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Issue title: Fuzzy model for human autonomous computing in extreme surveillance and it’s applications
Guest editors: Varatharajan Ramachandran
Article type: Research Article
Affiliations: College of Economics and Management, Wuchang Shouyi University, Wuhan, China
Correspondence: [*] Corresponding author. Ying Han, College of Economics and Management, Wuchang Shouyi University, Wuhan, China. E-mail: [email protected].
Abstract: When choosing stock investment, there are many stock companies, and the stock varieties are also complicated. At present, there are various systems for evaluating stock performance in the market, but there is no uniform standard, so investors often cannot effectively invest in stocks. Simultaneously, stock management companies also have their own characteristics, and there are differences in shareholding structure and internal management structure. Based on this, based on multiple regression models and artificial intelligence models, this paper constructs a stock return influencing factor analysis model to statistically describe the sample data and factor data, and tests the applicability of the five-factor model for performance evaluation of mixed stocks. In addition, this article combines the actual situation to carry out data simulation analysis and uses a five-factor analysis model to carry out quantitative research on stock returns. Through data simulation analysis, we can see that the model constructed in this paper has a certain effect in the analysis of factors affecting stock returns.
Keywords: Multiple regression, artificial intelligence, stock returns, influencing factors
DOI: 10.3233/JIFS-189485
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6457-6467, 2021
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