A topological based feature extraction method for the stock market
We proposed a topology-based method for pre-processed time series data extracted from stock market data. The topology features are extracted from data after denoising and normalization by using a version of weighted Vietoris-Rips complex. We compare the features from bullish, bearish and normal peri...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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AIMS Press
2023-07-01
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| Series: | Data Science in Finance and Economics |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/DSFE.2023013?viewType=HTML |
| _version_ | 1797657937633607680 |
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| author | Chen Chang Hongwei Lin |
| author_facet | Chen Chang Hongwei Lin |
| author_sort | Chen Chang |
| collection | DOAJ |
| description | We proposed a topology-based method for pre-processed time series data extracted from stock market data. The topology features are extracted from data after denoising and normalization by using a version of weighted Vietoris-Rips complex. We compare the features from bullish, bearish and normal periods of the Chinese stock market and found significant differences between the features extracted from the groups. Based on the previous research mentioned in the context, we proposed a topology-based stock market index which has the ability to distinguish different stages of the stock market and forewarn stock market crashes. |
| first_indexed | 2024-03-11T17:51:45Z |
| format | Article |
| id | doaj.art-349d98c2097f41d89cc33a0361623622 |
| institution | Directory Open Access Journal |
| issn | 2769-2140 |
| language | English |
| last_indexed | 2024-03-11T17:51:45Z |
| publishDate | 2023-07-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Data Science in Finance and Economics |
| spelling | doaj.art-349d98c2097f41d89cc33a03616236222023-10-18T02:45:50ZengAIMS PressData Science in Finance and Economics2769-21402023-07-013320822910.3934/DSFE.2023013A topological based feature extraction method for the stock marketChen Chang 0Hongwei Lin11. Polytechnic Institute, Zhejiang University, China2. School of Mathematical Science, Zhejiang University, ChinaWe proposed a topology-based method for pre-processed time series data extracted from stock market data. The topology features are extracted from data after denoising and normalization by using a version of weighted Vietoris-Rips complex. We compare the features from bullish, bearish and normal periods of the Chinese stock market and found significant differences between the features extracted from the groups. Based on the previous research mentioned in the context, we proposed a topology-based stock market index which has the ability to distinguish different stages of the stock market and forewarn stock market crashes.https://www.aimspress.com/article/doi/10.3934/DSFE.2023013?viewType=HTMLtopological data analysisstock marketfeature extraction |
| spellingShingle | Chen Chang Hongwei Lin A topological based feature extraction method for the stock market Data Science in Finance and Economics topological data analysis stock market feature extraction |
| title | A topological based feature extraction method for the stock market |
| title_full | A topological based feature extraction method for the stock market |
| title_fullStr | A topological based feature extraction method for the stock market |
| title_full_unstemmed | A topological based feature extraction method for the stock market |
| title_short | A topological based feature extraction method for the stock market |
| title_sort | topological based feature extraction method for the stock market |
| topic | topological data analysis stock market feature extraction |
| url | https://www.aimspress.com/article/doi/10.3934/DSFE.2023013?viewType=HTML |
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