Portfolio optimization: Risk metric with increased objective space
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/15189 |
Resumo: | Markowitz's efficient EV portfolio model, given a minimum required return, minimizes the portfolio variance, a central trend risk metric calculated by the statistical method of data concentration, and thus uses a literal formula allowing the optimization solution by a quadratic algorithm, requiring little computational consumption. The evolution of the Markowitz model for asymmetric risk metrics, minimizes and/or maximizes risk, below and/or above a target t, such as downside risk, mean-separated target deviations, value at risk and conditional value at risk, however, do not allow the use of a literal formula for the optimization solution, transformed into a non-smooth algorithm, with a complex solution and greater computational consumption. The relevant aspect of the Markowitz model was to show that the most important is not the risk of the asset, but the contribution that each asset provides to the risk of the portfolio, which depends on the interrelationships between the assets, the covariance of the portfolio. Extending the reasoning as an original and relevant contribution, the article presents a new asymmetric risk metric, with greater detail of the interrelationships between assets, increasing the objective space of the optimization, with a greater number of optimized parameters, enabling the search for better results and using a literal expression allowing solution by a non-linear algorithm, less complex than the non-smooth algorithm. The bibliometric analysis carried out demonstrates the originality of the evolution of the Markowitz model for asymmetric risk metrics, presenting a literal formula for solution and with increased objective space. |
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Portfolio optimization: Risk metric with increased objective spaceOptimización de lo portfolio: Métrica de riesgo con mayor espacio objetivoOtimização de portfólio: Métrica do risco com espaço objetivo aumentadoMétrica de riesgoMayor espacio objetivoMétrica estadística eficienteNuevas métricas para la eficiencia de lo portfolioOptimización de portfolio.Métrica do riscoEspaço objetivo aumentadoMétrica estatística eficienteNovas métricas para eficiência do portfólioOtimização de portfólio.Risk metricIncreased objective spaceEfficient statistical metricNew metrics for portfolio efficiencyPortfolio optimization.Markowitz's efficient EV portfolio model, given a minimum required return, minimizes the portfolio variance, a central trend risk metric calculated by the statistical method of data concentration, and thus uses a literal formula allowing the optimization solution by a quadratic algorithm, requiring little computational consumption. The evolution of the Markowitz model for asymmetric risk metrics, minimizes and/or maximizes risk, below and/or above a target t, such as downside risk, mean-separated target deviations, value at risk and conditional value at risk, however, do not allow the use of a literal formula for the optimization solution, transformed into a non-smooth algorithm, with a complex solution and greater computational consumption. The relevant aspect of the Markowitz model was to show that the most important is not the risk of the asset, but the contribution that each asset provides to the risk of the portfolio, which depends on the interrelationships between the assets, the covariance of the portfolio. Extending the reasoning as an original and relevant contribution, the article presents a new asymmetric risk metric, with greater detail of the interrelationships between assets, increasing the objective space of the optimization, with a greater number of optimized parameters, enabling the search for better results and using a literal expression allowing solution by a non-linear algorithm, less complex than the non-smooth algorithm. The bibliometric analysis carried out demonstrates the originality of the evolution of the Markowitz model for asymmetric risk metrics, presenting a literal formula for solution and with increased objective space.El modelo de portfolio EV eficiente de Markowitz, dado un rendimiento mínimo requerido, minimiza la varianza de la cartera, una métrica del riesgo de tendencia central calculada por el método estadístico de concentración de datos y, por lo tanto, utiliza una fórmula literal que permite la solución de la optimización mediante un algoritmo cuadrático, lo que requiere poco consumo computacional. La evolución del modelo de Markowitz para métricas asimétricas de riesgo, minimiza y/o maximiza el riesgo, por debajo y/o por encima de un objetivo t, como el downside risk, el mean-separated target deviations, el value at risk and el conditional value at risk, sin embargo, no permiten el uso de una fórmula literal para la solución de la optimización, transformada en un algoritmo no suave, con una solución compleja y mayor consumo computacional. El aspecto relevante del modelo de Markowitz fue mostrar que lo más importante no es el riesgo del activo sino la contribución que cada activo proporciona al riesgo de lo portfolio, que depende de las interrelaciones entre los activos, la covarianza de lo portfolio. Ampliando el razonamiento como un aporte original y relevante, el artículo presenta una nueva métrica asimétrica de riesgo, con mayor detalle de las interrelaciones entre activos, aumentando el espacio objetivo de optimización, con un mayor número de parámetros optimizados, posibilitando la búsqueda de mejores resultados y utilizando una expresión literal que permite la solución mediante un algoritmo no lineal, menos complejo que el algoritmo no suave. El análisis bibliométrico realizado demuestra la originalidad de la evolución del modelo de Markowitz para métricas asimétricas de riesgo, presentando una fórmula literal de solución y con mayor espacio objetivo.O modelo de portfólio EV eficiente de Markowitz, dado um retorno mínimo requerido, minimiza a variância do portfólio, uma métrica do risco de tendência central calculada pelo método estatístico de concentração de dados, e assim utiliza uma fórmula literal permitindo a solução da otimização por um algoritmo quadrático, exigindo pouco consumo computacional. As evoluções do modelo de Markowitz para métricas assimétricas do risco, minimizam e/ou maximizam o risco, abaixo e/ou acima de um alvo t, como o downside risk, o mean-separated target deviations, o value at risk e o conditional value at risk, porém, não permitem utilizar uma fórmula literal para solução da otimização, transformada em um algoritmo não suave, com solução complexa e maior consumo computacional. O aspecto relevante do modelo de Markowitz foi mostrar que o mais importante não é o risco do ativo mas a contribuição que cada ativo fornece para o risco do portfólio, que depende das interrelações entre os ativos, a covariância do portfólio. Estendendo o raciocínio como contribuição original e relevante, o artigo apresenta uma nova métrica assimétrica do risco, com maior detalhamento das interrelações entre os ativos, aumentando o espaço objetivo da otimização, com maior número de parâmetros otimizados, possibilitando a busca por melhores resultados e utilizando uma expressão literal permitindo solução por um algoritmo não linear, menos complexo que o algoritmo não suave. A análise bibliométrica realizada demonstra a originalidade da evolução do modelo de Markowitz para métricas assimétricas do risco, apresentando fórmula literal para solução e com espaço objetivo aumentado.Research, Society and Development2021-05-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/1518910.33448/rsd-v10i5.15189Research, Society and Development; Vol. 10 No. 5; e47210515189Research, Society and Development; Vol. 10 Núm. 5; e47210515189Research, Society and Development; v. 10 n. 5; e472105151892525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/15189/13605Copyright (c) 2021 Marcos Huber Mendes; Reinaldo Castro Souza; Marco Aurélio Sanfinshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessMendes, Marcos Huber Souza, Reinaldo Castro Sanfins, Marco Aurélio 2021-05-17T18:20:49Zoai:ojs.pkp.sfu.ca:article/15189Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:36:04.279721Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Portfolio optimization: Risk metric with increased objective space Optimización de lo portfolio: Métrica de riesgo con mayor espacio objetivo Otimização de portfólio: Métrica do risco com espaço objetivo aumentado |
title |
Portfolio optimization: Risk metric with increased objective space |
spellingShingle |
Portfolio optimization: Risk metric with increased objective space Mendes, Marcos Huber Métrica de riesgo Mayor espacio objetivo Métrica estadística eficiente Nuevas métricas para la eficiencia de lo portfolio Optimización de portfolio. Métrica do risco Espaço objetivo aumentado Métrica estatística eficiente Novas métricas para eficiência do portfólio Otimização de portfólio. Risk metric Increased objective space Efficient statistical metric New metrics for portfolio efficiency Portfolio optimization. |
title_short |
Portfolio optimization: Risk metric with increased objective space |
title_full |
Portfolio optimization: Risk metric with increased objective space |
title_fullStr |
Portfolio optimization: Risk metric with increased objective space |
title_full_unstemmed |
Portfolio optimization: Risk metric with increased objective space |
title_sort |
Portfolio optimization: Risk metric with increased objective space |
author |
Mendes, Marcos Huber |
author_facet |
Mendes, Marcos Huber Souza, Reinaldo Castro Sanfins, Marco Aurélio |
author_role |
author |
author2 |
Souza, Reinaldo Castro Sanfins, Marco Aurélio |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Mendes, Marcos Huber Souza, Reinaldo Castro Sanfins, Marco Aurélio |
dc.subject.por.fl_str_mv |
Métrica de riesgo Mayor espacio objetivo Métrica estadística eficiente Nuevas métricas para la eficiencia de lo portfolio Optimización de portfolio. Métrica do risco Espaço objetivo aumentado Métrica estatística eficiente Novas métricas para eficiência do portfólio Otimização de portfólio. Risk metric Increased objective space Efficient statistical metric New metrics for portfolio efficiency Portfolio optimization. |
topic |
Métrica de riesgo Mayor espacio objetivo Métrica estadística eficiente Nuevas métricas para la eficiencia de lo portfolio Optimización de portfolio. Métrica do risco Espaço objetivo aumentado Métrica estatística eficiente Novas métricas para eficiência do portfólio Otimização de portfólio. Risk metric Increased objective space Efficient statistical metric New metrics for portfolio efficiency Portfolio optimization. |
description |
Markowitz's efficient EV portfolio model, given a minimum required return, minimizes the portfolio variance, a central trend risk metric calculated by the statistical method of data concentration, and thus uses a literal formula allowing the optimization solution by a quadratic algorithm, requiring little computational consumption. The evolution of the Markowitz model for asymmetric risk metrics, minimizes and/or maximizes risk, below and/or above a target t, such as downside risk, mean-separated target deviations, value at risk and conditional value at risk, however, do not allow the use of a literal formula for the optimization solution, transformed into a non-smooth algorithm, with a complex solution and greater computational consumption. The relevant aspect of the Markowitz model was to show that the most important is not the risk of the asset, but the contribution that each asset provides to the risk of the portfolio, which depends on the interrelationships between the assets, the covariance of the portfolio. Extending the reasoning as an original and relevant contribution, the article presents a new asymmetric risk metric, with greater detail of the interrelationships between assets, increasing the objective space of the optimization, with a greater number of optimized parameters, enabling the search for better results and using a literal expression allowing solution by a non-linear algorithm, less complex than the non-smooth algorithm. The bibliometric analysis carried out demonstrates the originality of the evolution of the Markowitz model for asymmetric risk metrics, presenting a literal formula for solution and with increased objective space. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-05-13 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/15189 10.33448/rsd-v10i5.15189 |
url |
https://rsdjournal.org/index.php/rsd/article/view/15189 |
identifier_str_mv |
10.33448/rsd-v10i5.15189 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/15189/13605 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2021 Marcos Huber Mendes; Reinaldo Castro Souza; Marco Aurélio Sanfins https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2021 Marcos Huber Mendes; Reinaldo Castro Souza; Marco Aurélio Sanfins https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 10 No. 5; e47210515189 Research, Society and Development; Vol. 10 Núm. 5; e47210515189 Research, Society and Development; v. 10 n. 5; e47210515189 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
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1797052817890869248 |