Journal article
Research on Data Mining and Investment Recommendation of Individual Users Based on Financial Time Series Analysis
INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING, v 16(2)
Apr 2020
Abstract
With the continuous development of financial information technology, traditional data mining technology cannot effectively deal with large-scale user data sets, nor is it suitable to actively discover various potential rules from a large number of data and predict future trends. Time series are the specific values of statistical indicators on different time scales. Data sequences arranged in chronological order exist in our lives and scientific research. Financial time series is a special kind of time series, which has the commonness of time series, chaos, non-stationary and non-linear characteristics. Financial time series analysis judges the future trend of change through the analysis of historical time series. Through in-depth analysis of massive financial data, mining its potential valuable information, it can be used for individual or financial institutions in various financial activities, such as investment decision-making, market forecasting, risk management, customer requirement analysis provides scientific evidence.
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Details
- Title
- Research on Data Mining and Investment Recommendation of Individual Users Based on Financial Time Series Analysis
- Publication Details
- INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING, v 16(2)
- Publisher
- IGI GLOBAL; HERSHEY
- Number of pages
- 0
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Drexel University
- Web of Science ID
- WOS:000510434200006
- Scopus ID
- 2-s2.0-85083578900
- Other Identifier
- 991021860769904721
InCites Highlights
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- Web of Science research areas
- Computer Science, Software Engineering