International Financial Market Analysis and Investment Strategy Formulation Based on Social Network Data

Jie Huang

doi:10.47297/wspdecWSP2515-797308.20240802

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International Financial Market Analysis and Investment Strategy Formulation Based on Social Network Data

8卷第2期

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International Financial Market Analysis and Investment Strategy Formulation Based on Social Network Data
International Financial Market Analysis and Investment Strategy Formulation Based on Social Network Data
Nanjing University of Finance and Economics, Nantong, Jiangsu 210023
2024年8卷第2期页码：51-56
纸质出版日期： 2024-12-24 ，
DOI：10.47297/wspdecWSP2515-797308.20240802
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(2024). International Financial Market Analysis and Investment Strategy Formulation Based on Social Network Data. 发展经济学, 8(2), 51-56.

Jie Huang.International Financial Market Analysis and Investment Strategy Formulation Based on Social Network Data[J].Development Economics of China,2024,08(02):51-56.
(2024). International Financial Market Analysis and Investment Strategy Formulation Based on Social Network Data. 发展经济学, 8(2), 51-56. DOI： 10.47297/wspdecWSP2515-797308.20240802.

Jie Huang.International Financial Market Analysis and Investment Strategy Formulation Based on Social Network Data[J].Development Economics of China,2024,08(02):51-56. DOI： 10.47297/wspdecWSP2515-797308.20240802.

摘要

Abstract

This work examines the integration of social network data into financial market analysis and investment strategy formulation. Social network data

derived from platforms provides real-time insights into market sentiment and investor behavior

offering a novel perspective that traditional financial metrics might miss. The review highlights the definition

characteristics

and relevance of social network data

including its volume

velocity

and variety. The significance of incorporating social network data into financial analysis is emphasized

showcasing its ability to enhance market sentiment analysis

predict trends

and inform investment strategies. Challenges related to data quality

privacy

and methodological limitations are also addressed. This work concludes with recommendations for future research to refine analytical methods and integrate social network data more effectively with traditional financial analysis

underscoring its potential to revolutionize investment strategies and market analysis.

关键词

Keywords

social network datafinancial market analysisinvestment strategiessentiment analysisdata processing

references

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Marti G., Nielsen F., Bińkowski M., & Donnat P. (2021). A review of two decades of correlations, hierarchies, networks and clustering in financial markets. Progress in information geometry: Theory and applications, 245-274.

Li X., & Sun Y. (2020). Stock intelligent investment strategy based on support vector machine parameter optimization algorithm. Neural Computing and Applications, 32(6), 1765-1775.

Olayinka A. A. (2022). Financial statement analysis as a tool for investment decisions and assessment of companies' performance. International Journal of Financial, Accounting, and Management, 4(1), 49-66.

de Oliveira Carosia A. E., Coelho G. P., & Da Silva A. E. A. (2021). Investment strategies applied to the Brazilian stock market: a methodology based on sentiment analysis with deep learning. Expert Systems with Applications, 184, 115470.

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