Modelling and Representation of Risk Event Evolution in Financial Field

被引：0
|
作者：
Liu Z. [1 ,2 ,3 ]
Zhang Z. [1 ,2 ,3 ]
Chen S. [1 ,2 ]
Zeng X. [1 ]
机构：
[1] School of Information Management, Wuhan University, Wuhan
[2] Institute of Big Data, Wuhan University, Wuhan
[3] Center for Studies of Information Resources, Wuhan University, Wuhan
来源：
Data Analysis and Knowledge Discovery | 2023年 / 7卷 / 08期
基金：
中国国家自然科学基金;
关键词：
Event Association; Event Evolution Analysis; Event Evolution Graph; Evolution Model; Financial Risk Events;
D O I：
10.11925/infotech.2096-3467.2022.1152
中图分类号：
学科分类号：
摘要：
[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. © 2023 Data Analysis and Knowledge Discovery. All rights reserved.
引用
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页码：78 / 94
页数：16
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