Multi-period mean-semi-entropy portfolio management with transaction costs and bankruptcy control
| Autor: | Jiandong Zhou, Xiang Li |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
021103 operations research General Computer Science Computer science Entropy (statistical thermodynamics) Financial market 0211 other engineering and technologies Downside risk Computational intelligence 02 engineering and technology Portfolio investment Fuzzy logic Nonlinear programming Entropy (classical thermodynamics) Bankruptcy 0202 electrical engineering electronic engineering information engineering Financial modeling Entropy (information theory) 020201 artificial intelligence & image processing Entropy (energy dispersal) Project portfolio management Portfolio optimization Entropy (arrow of time) Entropy (order and disorder) |
| Zdroj: | Journal of Ambient Intelligence and Humanized Computing. 12:705-715 |
| ISSN: | 1868-5145 1868-5137 |
| DOI: | 10.1007/s12652-020-02053-4 |
| Popis: | This study investigates a multi-period portfolio management problem under fuzzy settings. For the first time, the newly proposed semi-entropy in the literature is employed as an efficient downside risk measure for risk control in multi-period portfolio optimization. Fuzzy techniques for financial modeling show advantageous performance when future financial market conditions cannot be effectively detected with only historical data. We describe the assert returns by fuzzy variables. Two realistic constraints of transaction costs and bankruptcy events are taken into consideration in our model formulation of a multi-period mean-semi-entropy optimization program. The formulated program is rewritten as a crisp single-objective nonlinear programming by introducing a risk-aversion factor, and final solution to the program is obtained by using genetic algorithm. For the demonstration of computational results, we provide a numerical example with real-life stock data, which illustrates the main modelling concept and the efficiency of genetic algorithm solving method. Comparative analyses over several baseline models show the advantages of adopting fuzzy semi-entropy as an efficient downside risk measure for multi-period portfolio investment optimization. |
| Databáze: | OpenAIRE |
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