Stability of China’s Stock Market: Measure and Forecast by Ricci Curvature on Network
The systemic stability of a stock market is one of the core issues in the financial field. The market can be regarded as a complex network whose nodes are stocks connected by edges that signify their correlation strength. Since the market is a strongly nonlinear system, it is difficult to measure th...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2023/2361405 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849408205008928768 |
|---|---|
| author | Xinyu Wang Liang Zhao Ning Zhang Liu Feng Haibo Lin |
| author_facet | Xinyu Wang Liang Zhao Ning Zhang Liu Feng Haibo Lin |
| author_sort | Xinyu Wang |
| collection | DOAJ |
| description | The systemic stability of a stock market is one of the core issues in the financial field. The market can be regarded as a complex network whose nodes are stocks connected by edges that signify their correlation strength. Since the market is a strongly nonlinear system, it is difficult to measure the macroscopic stability and depict market fluctuations in time. In this article, we use a geometric measure derived from discrete Ricci curvature to capture the higher-order nonlinear architecture of financial networks. In order to confirm the effectiveness of our method, we use it to analyze the CSI 300 constituents of China’s stock market from 2005 to 2020 and the systemic stability of the market is quantified through the network’s Ricci-type curvatures. Furthermore, we use a hybrid model to analyze the curvature time series and predict the future trends of the market accurately. As far as we know, this is the first article to apply Ricci curvature to forecast the systemic stability of China’s stock market, and our results show that Ricci curvature has good explanatory power for the market stability and can be a good indicator to judge the future risk and volatility of China’s stock market. |
| format | Article |
| id | doaj-art-39f6c64b02da4d0983ececd9c2577683 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-39f6c64b02da4d0983ececd9c25776832025-08-20T03:35:51ZengWileyComplexity1099-05262023-01-01202310.1155/2023/2361405Stability of China’s Stock Market: Measure and Forecast by Ricci Curvature on NetworkXinyu Wang0Liang Zhao1Ning Zhang2Liu Feng3Haibo Lin4School of ScienceSchool of Mathematical SciencesSchool of FinanceSchool of FinanceSchool of ScienceThe systemic stability of a stock market is one of the core issues in the financial field. The market can be regarded as a complex network whose nodes are stocks connected by edges that signify their correlation strength. Since the market is a strongly nonlinear system, it is difficult to measure the macroscopic stability and depict market fluctuations in time. In this article, we use a geometric measure derived from discrete Ricci curvature to capture the higher-order nonlinear architecture of financial networks. In order to confirm the effectiveness of our method, we use it to analyze the CSI 300 constituents of China’s stock market from 2005 to 2020 and the systemic stability of the market is quantified through the network’s Ricci-type curvatures. Furthermore, we use a hybrid model to analyze the curvature time series and predict the future trends of the market accurately. As far as we know, this is the first article to apply Ricci curvature to forecast the systemic stability of China’s stock market, and our results show that Ricci curvature has good explanatory power for the market stability and can be a good indicator to judge the future risk and volatility of China’s stock market.http://dx.doi.org/10.1155/2023/2361405 |
| spellingShingle | Xinyu Wang Liang Zhao Ning Zhang Liu Feng Haibo Lin Stability of China’s Stock Market: Measure and Forecast by Ricci Curvature on Network Complexity |
| title | Stability of China’s Stock Market: Measure and Forecast by Ricci Curvature on Network |
| title_full | Stability of China’s Stock Market: Measure and Forecast by Ricci Curvature on Network |
| title_fullStr | Stability of China’s Stock Market: Measure and Forecast by Ricci Curvature on Network |
| title_full_unstemmed | Stability of China’s Stock Market: Measure and Forecast by Ricci Curvature on Network |
| title_short | Stability of China’s Stock Market: Measure and Forecast by Ricci Curvature on Network |
| title_sort | stability of china s stock market measure and forecast by ricci curvature on network |
| url | http://dx.doi.org/10.1155/2023/2361405 |
| work_keys_str_mv | AT xinyuwang stabilityofchinasstockmarketmeasureandforecastbyriccicurvatureonnetwork AT liangzhao stabilityofchinasstockmarketmeasureandforecastbyriccicurvatureonnetwork AT ningzhang stabilityofchinasstockmarketmeasureandforecastbyriccicurvatureonnetwork AT liufeng stabilityofchinasstockmarketmeasureandforecastbyriccicurvatureonnetwork AT haibolin stabilityofchinasstockmarketmeasureandforecastbyriccicurvatureonnetwork |