A comprehensive decision support system for stock investment decisions

Solares, Efrain; De-León-Gómez, Víctor; Salas, Francisco; Díaz, Raymundo

doi:10.1016/j.eswa.2022.118485

Cited by 10 publications

(2 citation statements)

References 76 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results showed that the proposed two-step ahead prediction model is feasible and is better suited for short-term profits. In a recent work, Solares et al (2022) demonstrated a combined forecasting, selection and optimization framework related to investment in equity market. The authors applied artificial neural network, fundamental analysis, differential evolution and evolutionary algorithms like genetic algorithm for the stocks listed at the S&P's 500 index.…”

Section: Stock Selection Using Statistical Analysis and Predictive An...mentioning

confidence: 99%

A Multi-Criteria Based Stock Selection Framework in Emerging Market

Biswas

Bandyopadhyay

Pamučar

et al. 2022

Oper. Res. Eng. Sci. Theor. Appl.

View full text Add to dashboard Cite

The present study aims to compare the stock performances of the Fast Moving Consumer Goods (FMCG) and Consumer Durables (CD) firms at the Bombay Stock Exchange (BSE), India. It is evident from the extant literature that investment in the stock market depends on two broad objectives such as maximization of return while minimization of risk. Besides, investment decisions are also influenced by the behavioral nature of the investors. To this end, the current work considers the earning prospect (average market return, return on net worth, earning per share, and yield), marketcentric risk (beta), market perception (price to book value, shares traded), momentum (turnover) and benchmarked performance (alpha) to set the criteria for comparison. The study period considers seven consecutive financial years to discern the performance. For the comparative analysis, a combined multi-criteria decision-making (MCDM) framework of Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) (used to determine criteria weights) and Evaluation Based on Distance fromAverage Solution (EDAS) (for ranking) methods has been utilized. Borda Count Method (BC), Copeland Method, and Simple Additive Weighting (SAW) have been used to aggregate the year-wise rankings. The calculated weights show consistency to the modern portfolio theory as average return, beta, and return on net worth obtain higher weightage than others. It is observed that there are variations in the year-wise comparative ranking, while on aggregation, FMCG firms dominate the top positions. The analysis reveals that Avanti Feeds Ltd.

show abstract

Section: Stock Selection Using Statistical Analysis and Predictive An...mentioning

confidence: 99%

A Multi-Criteria Based Stock Selection Framework in Emerging Market

Biswas

Bandyopadhyay

Pamučar

et al. 2022

Oper. Res. Eng. Sci. Theor. Appl.

View full text Add to dashboard Cite

show abstract

“…In terms of the selection of evaluation methods, because in the current research, fuzzy comprehensive analysis method has been widely used in quantitative risk assessment of Arctic oil spills, vulnerability assessment and influencing factor analysis of marine economic system and risk assessment of renewable energy investment, highlighting its good ability in quantitative risk assessment, Therefore, this paper selects the fuzzy comprehensive analysis model as the main evaluation model for scoring [6][7][8]. In the process of building the model, according to the existing comprehensive decision-making support system for stock investment decision-making and other evidence of venture capital around the world at this stage, the early evidence of banks and fintech stocks, and the existing data of banking systemic risk around covid-19, this paper objectively and comprehensively constructs the weight allocation scheme in the model [9][10][11][12]. Finally, this paper constructs the final appropriate stock investment decision through Sharpe ratio.…”

Section: Introductionmentioning

confidence: 99%

Stock Screening Based on Fuzzy Comprehensive Evaluation Model: A Case Study of the U.S. Financial Services Industry Banking under the COVID-19 pandemic

Yu¹

2023

BCPBM

View full text Add to dashboard Cite

Faced with the strong impact of the epidemic, investment strategies also need to be optimized according to the actual situation. This paper analyzes the data of 282 stocks in the financial services industry and banking industry in the U.S. stock market from 2015-2021 through the fuzzy comprehensive analysis model, and selects a relatively appropriate intra industry portfolio according to the Sharpe ratio. In the process of research, based on the existing data and the social assessment of the covid-19 epidemic, a fuzzy comprehensive analysis model was initially constructed. This provides corresponding evaluation rules for each influencing factor, and determines its weight in a certain level of fuzzy comprehensive analysis model. Then, the experiment can screen out 29 high-quality stocks in the industry according to the total score. Then, the experiment classifies high-quality stocks according to their different characteristics, and selects the stocks with the highest scores in each category to participate in portfolio comparison. Finally, the experiment will focus on the Sharpe ratio and select a relatively good portfolio example at this stage after comprehensively evaluating the rationality of other values. At present, this example has strong investment value, and the investment strategy discussed in this paper may also have strong applicability in other industries after appropriate adjustment.

show abstract