E., & Haratizadeh, S. (2019). CNNpred: CNN-based stock market prediction using a diverse set of variables. Expert Systems with Applications, 129, 273–285. https://doi.org/10.1016/J.ESWA.2019.03.029
Javadi, R., Ghanbari, H., & Seiti, H. (2025). A bibliometric analysis on supply chain disruptions: Current status, development, and future directions. Journal of Future Sustainability, 107–126. https://doi.org/10.5267/J.JFS.2025.4.002
Jezeie, F. V., Sadjadi, S. J., & Makui, A. (2022). Constrained portfolio optimization with discrete variables: An algorithmic method based on dynamic programming. PLoS ONE, 17(7 July). https://doi.org/10.1371/JOURNAL.PONE.0271811
Khan, A. Z., & Mehlawat, M. K. (2022). Dynamic portfolio optimization using technical analysis-based clustering. International Journal of Intelligent Systems, 37(10), 6978–7057. https://doi.org/10.1002/INT.22870
Khan, K. I., Naqvi, S. M. W. A., Ghafoor, M. M., & Akash, R. S. I. (2020). Sustainable Portfolio Optimization with Higher-Order Moments of Risk. Sustainability 2020, Vol. 12, Page 2006, 12(5), 2006. https://doi.org/10.3390/SU12052006
Konno, H., & Yamazaki, H. (1991). Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market. Https://Doi.Org/10.1287/Mnsc.37.5.519, 37(5), 519–531. https://doi.org/10.1287/MNSC.37.5.519
Krzemienowski, A., & Ogryczak, W. (2005). On extending the LP computable risk measures to account downside risk. Computational Optimization and Applications, 32(1–2), 133–160. https://doi.org/10.1007/S10589-005-2057-4
Kumar, R. R., Stauvermann, P. J., & Samitas, A. (2022). An Application of Portfolio Mean-Variance and Semi-Variance Optimization Techniques: A Case of Fiji. Journal of Risk and Financial Management 2022, Vol. 15, Page 190, 15(5), 190. https://doi.org/10.3390/JRFM15050190
Larni-Fooeik, A., Ghanbari, H., Sadjadi, S. J., & Mohammadi, E. (2024). Behavioral Finance biases: A Comprehensive Review on regret approach studies in portfolio optimization. International Journal of Industrial Engineering & Production Research, 35(1), 1–23. https://doi.org/10.22068/IJIEPR.35.1.1909
Larni-Fooeik, A. M., Ghanbari, H., Shabani, M., & Mohammadi, E. (2024). Bi-Objective Portfolio Optimization with Mean-CVaR Model: An Ideal and Anti-Ideal Compromise Programming Approach. Studies in Systems, Decision and Control, 518, 69–79. https://doi.org/10.1007/978-3-031-51719-8_5
Leković, M. (2018). Investment diversification as a strategy for reducing investment risk. Ekonomski Horizonti, 20(2), 173–187. https://doi.org/10.5937/EKONHOR1802173L
Liu, Y. J., Zhang, W. G., & Zhang, P. (2013). A multi-period portfolio selection optimization model by using interval analysis. Economic Modelling, 33, 113–119. https://doi.org/10.1016/j.econmod.2013.03.006
Lwin, K. T., Qu, R., & MacCarthy, B. L. (2017). Mean-VaR portfolio optimization: A nonparametric approach. European Journal of Operational Research, 260(2), 751–766. https://doi.org/10.1016/j.ejor.2017.01.005
Manganelli, S., & Engle, R. F. (2001). Value at Risk Models in Finance. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.356220
Mansini, R., Ogryczak, W., & Speranza, M. G. (2014). Twenty years of linear programming based portfolio optimization. European Journal of Operational Research, 234(2), 518–535. https://doi.org/10.1016/j.ejor.2013.08.035
Marín-Rodríguez, N. J., González-Ruiz, J. D., & Botero Botero, S. (2022). Dynamic Co-Movements among Oil Prices and Financial Assets: A Scientometric Analysis. Sustainability 2022, Vol. 14, Page 12796, 14(19), 12796. https://doi.org/10.3390/SU141912796
Markowitz, H. (1952). The Utility of Wealth. Https://Doi.Org/10.1086/257177, 43–50. https://doi.org/10.1086/257177
Michalowski, W., & Ogryczak, W. (2001). Extending the MAD portfolio optimization model to incorporate downside risk aversion. Naval Research Logistics (NRL), 48(3), 185–200. https://doi.org/10.1002/NAV.1
Ngoc, L. T. B. (2013). Behavior Pattern of Individual Investors in Stock Market. International Journal of Business and Management, 9(1). https://doi.org/10.5539/IJBM.V9N1P1
Ogryczak, W., Przyłuski, M., & Śliwiński, T. (2017). Efficient optimization of the reward-risk ratio with polyhedral risk measures. Mathematical Methods of Operations Research, 86(3), 625–653. https://doi.org/10.1007/S00186-017-0613-1/TABLES/1
Rockafellar, R. T., & Uryasev, S. (2000). Optimization of conditional value-at risk. Journal of Risk, 2(3), 21–41. https://doi.org/10.21314/JOR.2000.038
Rockafellar, R. T., & Uryasev, S. (2002). Conditional value-at-risk for general loss distributions. Journal of Banking & Finance, 26(7), 1443–1471. https://doi.org/10.1016/S0378-4266(02)00271-6
Steinbach, M. (1999). Markowitz Revisited: Single-Period and Multi-Period Mean-Variance Models.
Surtee, T. G. H., & Alagidede, I. P. (2023). A novel approach to using modern portfolio theory. Borsa Istanbul Review, 23(3), 527–540. https://doi.org/10.1016/J.BIR.2022.12.005
Tsinaslanidis, P. E. (2018). Subsequence dynamic time warping for charting: Bullish and bearish class predictions for NYSE stocks. Expert Systems with Applications, 94, 193–204. https://doi.org/10.1016/J.ESWA.2017.10.055
Yeo, L. L. X., Cao, Q., & Quek, C. (2023). Dynamic portfolio rebalancing with lag-optimised trading indicators using SeroFAM and genetic algorithms. Expert Systems with Applications, 216. https://doi.org/10.1016/J.ESWA.2022.119440
Yitzhaki, S., Yitzhaki, & Shlomo. (1982). Stochastic Dominance, Mean Variance, and Gini’s Mean Difference. American Economic Review, 72(1), 178–185. https://EconPapers.repec.org/RePEc:aea:aecrev:v:72:y:1982:i:1:p:178-85
Young, M. R. (1998). A Minimax Portfolio Selection Rule with Linear Programming Solution. Https://Doi.Org/10.1287/Mnsc.44.5.673, 44(5), 673–683. https://doi.org/10.1287/MNSC.44.5.673