Stock Portfolio Selection Hybridizing Fuzzy Base-Criterion Method and Evidence Theory in Triangular Fuzzy Environment

Bisht, Kiran; Kumar, Arun

doi:10.1007/s43069-022-00167-3

Cited by 8 publications

(4 citation statements)

References 48 publications

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“…O Sistema de Inferência Fuzzy (SIF) é baseado nos conceitos de conjuntos, regras e raciocínio fuzzy. As regras se mostram eficientes na modelagem de proposic ¸ões em linguagem natural e esses sistemas podem ser encontrados de forma isolada ou combinada com outros métodos [Das et al 2022] em aplicac ¸ões em áreas de classificac ¸ão, regressão e agrupamento de dados [Skrjanc et al 2019], predic ¸ão de séries temporais [Orang et al 2022], tomada de decisões [Bisht and Kumar 2022] entre outros. O SIF é um modelo que faz predic ¸ões numéricas a partir dos dados de entrada e, por esse motivo é utilizado neste trabalho como um método de regressão.…”

Section: Sistemas De Inferência Fuzzyunclassified

“…Uma estrutura integrada de tomada de decisão multicritério usando conjunto fuzzy triangulares é desenvolvida para a construc ¸ão de portfólio, unificando as avaliac ¸ões de um investidor iniciante e de um especialista no mercado de ac ¸ões em [Bisht and Kumar 2022]. O trabalho de [Jiménez-Preciado et al 2022] teve como objetivo desenvolver um modelo de AM para detectar empresas com vantagens competitivas duradouras de acordo com seus índices financeiros, a fim de melhorar o desempenho das carteiras de investimento.…”

Section: Trabalhos Relacionadosunclassified

“…Ambos os trabalhos citados têm, como o apresentado neste artigo, o objetivo de simplificar o processo de selec ¸ão de ac ¸ões para investidores inexperientes. Entretanto, esses dois trabalhos requerem o uso de procedimentos mais complexos, seja para obter e estruturar o conhecimento de especialistas, como em [Bisht and Kumar 2022], ou para obter dados, calcular índices e fazer a classificac ¸ão manual das ac ¸ões em categorias, como em [Jiménez-Preciado et al 2022]. Já a abordagem proposta por nós requer apenas dados disponibilizados publicamente que podem ser obtidos com razoável facilidade.…”

Section: Trabalhos Relacionadosunclassified

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Uma Estratégia para Alocação de Carteira de Ações usando Algoritmos de Aprendizado de Máquina e Regras Fuzzy

Gambim,

Camargo,

Lucca

et al. 2023

Anais Do XX Encontro Nacional De Inteligência Artificial E Computacional (ENIAC 2023)

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No mercado de ações, investidores interessados em investimentos de longo prazo buscam formas de selecionar ações com potencial de valorização futura para melhorar seus rendimentos. Os métodos de aprendizado de máquina têm um longo histórico de aplicações no mercado financeiro. Este artigo apresenta e avalia uma estratégia simples e eficaz para alocação de carteiras de ações, que utiliza algoritmos de aprendizado de máquina para prever o desempenho das ações e selecionar algumas delas para compor a carteira. O método proposto é particularmente útil para investidores com pouco conhecimento do mercado. Os resultados obtidos mostram que a estratégia proposta levou à alocação de carteiras com lucros superiores aos do índice de mercado S&P500 e aos de um método manual conhecido na literatura.

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Section: Sistemas De Inferência Fuzzyunclassified

Section: Trabalhos Relacionadosunclassified

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Uma Estratégia para Alocação de Carteira de Ações usando Algoritmos de Aprendizado de Máquina e Regras Fuzzy

Gambim,

Camargo,

Lucca

et al. 2023

Anais Do XX Encontro Nacional De Inteligência Artificial E Computacional (ENIAC 2023)

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“…In recent years, researchers have applied and extended the BCM under various fuzzy sets like triangular fuzzy numbers (TFNs) (Haseli et al 2021 ; Narang et al 2021 ), hesitant fuzzy multiplicative (Narang et al 2022b ), Heronian mean (Narang et al 2022a ), spherical fuzzy (Haseli and Jafarzadeh Ghoushchi 2022 ), and evidence theory (Bisht and Kumar 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Assessment of sustainable waste management alternatives using the extensions of the base criterion method and combined compromise solution based on the fuzzy Z-numbers

Zafaranlouei

Ghoushchi

Haseli

2023

Environ Sci Pollut Res

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A number of factors have contributed to the increase in waste production and diversity of waste, such as the increase in population, alterations in consumption patterns, economic development, income changes, urbanization, and industrialization. The production of different types of waste, such as electronic, urban, hospital, and industrial waste, makes it necessary to classify waste accurately and recognize effective criteria for waste management. To design and operate waste management systems, it is necessary to understand the sources and types of waste, as well as information about their composition and rate of production. As a result, this study aims to rank 21 types of waste according to Iran’s economic, social, and environmental criteria, as well as 13 sub-criteria related to those criteria. For this aim, proposed a novel decision-making approach based on the extension of the base criterion method (BCM) and combined compromise solution (CoCoSo) methods under fuzzy Z -numbers. Additionally, sensitivity analysis and comprehensive analysis are conducted on the results of the criteria and alternatives of sustainable waste management. Based on the results of this study, direct profit and reduced landfill are the most important criteria for assessing sustainable waste management alternatives. According to the results of this study, the sub-alternative of industrial metal waste is the most important waste management option. Examining the next sub-alternative ranks under sustainable waste management options (mobile, communication equipment, and battery) shows that electronic waste requires more attention for recycling and sustainable waste management. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-023-26380-z.

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A fuzzy model for financial performance measurement of real estate investment trusts: comparison of investment areas

Kazanci,

Ulubeyli,

Dogan

2023

ECAM

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PurposeThis study aims to present the financial performance of companies and investment areas in the real estate investment trust (REIT) industry.Design/methodology/approachA fuzzy model for financial performance measurement (FM-FPM) was proposed through the collaboration of fuzzy axiomatic design (FAD) and fuzzy entropy weighting (FEW). For the data, financial ratios were used, and their importance and functional requirements were collected via a questionnaire survey.FindingsThe FM-FPM is a beneficial model to be used for a REIT industry based on the structured procedures of FAD and FEW techniques. It can be suitable to regularly evaluate the performance of REITs and their investment areas in financial means, especially in today’s turbulent business environment. The Turkish market that was considered to show the practical applicability of the FM-FPM demonstrated specifically that diversified real estate was found to rank first, followed by mixed-buildings, warehouses, shopping malls and hotels, respectively.Research limitations/implicationsThe FM-FPM can be employed for REIT industries in other countries and adapted to different industries. However, more respondents or a different set of criteria might lead to different outputs.Practical implicationsThe FM-FPM may guide REIT managers and investors while making their decisions and controlling the performance of REITs and investment areas.Social implicationsThe FM-FPM may encourage low- and middle-income investors to make good use of their savings.Originality/valueThe research is first (1) to offer a FPM model in order to determine investable areas in a REIT industry and (2) to employ multiple criteria decision-making tools in order to measure the financial performance of individual companies and investment areas in a REIT industry.

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Stock Portfolio Selection Hybridizing Fuzzy Base-Criterion Method and Evidence Theory in Triangular Fuzzy Environment

Cited by 8 publications

References 48 publications

Uma Estratégia para Alocação de Carteira de Ações usando Algoritmos de Aprendizado de Máquina e Regras Fuzzy

Uma Estratégia para Alocação de Carteira de Ações usando Algoritmos de Aprendizado de Máquina e Regras Fuzzy

Assessment of sustainable waste management alternatives using the extensions of the base criterion method and combined compromise solution based on the fuzzy Z-numbers

A fuzzy model for financial performance measurement of real estate investment trusts: comparison of investment areas

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