The study on Chinese investment willingness of private digital currency by big data analysis algorithms

Mengxiang Jin; Weilun Huang

doi:10.1117/12.2669982

1 June 2023 The study on Chinese investment willingness of private digital currency by big data analysis algorithms

Mengxiang Jin, Weilun Huang

Proceedings Volume 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022); 126250A (2023) https://doi.org/10.1117/12.2669982
Event: International Conference on Mathematics, Modeling and Computer Science (MMCS2022),, 2022, Wuhan, China

Abstract

The purpose of this paper is based on the results of questionnaires survey and literature review, combined with the methods of big data analysis algorithms, analysis of correlation, analysis of variance, analysis of regression, analysis of effects and other methods to explore the factors influencing Chinese investors' investment behavior in private digital currencies. The investors' willingness to invest in private digital currencies and the amount they are willing to invest are studied in investment behavior, and the investors' perceptions of the advantages and risks of private digital currencies are studied in influencing factors. The influence of personal factors on private digital currency investment behavior is also studied. The results show that the willingness to invest in private digital currency is significantly and positively related to the perception of individual advantages and social advantages of private digital currency as well as education and income, and significantly and negatively related to the perception of individual risks and social risks. The willingness to invest in private digital currency was significantly and positively correlated with age, education, and income and showed no significant correlation with the perception of private digital currency advantages and risks.

Citation Download Citation

Mengxiang Jin and Weilun Huang "The study on Chinese investment willingness of private digital currency by big data analysis algorithms", Proc. SPIE 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022), 126250A (1 June 2023); https://doi.org/10.1117/12.2669982

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KEYWORDS

Cognition

Statistical analysis

Data analysis

Error analysis

Correlation coefficients

Analytical research

Blockchain

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