nach oben

Artificial Intelligence Review

Erschienen in:

15.02.2021

Mean-variance-skewness portfolio optimization under uncertain environment using improved genetic algorithm

verfasst von: Sunil Kumar Mittal, Namita Srivastava

Erschienen in: Artificial Intelligence Review | Ausgabe 8/2021

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

An indeterminacy economic environment includes uncertainty during adopting experts knowledge for the analysis of stock returns. The main goal in this paper is to discuss the problem of portfolio selection with uncertain environment; because, the experts alone has the ability to evaluate the security returns and not with the historical data. However, the uncertain variables considered have shown the stock returns. Uncertainty programming is used to formulate mean-variance skewness indicating the problem of portfolio selection in uncertain environment based on different decision criteria. At different conditions, some significant crisp equivalents are explained for the ease of solving models within the uncertainty theory framework. Furthermore, this paper has solved the new models included in general cases using a general method developed through designing a novel hybrid intelligent algorithm. Ultimately, the developed algorithm and models applications and performance was evidently proved using a numerical example.

Vorheriger Artikel Design and applications of an advanced hybrid meta-heuristic algorithm for optimization problems

Nächster Artikel Algorithm for T-spherical fuzzy MADM based on associated immediate probability interactive geometric aggregation operators

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Ahmadi-Javid A (2012) Entropic value-at-risk: A new coherent risk measure. J Optim Theory Appl 155(3):1105–1123MathSciNetCrossRef

Ahmadi-Javid A, Fallah-Tafti M (2019) Portfolio optimization with entropic value-at-risk. Eur J Oper Res 279(1):225–241MathSciNetCrossRef

Artzner P, Delbaen F, Eber J-M, Heath D (1999) Coherent measures of risk. Math Finance 9(3):203–228MathSciNetCrossRef

Carlsson C and Fullér R (2009) Possibilistic mean value and variance of fuzzy numbers: Some examples of application. In 2009 IEEE International Conference on Fuzzy Systems, 587–592. IEEE

Chang T-J, Yang S-C, Chang K-J (2009) Portfolio optimization problems in different risk measures using genetic algorithm. Expert Syst Appl 36(7):10529–10537CrossRef

Chen K, Zhou Y, Dai F (2015) A LSTM-based method for stock returns prediction: A case study of China stock market. In 2015 IEEE international conference on big data (big data). IEEE, pp 2823–2824

Chen W, Wang Y, Gupta P, Mehlawat MK (2018) A novel hybrid heuristic algorithm for a new uncertain mean-variance-skewness portfolio selection model with real constraints. Appl Intell 48(9):2996–3018CrossRef

Cheong D, Kim YM, Byun HW, Oh KJ, Kim TY (2017) Using genetic algorithm to support clustering-based portfolio optimization by investor information. Appl Soft Comput 61:593–602CrossRef

Freitas FD, de Souza AF, de Almeida AR (2009) Prediction-based portfolio optimization model using neural networks. Neurocomputing 72(10–12):2155–2170CrossRef

García F, González-Bueno J, Oliver J, Riley N (2019a) Selecting socially responsible portfolios: a fuzzy multicriteria approach. Sustainability 11(9):2496CrossRef

García F, González-Bueno J, Oliver J, Tamošiūnienė R (2019b) A credibilistic mean-semivariance-PER portfolio selection model for Latin America. Journal of Business Economics and Management 20(2):225–243CrossRef

Guijarro F and Prodromos E. Tsinaslanidis, (2019) A surrogate similarity measure for the mean-variance frontier optimisation problem under bound and cardinality constraints. Journal of the Operational Research Society, 1–16.

Gupta P, Mehlawat MK, Yadav S, Kumar A (2020) Intuitionistic fuzzy optimistic and pessimistic multi-period portfolio optimization models. Soft Comput 24(16):11931–11956CrossRef

Harvey CR, Liechty JC, Liechty MW, Müller P (2010) Portfolio selection with higher moments. Quant Finance 10(5):469–485MathSciNetCrossRef

Hsieh T-J, Hsiao H-F, Yeh W-C (2011) Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm. Appl Soft Comput 11(2):2510–2525CrossRef

Huang X (2011) Mean-risk model for uncertain portfolio selection.". Fuzzy Optim Decis Making 10(1):71–89MathSciNetCrossRef

Huang X, Ying H (2013) Risk index based models for portfolio adjusting problem with returns subject to experts’ evaluations. Econ Model 30:61–66CrossRef

Jana P, Roy TK, Mazumder SK (2009) Multi-objective possibilistic model for portfolio selection with transaction cost. J Comput Appl Math 228(1):188–196MathSciNetCrossRef

Li H-Q, Yi Z-H (2019) Portfolio selection with coherent Investor’s expectations under uncertainty. Expert Syst Appl 133:49–58CrossRef

Li L, Li J, Qin Q, and Cheng S (2013) Credibilistic conditional value at risk under fuzzy environment. In 2013 Sixth International Conference on Advanced Computational Intelligence (ICACI), 350–353. IEEE

Li Bo, Zhu Y, Sun Y, Aw G, Teo KL (2018) Multi-period portfolio selection problem under uncertain environment with bankruptcy constraint. Appl Math Model 56:539–550MathSciNetCrossRef

Liagkouras K, Metaxiotis K (2018) Multi-period mean–variance fuzzy portfolio optimization model with transaction costs. Eng Appl Artificial Intell 67:260–269CrossRef

Lipton ZC, Berkowitz J, Elkan C (2015) A critical review of recurrent neural networks for sequence learning. arXiv preprintarXiv:1506.00019

Liu B (2010) Uncertainty theory. Springer, Berlin, pp 1–79CrossRef

Liu Y, Qin Z (2012) Mean semi-absolute deviation model for uncertain portfolio optimization problem. J Uncertain Syst 6(4):299–307MathSciNet

Liu Y-J, Zhang W-G, Zhang Q (2016) Credibilistic multi-period portfolio optimization model with bankruptcy control and affine recourse.". Appl Soft Comput 38:890–906CrossRef

Liu N, Chen Y, Liu Y (2018) Optimizing portfolio selection problems under credibilistic CVaR criterion. J Intell Fuzzy Syst 34(1):335–347MathSciNetCrossRef

Liu YJ, Zhang WG, Gupta P (2019) Multiperiod portfolio performance evaluation model based on possibility theory. IEEE Trans Fuzzy Syst 28(12):3391–3405CrossRef

Macedo LL, Godinho P, Alves MJ (2017) Mean-semivariance portfolio optimization with multi-objective evolutionary algorithms and technical analysis rules. Expert Syst Appl 79:33–43CrossRef

Mehlawat MK (2016) Credibilistic mean-entropy models for multi-period portfolio selection with multi-choice aspiration levels. Inf Sci 345:9–26CrossRef

Mercangöz BA, and Eroglu E (2019) The Genetic Algorithm: An Application on Portfolio Optimization. In Metaheuristic Approaches to Portfolio Optimization, 154–178 IGI Global

Mittal SK, Srivastava N (2020) Gated neural network-based mean–EVaR–skewness portfolio optimization under uncertain environment. J Circuits Syst Comput 30(6):2150100CrossRef

Nelson DMQ, Pereira ACM, de Oliveira RA (2017) Stock market's price movement prediction with LSTM neural networks. In 2017 International joint conference on neural networks (IJCNN). IEEE, pp 1419–1426

Qin Z (2017) Random fuzzy mean-absolute deviation models for portfolio optimization problem with hybrid uncertainty. Applied Soft Computing 56:597–603CrossRef

Qin Z, Kar S, and Li X (2009) Developments of mean-variance model for portfolio selection in uncertain environment.

Sundararaj V (2019) Optimised denoising scheme via opposition-based self-adaptive learning PSO algorithm for wavelet-based ECG signal noise reduction. Int J Biomed Eng Technol 31(4):325CrossRef

Sundararaj V, Muthukumar S, Kumar RS (2018) An optimal cluster formation based energy efficient dynamic scheduling hybrid MAC protocol for heavy traffic load in wireless sensor networks. Comput Secur 77:277–288CrossRef

Sundararaj V, Anoop V, Dixit P, Arjaria A, Chourasia U, Bhambri P, Rejeesh MR, Sundararaj R (2020) CCGPA-MPPT: Cauchy preferential crossover-based global pollination algorithm for MPPT in photovoltaic system. Prog Photovolt 28(11):1128–1145CrossRef

Thakur M, Meghwani SS, Jalota H (2014) A modified real coded genetic algorithm for constrained optimization. Appl Math Comput 235:292–317MathSciNetMATH

Vinu S (2016) An efficient threshold prediction scheme for wavelet based ECG signal noise reduction using variable step size firefly algorithm. Int J Intell Eng Syst 9(3):117–126

Vinu S (2019) Optimal task assignment in mobile cloud computing by queue based ant-bee algorithm. Wirel Pers Commun 104(1):173–197CrossRef

Wang Bo, Li Y, Watada J (2017) Multi-period portfolio selection with dynamic risk/expected-return level under fuzzy random uncertainty. Inf Sci 385:1–18MATH

Chen W, Xu W (2019) A hybrid multiobjective bat algorithm for fuzzy portfolio optimization with real-world constraints. Int J Fuzzy Syst 21(1):291–307MathSciNetCrossRef

Yue W, Wang Y, Xuan H (2019) Fuzzy multi-objective portfolio model based on semi-variance–semi-absolute deviation risk measures. Soft Comput 23(17):8159–8179CrossRef

Zhang W-G, Wang Y-L, Chen Z-P, Nie Z-K (2007) Possibilistic mean–variance models and efficient frontiers for portfolio selection problem. Inf Sci 177(13):2787–2801MathSciNetCrossRef

Zhang W-G, Liu Y-J, Wei-Jun Xu (2012) A possibilistic mean-semivariance-entropy model for multi-period portfolio selection with transaction costs. Eur J Oper Res 222(2):341–349MathSciNetCrossRef

Zhou J, Li X, Pedrycz W (2016) Mean-semi-entropy models of fuzzy portfolio selection. IEEE Trans Fuzzy Syst 24(6):1627–1636CrossRef

Zhu H, and Zhang J (2009) A credibility-based fuzzy programming model for APP problem. In 2009 International Conference on Artificial Intelligence and Computational Intelligence, 1: 455–459 IEEE

Titel: Mean-variance-skewness portfolio optimization under uncertain environment using improved genetic algorithm
verfasst von: Sunil Kumar Mittal
Namita Srivastava
Publikationsdatum: 15.02.2021
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 8/2021
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-021-09966-2

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 8/2021

Decision-making model for China’s stock market bubble warning: the CoCoSo with picture fuzzy information

A data-driven missing value imputation approach for longitudinal datasets

Multi-focus image fusion techniques: a survey

Benchmarking lightweight face architectures on specific face recognition scenarios

Algorithm for T-spherical fuzzy MADM based on associated immediate probability interactive geometric aggregation operators

Transformer models for text-based emotion detection: a review of BERT-based approaches

Premium Partner