Exploring the Evolution of Robust Portfolio Optimization: A Scientometric Analysis

Iranian Journal of Accounting, Auditing and Finance

دوره 8، شماره 3 - شماره پیاپی 28، آبان 2024، صفحه 75-92   

نوع مقاله: Review article

شناسه دیجیتال (DOI): 10.22067/ijaaf.2024.44518.1402

نویسندگان

Amirhossein Eskorouchi¹؛ Hossein Ghanbari¹؛ Emran Mohammadi^{* 2}

¹School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

²Department of Industrial and Systems Engineering, Mississippi State University, Mississippi State 39762, USA

چکیده

In the wake of recent turbulent events in the global economy, the need for robust methods to navigate uncertainties in financial markets has become increasingly apparent. Robust portfolio optimization (RPO) offers a solution by devising investment strategies that perform well even under adverse scenarios of uncertain inputs such as returns and covariances. This paper conducts a systematic review of recent developments and extensions in the field of RPO. Leveraging bibliometric analysis and visual mapping techniques, we scrutinize 1085 articles published between 2000 and 2023. Our analysis traces the evolution and trends within RPO, examining the interconnectedness among articles, authors, sources, countries, and keywords. The insights gleaned from our study can guide future research endeavors in this domain and aid practitioners in making more informed investment decisions.

کلیدواژه‌ها

Bibliometric Analysis؛ Financial Markets؛ Robust Portfolio Optimization؛ Uncertainty؛ Scientometric Analysis

مراجع

1. Aria, M., and Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science
mapping analysis. Journal of Informetrics, 11(4), pp. 959–975. https://doi.org/10.1016/j.joi.2017.08.007
2. Arreola Hernandez, J., Hammoudeh, S., Nguyen, D. K., Al Janabi, M. A. M., and Reboredo, J. C. (2017). Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach. Applied Economics, 49(25), pp. 2409–2427. https://doi.org/10.1080/00036846.2016.1240346
3. Ben-Tal, A., and Nemirovski, A. (1999). Robust solutions of uncertain linear programs. Operations Research Letters, 25(1), pp. 1–13. https://doi.org/10.1016/S0167-6377(99)00016-4
4. Bertsimas, D., and Sim, M. (2003). Robust discrete Optimization and network flows. Mathematical Programming, 98(1–3), pp. 49–71. https://doi.org/10.1007/s10107-003-0396-4
5. Best, M. J., and Grauer, R. R. (1991). On the Sensitivity of Mean-Variance-Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results. The Review of Financial Studies, 4(2), pp. 315–342. https://doi.org/10.1093/RFS/4.2.315
6. Bernardo, A. E., and Ledoit, O. (2000). Gain, loss, and asset pricing. Journal of Political Economy, 108(1), pp. 144-172. https://doi.org/10.1086/262114
7. Broadus, R. N. (1987). Toward a definition of “bibliometrics.” Scientometrics, 12(5–6), pp. 373–379. https://doi.org/10.1007/BF02016680
8. Buehler, H., Gonon, L., Teichmann, J., and Wood, B. (2019). Deep hedging. Quantitative Finance, 19(8), pp. 1271-1291. https://doi.org/10.1080/14697688.2019.1571683
9. Catania, L., and Luati, A. (2021). Quasi Maximum Likelihood Estimation of Value at Risk and Econometrics and Statistics. https://doi.org/10.1016/j.ecosta.2021.08.003
10. Dauod, H., Serhan, D., Wang, H., Khader, N., Won Yoon, S., & Srihari, K. (2019). Robust receding horizon control strategy for replenishment planning of pharmacy robotic dispensing systems. Robotics and Computer-Integrated Manufacturing, 59(10), pp. 177–188. https://doi.org/10.1016/j.rcim.2019.04.001
11. DeMiguel, V., Garlappi, L., and Uppal, R. (2009). Optimal versus naive diversification: How inefficient is the 1/N portfolio strategy?. The Review of Financial Studies, 22(5), pp. 1915-1953. https://doi.org/10.1093/rfs/hhm075
12. Dzikowski, P. (2018). A bibliometric analysis of born global firms. Journal of Business Research, 85(24), pp 281–294. https://doi.org/10.1016/j.jbusres.2017.12.054
13. Eskorouchi, A., Mohammadi, E., and Sajadi, S. J. (2022). Robust Portfolio Optimization based on Evidence Theory.
14. Fama, E. F., & French, K. R. (1992). The cross‐section of expected stock returns. the Journal of Finance, 47(2), pp. 427-465. https://doi.org/10.1111/j.1540-6261.1992.tb04398.x.
15. Fishburn, C, P. (1977). Mean-Risk Analysis with Risk Associated with Below-Target Returns. American Economic Review, 67(2), pp. 116–126. https://ideas.repec.org/a/aea/aecrev/v67y1977i2p116-26.html
16. Fooeik, A. M. L., Ghanbari, H., Bagheriyan, M., and 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), pp. 105–112. https://doi.org/10.5267/j.jfs.2022.9.010
17. Ghahtarani, A., Saif, A., and Ghasemi, A. (2022). Robust portfolio selection problems: a comprehensive review. Operational Research, 22(4), pp. 3203-3264. https://doi.org/10.1007/s12351-022-00690-5
18. Ghanbari, H., Fooeik, A. M. L., Eskorouchi, A., and Mohammadi, E. (2022). Investigating the effect of US dollar, gold and oil prices on the stock market. Journal of Future Sustainability, 2(3), pp. 97–104. https://doi.org/10.5267/j.jfs.2022.9.009
19. Ghanbari, H., Safari, M., Ghousi, R., Mohammadi, E., and Nakharutai, N. (2023). Bibliometric analysis of risk measures for portfolio optimization. Accounting, 9(2), pp. 95-108. https://doi.org/10.5267/j.ac.2022.12.003
20. Goldfarb, D., and Iyengar, G. (2003). Robust portfolio selection problems. Mathematics of operations research, 28(1), pp. 1-38. https://doi.org/10.1287/moor.28.1.1.14260
21. Hirsch, J. E. (2010). An index to quantify an individual’s scientific research output that takes into account the effect of multiple coauthorship. Scientometrics, 85(3), pp. 741–754. https://doi.org/10.1007/s11192-010-0193-9
22. Jobson, J. D., and Korkie, R. M. (1981). Putting Markowitz theory to work. The Journal of Portfolio Management, 7(4), pp. 70–74. https://doi.org/10.3905/JPM.1981.408816
23. Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk. In Journal of Chemical Information and Modeling 53 (9) pp. 1-602. https://thuvienso.hoasen.edu.vn/handle/123456789/10569
24. Kalayci, C. B., Ertenlice, O., and Akbay, M. A. (2019). A comprehensive review of deterministic models and applications for mean-variance portfolio optimization. Expert Systems with Applications, 125(26), pp. 345–368. https://doi.org/10.1016/j.eswa.2019.02.011
25. Kilani, M. Al, and Kobziev, V. (2016). An Overview of Research Methodology in Information System (IS). OALib, 03(11), pp. 1–9. https://doi.org/10.4236/oalib.1103126
26. Konno, H., and Yamazaki, H. (1991). Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market. Management Science, 37(5), pp. 519–531. https://doi.org/10.1287/mnsc.37.5.519
27. Ledoit, O., and Wolf, M. (2003). Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. Journal of Empirical Finance, 10(5), pp. 603-621. https://doi.org/10.1016/S0927-5398(03)00007-0
28. Lu, Y., Young, S. N., Wang, H., and Wijewardane, N. (2022). Robust Plant Segmentation of Color Images Based on Image Contrast Optimization. Computers and Electronics in Agriculture, 193 (41), pp. 711-723. https://doi.org/10.1007/s10479-017-2466-7.
29. Lutgens, F., Sturm, J., and Kolen, A. (2006). Robust one-period option hedging. Operations Research, 54(6), pp. 1051-1062. https://doi.org/10.1287/opre.1060.0352
30. Masmoudi, M., and Abdelaziz, F. Ben. (2018). Portfolio selection problem: a review of deterministic and stochastic multiple objective programming models. Annals of Operations Research, 267(1–2), 335–352. https://doi.org/10.1007/s10479-017-2466-7
31. Mensi, W., Hammoudeh, S., Rehman, M. U., Al-Maadid, A. A. S., and Kang, S. H. (2020). Dynamic risk spillovers and portfolio risk management between precious metals and global foreign exchange markets. The North American Journal of Economics and Finance, 51, pp. 101086. https://doi.org/10.1016/j.najef.2019.101086
32. Milhomem, D. A., and Dantas, M. J. P. (2020). Analysis of new approaches used in portfolio optimization: a systematic literature review. Production, 30(5), pp. 20190144. https://doi.org/10.1590/0103-6513.20190144
33. Moral-Munoz, J. A., Arroyo-Morales, M., Herrera-Viedma, E., and Cobo, M. J. (2018). An Overview of Thematic Evolution of Physical Therapy Research Area From 1951 to 2013. Frontiers in Research Metrics and Analytics, 3(13), pp. 1–11. https://doi.org/10.3389/frma.2018.00013
34. Motamedi, N. (2023). Bibliometric Analysis and Topic Modeling of Information Systems in Maternal Health Publications. International Journal of Information Science and Management, 21(2), 85–101. https://doi.org/10.22034/ijism.2023.1977814.0/DOR
35. Ortobelli, S., Rachev, S. T., Stoyanov, S., Fabozzi, F. J., and Biglova, A. (2005). The proper use of risk measures in portfolio theory. International Journal of Theoretical and Applied Finance, 8(08), 1107-1133. https://doi.org/10.1142/S0219024905003402.
36. Amiri, M. R., Saberi, M. K., Ouchi, A., Mokhtari, H., and Barkhan, S. (2023). Publication performance and trends in altmetrics: A bibliometric analysis and visualization. International Journal of Information Science and Management (IJISM), 21(1), 97-117. https://doi.org/10.22034/ijism.2022.1977686.0
37. Rockafellar, R. T., and Uryasev, S. (2000). Optimization of conditional value-at-risk. Journal of Risk, 2, pp. 21-42. http://www.ise.u .edu/uryasev
38. Rockafellar, R. T., and Uryasev, S. (2002). Conditional value-at-risk for general loss distributions. Journal of Banking & Finance, 26(7), pp. 1443-1471. https://doi.org/10.1016/S0378-4266(02)00271-6
39. Rubinstein, M. (2002). Markowitz's" portfolio selection": A fifty-year retrospective. The Journal of Finance, 57(3), pp. 1041-1045. https://www.jstor.org/stable/2697771
40. Sadjadi, S. J., Gharakhani, M., and Safari, E. (2012). Robust optimization framework for cardinality constrained portfolio problem. Applied Soft Computing Journal, 12(1), pp. 91–99. https://doi.org/10.1016/j.asoc.2011.09.006
41. Schubert, C. (2009). Investigating the complex nature of the stressorcortisol association is possible: A response to Michaud et al. Stress, 12(5), pp. 464–465. https://doi.org/10.1080/10253890802603925
42. Sharpe, W. F. (1963). A Simplified Model for Portfolio Analysis. Management Science, 9(2), pp. 277–293. https://doi.org/10.1287/mnsc.9.2.277
43. Sharpe, W. F. (1966). Mutual fund performance. The Journal of Business, 39(1), pp. 119-138. https://www.jstor.org/stable/2351741
44. Sharpet, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance, 19(3), pp. 425-442. https://doi.org/10.1111/j.1540-6261.1964.tb02865.x
45. Skoruchi, A., and Mohammadi, E. (2022). Uncertain portfolio optimization based on Dempster-Shafer theory. Management Science Letters, 12(3), pp. 207–214. https://doi.org/10.5267/j.msl.2022.1.001
46. Soyster, A. L. (1973). Technical Note—Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming. Operations Research, 21(5), pp. 1154–1157. https://doi.org/10.1287/opre.21.5.1154
47. Wan, G., Student, P. D., and Dawod, A. Y. (2023). A Bibliometric and Visual Analysis in the Field of Environment, Social and Governance (ESG) Between 2004 and 2021 Nopasit Chakpitak. International Journal of Information Science and Management, 21(2), pp. 103–125. https://doi.org/10.22034/ijism.2023.1977765.0/DOR
48. Xiang, J. (2014). Research on Teaching Methods for Communication Engineering Students in Colleges. Open Journal of Social Sciences, 02(05), pp. 9–12. https://doi.org/10.4236/jss.2014.25003
49. Xidonas, P., Steuer, R., and Hassapis, C. (2020). Robust portfolio optimization: a categorized bibliographic review. Annals of Operations Research, 292(1), pp. 533-552. https://doi.org/10.1007/s10479-020-03630-8
50. Zabavnik, D., and Verbič, M. (2021). Relationship between the financial and the real economy:
A bibliometric analysis. International Review of Economics and Finance, 75(4), pp. 55–75. https://doi.org/10.1016/j.iref.2021.04.014
51. Zhang, Y., Li, X., and Guo, S. (2018). Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature. Fuzzy Optimization and Decision Making, 17, pp.125-158. https://doi.org/10.1007/s10700-017-9266-z