Dynamic changes and multi-dimensional evolution of portfolio optimization

被引:2
|
作者
Zhou, Wei [1 ]
Zhu, Wenqiang [1 ]
Chen, Yan [1 ]
Chen, Jin [2 ]
机构
[1] Yunnan Univ Finance & Econ, Sch Finance, Kunming, Yunnan, Peoples R China
[2] Kunming Univ Sci & Technol, Fac Management & Econ, Kunming, Yunnan, Peoples R China
来源
关键词
Portfolio optimization; dynamic changes; multi-dimensional evolution; multi-disciplinary; heuristic algorithms; MEAN-ABSOLUTE DEVIATION; PROGRAMMING-MODEL; SELECTION MODEL; NAIVE DIVERSIFICATION; BIBLIOMETRIC ANALYSIS; STOCHASTIC-DOMINANCE; DECISION-MAKING; RISK; ALGORITHMS; PERFORMANCE;
D O I
10.1080/1331677X.2021.1968308
中图分类号
F [经济];
学科分类号
02 ;
摘要
Although there has been an increasing number of studies investigate portfolio optimization from different perspectives, few attempts could be found that focus on the development trend and hotspots of this research area. Therefore, it motivates us to comprehensively investigate the development of portfolio optimization research and give some deep insights into this knowledge domain. In this paper, some bibliometric methods are utilized to analyse the status quo and emerging trends of portfolio optimization research on various aspects such as authors, countries and journals. Besides, 'theories', 'models' and 'algorithms', especially heuristic algorithms are identified as the hotspots in the given periods. Furthermore, the evolutionary analysis tends to presents the dynamic changes of the cutting-edge concepts of this research area in the time dimension. It is found that more portfolio optimization studies were at an exploration stage from mean-variance analysis to consideration of multiple constraints. However, heuristic algorithms have become the driving force of portfolio optimization research in recent years. Multi-disciplinary analyses and applications are also the main trends of portfolio optimization research. By analysing the dynamic changes and multi-dimensional evolution in recent decades, we contribute to presenting some deep insights of the portfolio optimization research directly, which assists researchers especially beginners to comprehensively learn this research field.
引用
收藏
页码:1431 / 1456
页数:26
相关论文
共 50 条
  • [1] On the multi-dimensional portfolio optimization with stochastic volatility
    Kufakunesu, Rodwell
    [J]. QUAESTIONES MATHEMATICAE, 2018, 41 (01) : 27 - 40
  • [2] Multi-dimensional Particle Swarm Optimization for Dynamic Environments
    Kiranyaz, Serkan
    Pulkkinen, Jenni
    Gabbouj, Moncef
    [J]. IIT: 2008 INTERNATIONAL CONFERENCE ON INNOVATIONS IN INFORMATION TECHNOLOGY, 2008, : 51 - 55
  • [3] Multi-dimensional particle swarm optimization in dynamic environments
    Kiranyaz, Serkan
    Pulkkinen, Jenni
    Gabbouj, Moncef
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (03) : 2212 - 2223
  • [4] MULTI-DIMENSIONAL PARTICLE SWARM OPTIMIZATION FOR DYNAMIC CLUSTERING
    Kiranyaz, Serkan
    Ince, Turker
    Yildirim, Alper
    Gabbouj, Moncef
    [J]. EUROCON 2009: INTERNATIONAL IEEE CONFERENCE DEVOTED TO THE 150 ANNIVERSARY OF ALEXANDER S. POPOV, VOLS 1- 4, PROCEEDINGS, 2009, : 1398 - 1405
  • [5] The grouping differential evolution algorithm for multi-dimensional optimization problems
    Piotrowski, Adam P.
    Napiorkowski, Jaroslaw J.
    [J]. CONTROL AND CYBERNETICS, 2010, 39 (02): : 527 - 550
  • [6] Differential Evolution algorithm with Separated Groups for multi-dimensional optimization problems
    Piotrowski, Adam P.
    Napiorkowski, Jaroslaw J.
    Kiczko, Adam
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2012, 216 (01) : 33 - 46
  • [7] Dynamic Multi-dimensional Jaguar Algorithm with Adaptive Step for Optimization Problem
    Yang, Li-Sheng
    Yang, Chia-Yun
    Jiang, Yu-Chi
    Chang, Du-Sing
    Kuo, Shu-Yu
    Chou, Yao-Hsin
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2018, : 1546 - 1551
  • [8] Multi-dimensional portfolio risk and its diversification: A note
    Kim, Woohwan
    Kim, Young Min
    Kim, Tae-Hwan
    Bang, Seungbeom
    [J]. GLOBAL FINANCE JOURNAL, 2018, 35 : 147 - 156
  • [9] MOEA/D with An Improved Multi-Dimensional Mapping Coding Scheme for Constrained Multi-Objective Portfolio Optimization
    Chen, Yi
    Zhou, Aimin
    [J]. 2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2019, : 1742 - 1749
  • [10] Multi-dimensional control of clonal evolution
    Michael McHeyzer-Williams
    [J]. Nature Reviews Immunology, 2017, 17 (3) : 149 - 149