Affiliation:
1. Shanghai University, Center for Global Studies, Shanghai, China
2. College of Economics and Business Administration, Chongqing University, P.R. China
Abstract
The economic interaction between the countries of the world is gradually strengthening. Among them, the US stock market is a “barometer” of the global economy, which has a huge impact on the global economy. Therefore, it is of great significance to study the data in the US stock market, especially the data mining algorithm of abnormal data. At present, although data mining technology has achieved many research results in the financial field, it has not formed a good research system for time series data in stock market anomalies. According to the actual performance and data characteristics of the stock market anomaly, this paper uses data mining techniques to find the abnormal data in the stock market data, and uses the isolated point detection method based on density and distance to analyze the obtained abnormal data to obtain its implicit useful information. However, due to the defects of traditional data mining algorithms in dealing with stock market anomalies containing uncertain factors, that is, the errors caused by other human factors, this paper introduces the roughening entropy of the uncertainty data and applies its theory to the field of data mining, a data mining algorithm based on rough entropy in the US stock market anomaly is designed. Finally, the empirical analysis of the algorithm is carried out. The experimental results show that the data mining algorithm based on rough entropy proposed in this paper can effectively detect the abnormal fluctuation of time series in the stock market.
Subject
Artificial Intelligence,General Engineering,Statistics and Probability
Reference26 articles.
1. Wang J.H. , Wang F. , Huang G.J. , Current Status and Prospects of Data Mining Technology Research, Proceedings of the 6th Academic Exchange Conference of China Operations Research Society, (Vol. 2).
2. Chen P. , Feng X. , Mao X. , Reasonable Evaluation Model of Pediatric Disease Based on pharmacology and Data Mining, Investigación Clínica 60(5) (2019).
3. Application of Analysis of Isolated Points in Data Mining in Practice;Li;Network New Media Technology,2006
4. Influence of Ce addition on microstructure and mechanical properties of high pressure die cast AM50 magnesium alloy;Mert;Transactions of Nonferrous Metals Society of China,2013
5. Remediation of heavy metal contaminated soils: phytoremediation as a potentially promising clean-up technology;Marques;Critical Reviews in Environmental Science & Technology,2009
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