Please wait a minute...
Data Analysis and Knowledge Discovery  2023, Vol. 7 Issue (8): 78-94    DOI: 10.11925/infotech.2096-3467.2022.1152
Current Issue | Archive | Adv Search |
Modelling and Representation of Risk Event Evolution in Financial Field
Liu Zhenghao1,2,3(),Zhang Zhijian1,2,3,Chen Shuaipu1,2,Zeng Xi1
1School of Information Management, Wuhan University, Wuhan 430072, China
2Institute of Big Data, Wuhan University, Wuhan 430072, China
3Center for Studies of Information Resources, Wuhan University, Wuhan 430072, China
Download: PDF (5211 KB)   HTML ( 14
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] This paper addresses the issues of insufficient consideration of evolution patterns and factors in the analysis of financial events evolution. It focuses on modeling and representing the evolution of financial risk events based on event correlation and evolution. This study also constructs an event evolution graph. [Methods] We combined event evolution pattern modeling to analyze evolution conditions and proposed a graph generation algorithm for event evolution based on the nearest neighbor query Ball-Tree. This algorithm enables an adequate representation of financial risk events. [Results] We analyzed the risk events related to “Evergrande Group”. We found that when the strength of event evolution relationships was set at 0.2, 489 correct evolutionary relationships were detected among all 629 event pairs with evolutionary relationships, with an accuracy rate of 77.74%. [Limitations] Due to the space limitation, identifying financial risk events was not extensively described, and the dynamic updating of financial events was not considered. [Conclusions] The proposed modeling approach can analyze various potential association relationships among events, recreate significant scenarios during the development of risk events, and provide effective technical support for understanding potential evolution paths and patterns.

Key wordsEvent Evolution Analysis      Financial Risk Events      Evolution Model      Event Association      Event Evolution Graph     
Received: 04 November 2022      Published: 28 March 2023
ZTFLH:  TP391  
  F832  
Fund:National Natural Science Foundation of China(91646206);Scientific and Technological Innovation 2030 - “New Generation Artificial Intelligence” Major Project(2020AAA0108505)
Corresponding Authors: Liu Zhenghao,ORCID:0000-0003-1356-7017,E-mail:zhenghaoliu@whu.edu.cn。   

Cite this article:

Liu Zhenghao, Zhang Zhijian, Chen Shuaipu, Zeng Xi. Modelling and Representation of Risk Event Evolution in Financial Field. Data Analysis and Knowledge Discovery, 2023, 7(8): 78-94.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2022.1152     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2023/V7/I8/78

Evolution Stage and Risk Evolution Cycle of Financial Risk Events
“One-to-One” Evolution Process of Baoshang Bank Bankruptcy Events
Evolution Process of “One-to-More” Branch of Crude Oil Treasure Event of Bank of China
Evolution Pattern of “More-to-One” Convergence in Four Circuit Breaker Events of US Stocks
“More-to-More” Evolution Mode of Evergrande Bankruptcy Event
Subgraph Construction Process of Financial Risk Event Evolution
ID 企业/金融机构名称 所属行业 涉及的一级风险类型 包含事件数
1 中国恒大 房地产 财务风险,运营风险 252
2 民生银行 银行 运营风险,财务风险,法律风险 227
3 蚂蚁集团 互联网 战略风险,法律风险 217
4 中金公司 资本市场服务 运营风险,法律风险 200
5 万科A 房地产 运营风险,财务风险 184
6 中信证券 证券 法律风险 162
7 方正证券 证券 运营风险,法律风险 149
8 安信信托 信托 财务风险,法律风险 139
9 坚瑞沃能 新能源汽车 财务风险 111
10 权健 自然医学产业 法律风险 109
11 精功集团 结构建筑、装备制造等 财务风险 97
12 中金公司 证券 运营风险,法律风险 80
13 神州优车 生活服务 运营风险,财务风险 73
14 海航集团 航空 战略风险,财务风险 71
15 康美药业 中药饮片 财务风险 61
16 贵州茅台 白酒 战略风险,市场风险,运营风险 60
17 国海证券 证券 法律风险 54
18 永泰能源 综合能源 运营风险 49
19 包商银行 银行 运营风险 48
20 贵人鸟 纺织服饰 战略风险,运营风险 37
Representative Enterprises and Financial Institutions with Risk Events
排序 实体 亲密度 排序 实体 亲密度
1 恒大财富 1.442 695 6 龙光地产 0.721 347
2 鼎尖软件 1.442 695 7 云峰资金 0.716 535
3 乐视 0.910 239 8 红杉资本 0.716 535
4 Koenigsegg 0.721 347 9 碧桂园 0.716 535
5 绿地香港 0.721 347 10 万科 0.716 535
Top10 Entities of Intimacy Based on Link Prediction Algorithm
E a E b T a T b
中国恒大7月3日以2.865亿港元回购1410万股股份。 中国恒大7月5日耗资8.35亿港元回购
4035.1万股,为连续第三日回购股份。
2018-7-3 2018-7-5 γ E E C C 1
T C D I 0.819
E I C S 1
S i m 0.798
E V I 0.046
E v o _ s c o r e 0.865
贾跃亭发难背后:死也不会放手FF控制权。 【争夺乐视汽车控制权:恒大方面未派时守明出任董事】恒大健康步步紧逼下,贾跃亭还是一直友好交涉,试图通过谈判解决,但一直效果不佳,没办法之后只有进行仲裁。 2018-10-7 2018-10-8 γ E E C C 0.800
T C D I 0.905
E I C S 0.600
S i m 0.440
E V I 0.149
E v o _ s c o r e 0.493
中国恒大在港交所公告,目前建议重组交易之工作尚在有序进行中,凯隆置业及恒大地产于2018年12月28日与深投控及深深房签订对合作协议之进一步补充协议。 中国恒大集团发布有关与深深房的建议重组合作协议之进一步公告:凯隆置业及恒大地产于3月13日与深投控及深深房签订对合作协议之进一步补充协议,将合作协议内之排他性及协议有效期从3月31日进一步延申至12月31日。 2018-12-28 2019-3-13 γ E E C C 1
T C D I 0.006
E I C S 0.500
S i m 0.711
E V I 3.46× 10 - 7
E v o _ s c o r e 0.641
2021年8月19日,央行、银保监局相关部门负责同志约谈恒大集团高管,要求努力保持经营稳定,积极化解债务风险,维护房地产和金融稳定。 2021年8月20日凌晨,恒大发布声明称恒大集团接受了人民银行、银保监会的约谈。恒大集团将全面落实约谈要求,……,以最大决心、最大力度保持公司经营稳定,化解债务风险,维护房地产市场和金融稳定。 2021-8-19 2021-8-20 γ E E C C 1
T C D I 0.905
E I C S 0.750
S i m 0.424
E V I 0.002
E v o _ s c o r e 0.533
据港交所披露文件:在完成出售事项后,10月18日,中国恒大董事局主席许家印在盛京银行的持股比例从49.59%下降至19.85%。 据港交所文件:11月12日,中国恒大对恒大汽车的持股比例从66.77%降至64.98%。 2021-11-16 2021-12-8 γ E E C C 1
T C D I 0.301
E I C S 0.300
S i m 0.670
E V I 0.367
E v o _ s c o r e 0.547
中国恒大公告,考虑到本集团目前面临的经营上和财务上的挑战,本公司董事会决议设立中国恒大集团风险化解委员会。其中,许家印任风险化解委员会主席。 中国恒大港交所公告,针对本集团目前面临的风险,中国恒大集团风险化解委员会正调动广泛资源,并将积极与债权人保持沟通,努力化解集团风险,维护各方合法权益。 2021-12-6 2021-12-22 γ E E C C 1
T C D I 0.202
E I C S 0.800
S i m 0.639
E V I 0.001
E v o _ s c o r e 0.692
Related Indicators of Risk Events of Evergrande Group (Part)
Real Evolution Graph of Evergrande Group Risk Events Based on Manual Labeling
Precision and Recall under Different Evolutionary Strength Thresholds
演化分支 时间跨度 核心事件 事件数
1 2018.10.22-2021.9.17 恒大销售额下降 58
2 2018.8.28-2020.9.24 恒大并购重组 6
3 2020.9.24-2021.12.8 恒大股权变更 8
4 2021.6.1-2021.12.6 恒大债务危机 79
5 2020.8.20-2021.9.18 恒大增发/兑付票据 16
6 2018.7.3-2020.6.1 恒大回购 14
Evolutionary Branches of Risk Events of Evergrande Group
Risk Event Evolution Graph of Evergrande Group When λ=0.2
[1] 中国互联网络信息中心. 第 50 次《中国互联网络发展状况统计报告》[EB/OL]. [2022-11-01]. https://www3.cnnic.cn/n4/2022/0914/c88-10226.html.
[1] (China Internet Network Information Center. The 50th Statistical Report on China’s Internet Development[EB/OL]. [2022-11-01]. https://www3.cnnic.cn/n4/2022/0914/c88-10226.html.)
[2] Yang C C, Shi X D, Wei C P. Discovering Event Evolution Graphs from News Corpora[J]. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 2009, 39(4): 850-863.
doi: 10.1109/TSMCA.2009.2015885
[3] 宣俊宇. 基于关键词关联语义链网络的Web事件演化研究[D]. 上海: 上海大学, 2016.
[3] (Xuan Junyu. Research on the Evolution of Web Events Based on Keyword Association Semantic Chain Network[D]. Shanghai: Shanghai University, 2016.)
[4] Zhou P P, Wu B, Cao Z. EMMBTT: A Novel Event Evolution Model Based on TFxIEF and TDC in Tracking News Streams[C]// Proceedings of 2nd International Conference on Data Science in Cyberspace. IEEE, 2017: 102-107.
[5] Mu L, Jin P Q, Zheng L Z, et al. EventSys:Tracking Event Evolution on Microblogging Platforms[C]// Proceedings of International Conference on Database Systems for Advanced Applications. 2018: 797-801.
[6] Xu N, Tang X J. Evolution Analysis of Societal Risk Events by Risk Maps[J]. Journal of Systems Science and Systems Engineering, 2020, 29(4): 454-467.
doi: 10.1007/s11518-020-5458-0
[7] 陈玉博. 面向非结构化文本的事件抽取关键技术研究[D]. 北京: 中国科学院大学, 2017.
[7] (Chen Yubo. Research on Key Technologies of Event Extraction for Unstructured Text[D]. Beijing: University of Chinese Academy of Sciences, 2017.)
[8] Wang X R, McCallum A. Topics over Time: A Non-Markov Continuous-Time Model of Topical Trends[C]// Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2006: 424-433.
[9] Makkonen J. Investigations on Event Evolution on TDT[C]// Proceedings of the HLT-NAACL 2003 Student Research Workshop. 2003: 43-48.
[10] Nallapati R, Feng A, Peng F C, et al. Event Threading Within News Topics[C]// Proceedings of the 13th ACM International Conference on Information and Knowledge Management. 2004: 446-453.
[11] Fiscus J G, Doddington G R. Topic Detection and Tracking Evaluation Overview[A] //Topic Detection and Tracking[M]. Boston, MA: Springer US, 2002: 17-31.
[12] Yang Y M, Pierce T, Carbonell J. A Study of Retrospective and On-line Event Detection[C]// Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. 1998:28-36.
[13] Ding C L, Wei C F, Gu T T, et al. Study on Propagation Model of Network Public Opinion Based on Fuzzy Cellular Automata[C]// Proceedings of the 2nd International Conference on Measurement, Information and Control. 2014: 1009-1013.
[14] 张晓艳, 王挺, 陈火旺. 基于多向量和实体模糊匹配的话题关联识别[J]. 中文信息学报, 2008, 22(1): 9-14.
[14] (Zhang Xiaoyan, Wang Ting, Chen Huowang. Story Link Detection Based on Multi-Vector Model and Entity Fuzzy Matching[J]. Journal of Chinese Information Processing, 2008, 22(1): 9-14.)
[15] Yang C C, Shi X D, Wei C P. Tracing the Event Evolution of Terror Attacks from On-Line News[C]// Proceedings of IEEE International Conference on Intelligence and Security Informatics. 2006: 343-354.
[16] 曾子明, 黄城莺. 基于BP神经网络的突发传染病舆情热度趋势预测模型研究[J]. 现代情报, 2018, 38(5): 37-44.
doi: 10.3969/j.issn.1008-0821.2018.05.006
[16] (Zeng Ziming, Huang Chengying. Research on Public Opinion Heat Trend Prediction Model of Emergent Infectious Diseases Based on BP Neural Network[J]. Modern Information, 2018, 38(5): 37-44.)
doi: 10.3969/j.issn.1008-0821.2018.05.006
[17] Wen A Z, Lin W W, Ma Y C, et al. News Event Evolution Model Based on the Reading Willingness and Modified TF-IDF Formula[J]. Journal of High Speed Networks, 2017, 23(1): 33-47.
doi: 10.3233/JHS-170555
[18] Yang Y Y, Wei Z Y, Chen Q, et al. Using External Knowledge for Financial Event Prediction Based on Graph Neural Networks[C]// Proceedings of the 28th ACM International Conference on Information and Knowledge Management. 2019: 2161-2164.
[19] 周磊. 社交网络事件演化分析方法研究[D]. 成都: 电子科技大学, 2019.
[19] (Zhou Lei. Research on the Analysis Method of Social Network Event Evolution[D]. Chengdu: University of Electronic Science and Technology of China, 2019.)
[20] 张辉, 李国辉, 孙博良, 等. 一种新闻事件演化建模方法[J]. 国防科技大学学报, 2013, 35(4): 166-170.
[20] (Zhang Hui, Li Guohui, Sun Boliang, et al. Modeling News Event Evolution[J]. Journal of National University of Defense Technology, 2013, 35(4): 166-170.)
[21] 单晓红, 庞世红, 刘晓燕, 等. 基于事理图谱的网络舆情演化路径分析——以医疗舆情为例[J]. 情报理论与实践, 2019, 42(9): 99-103, 85.
doi: 10.16353/j.cnki.1000.7490.2019.09.017
[21] (Shan Xiaohong, Pang Shihong, Liu Xiaoyan, et al. Analysis on the Evolution Path of Internet Public Opinions Based on the Event Evolution Graph: Taking Medical Public Opinions as an Example[J]. Information Studies:Theory& Application, 2019, 42(9): 99-103, 85.)
doi: 10.16353/j.cnki.1000.7490.2019.09.017
[22] Li Z, Ding X, Liu T. Constructing Narrative Event Evolutionary Graph for Script Event Prediction[OL]. arXiv Preprint, arXiv:1805.05081.
[23] 王军平, 张文生, 王勇飞, 等. 面向大数据领域的事理认知图谱构建与推断分析[J]. 中国科学: 信息科学, 2020, 50(7): 988-1002.
[23] Wang Junping, Zhang Wensheng, Wang Yongfei, et al. Constructing and Inferring Event Logic Cognitive Graph in the Field of Big Data[J]. Scientia Sinica (Informationis), 2020, 50(7): 988-1002.)
[24] 于强, 徐志栋, 时斌, 等. 基于事理知识图谱的舆情推演方法[J]. 计算机系统应用, 2021, 30(4): 25-31.
[24] (Yu Qiang, Xu Zhidong, Shi Bin, et al. Public Opinion Deduction Based on Event Logic Graph[J]. Computer Systems & Applications, 2021, 30(4): 25-31.)
[25] 张世晓. 金融舆情演化机理与监测管理机制研究[M]. 武汉: 湖北人民出版社, 2014.
[25] (Zhang Shixiao. Research on Evolution Mechanism and Monitoring Management Mechanism of Financial Public Opinion[M]. Wuhan: Hubei People’s Press, 2014.)
[26] 董志学. 互联网金融舆情风险防控理论研究[J]. 中国集体经济, 2017(16): 57-61.
[26] (Dong Zhixue. Theoretical Research on Risk Prevention and Control of Internet Financial Public Opinion[J]. China Collective Economy, 2017(16): 57-61.)
[27] Adi A, Botzer D, Nechushtai G, et al. Complex Event Processing for Financial Services[C]// Proceedings of 2006 IEEE Services Computing Workshops. 2006: 7-12.
[28] 王雪秋. 突发金融舆情事件信息传播规律与对策研究[J]. 情报科学, 2021, 39(4): 54-61.
[28] (Wang Xueqiu. Research on Information Dissemination Law and Countermeasures of Financial Public Opinion Emergencies[J]. Information Science, 2021, 39(4): 54-61.)
[29] 厉臣璐. 基于论坛用户情感分析的金融网络舆情演化研究[D]. 武汉: 武汉大学, 2019.
[29] (Li Chenlu. Research on the Evolution of Financial Online Public Opinion Based on the Emotion Analysis of Forum Users[D]. Wuhan: Wuhan University, 2019.)
[30] García F J P. Financial Risk Management: Identification, Measurement and Management[M]. Berlin: 2017.
[31] 安璐, 李倩. 基于热点主题识别的突发事件次生衍生事件探测[J]. 情报资料工作, 2020, 41(6): 26-35.
[31] (An Lu, Li Qian. A Probe into Secondary Derived Events of Emergencies Based on Hot Topic Recognition[J]. Information and Documentation Services, 2020, 41(6): 26-35.)
[32] 杨鑫源, 郑家启, 任泽华. 美国熔断机制连续触发的原因及对策分析[J]. 中国商论, 2020(9):13-14.
[32] (Yang Xinyuan, Zheng Jiaqi, Ren Zehua. Causes and Countermeasures of Continuous Triggering of Fuse Mechanism in the United States[J]. China Business & Trade, 2020(9): 13-14.)
[33] 张敬伟. 疫情“灰犀牛”熔断美股释放的市场警训[N]. 中国审计报, 2020-03-16( 003).
[33] (Zhang Jingwei. Market Warning on the Release of US Stocks due to the Epidemic “Grey Rhinoceros”[N]. China Audit Journal, 2020-03-16( 003).)
[34] 夏立新, 毕崇武, 梅潇, 等. 基于事件链的网络舆情事件演化研究[J]. 情报理论与实践, 2020, 43(5): 123-130.
[34] (Xia Lixin, Bi Chongwu, Mei Xiao, et al. Research on Evolution of Public Opinion in the Network Based on Chain of Events[J]. Information Studies:Theory & Application, 2020, 43(5): 123-130.)
[35] 冯德育, 王紫. 演化金融学的创新与展望[J]. 学习与探索, 2012(7): 112-115.
[35] (Feng Deyu, Wang Zi. Innovation and Prospect of Evolutionary Finance[J]. Study & Exploration, 2012(7): 112-115.)
[36] Wen A Z, Lin W W, Ma Y C, et al. News Event Evolution Model Based on the Reading Willingness and Modified TF-IDF Formula[J]. Journal of High Speed Networks, 2017, 23(1): 33-47.
doi: 10.3233/JHS-170555
[37] Adamic L A, Adar E. Friends and Neighbors on the Web[J]. Social Networks, 2003, 25(3): 211-230.
doi: 10.1016/S0378-8733(03)00009-1
[38] 季冬. 基于事件图谱的新闻事件演化分析[D]. 南京: 东南大学, 2020.
[38] (Ji Dong. Evolution Analysis of News Events Based on Event Map[D]. Nanjing: Southeast University, 2020.)
[1] He Yumei, Qi Jiayin, Liu Huili. The Study of Local-world Network Evolution Model Based on Microblog[J]. 现代图书情报技术, 2014, 30(5): 66-73.
[2] Xue Jianwu, Gao Junping. Research on Knowledge Evolution Model of Intelligent IETM[J]. 现代图书情报技术, 2012, 28(1): 27-33.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn