Portfolio implementation risk management using evolutionary multiobjective optimization
| Autor: | Roman Denysiuk, Sandra Garcia-Rodriguez, António Gaspar-Cunha, David Quintana |
|---|---|
| Přispěvatelé: | Departamento Lenguajes y Ciencias de la Computación (LCC), Universidad de Málaga [Málaga] = University of Málaga [Málaga], Universidade do Minho = University of Minho [Braga], Laboratoire d'analyse des données et d'intelligence des systèmes (LADIS), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Spanish Ministry of Economy and Competitivity under grant ENE2014-56126-C2-2-R, Portuguese Foundation for Science and Technology under grant PEst-C/CTM/LA0025/2013 (Projecto Estrategico-LA 25-2013-2014-Strategic Project-LA 25-2013-2014), Universidade do Minho, Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Spanish Ministry of Economy and Competitivity under grant ENE2014-56126-C2-2-RPortuguese Foundation for Science and Technology under grant PEst-C/CTM/LA0025/2013 (Projecto Estrategico-LA 25-2013-2014-Strategic Project-LA 25-2013-2014) |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
evolutionary computation
multiobjective optimization portfolio optimization robustness ROBUST OPTIMIZATION Mathematical optimization Computer science [QFIN.PM]Quantitative Finance [q-fin]/Portfolio Management [q-fin.PM] 0211 other engineering and technologies 02 engineering and technology Multi-objective optimization lcsh:Technology Evolutionary computation lcsh:Chemistry [STAT.ML]Statistics [stat]/Machine Learning [stat.ML] 0202 electrical engineering electronic engineering information engineering General Materials Science Trading strategy Robustness (economics) Instrumentation lcsh:QH301-705.5 Risk management Fluid Flow and Transfer Processes 021103 operations research Science & Technology business.industry lcsh:T Process Chemistry and Technology General Engineering Ciências Naturais::Ciências da Computação e da Informação lcsh:QC1-999 Computer Science Applications lcsh:Biology (General) lcsh:QD1-999 multi-objective optimization lcsh:TA1-2040 Portfolio 020201 artificial intelligence & image processing Ciências da Computação e da Informação [Ciências Naturais] [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC] Project portfolio management Portfolio optimization business lcsh:Engineering (General). Civil engineering (General) lcsh:Physics |
| Zdroj: | Applied Sciences Applied Sciences, 2017, 7 (10), pp.1079. ⟨10.3390/app7101079⟩ Applied Sciences, MDPI, 2017, 7 (10), pp.1079. ⟨10.3390/app7101079⟩ Applied Sciences, Vol 7, Iss 10, p 1079 (2017) Applied Sciences; Volume 7; Issue 10; Pages: 1079 Repositório Científico de Acesso Aberto de Portugal Repositório Científico de Acesso Aberto de Portugal (RCAAP) instacron:RCAAP |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app7101079⟩ |
| Popis: | Portfoliomanagementbasedonmean-varianceportfoliooptimizationissubjecttodifferent sources of uncertainty. In addition to those related to the quality of parameter estimates used in the optimization process, investors face a portfolio implementation risk. The potential temporary discrepancybetweentargetandpresentportfolios,causedbytradingstrategies,mayexposeinvestors to undesired risks. This study proposes an evolutionary multiobjective optimization algorithm aiming at regions with solutions more tolerant to these deviations and, therefore, more reliable. The proposed approach incorporates a user’s preference and seeks a fine-grained approximation of the most relevant efficient region. The computational experiments performed in this study are based on a cardinality-constrained problem with investment limits for eight broad-category indexes and 15 years of data. The obtained results show the ability of the proposed approach to address the robustness issue and to support decision making by providing a preferred part of the efficient set. The results reveal that the obtained solutions also exhibit a higher tolerance to prediction errors in asset returns and variance–covariance matrix. Sandra Garcia-Rodriguez and David Quintana acknowledge financial support granted by the Spanish Ministry of Economy and Competitivity under grant ENE2014-56126-C2-2-R. Roman Denysiuk and Antonio Gaspar-Cunha were supported by the Portuguese Foundation for Science and Technology under grant PEst-C/CTM/LA0025/2013 (Projecto Estratégico-LA 25-2013-2014-Strategic Project-LA 25-2013-2014). info:eu-repo/semantics/publishedVersion |
| Databáze: | OpenAIRE |
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