This #china Wuhan University study proposes a Financial Event Evolution Knowledge Graph (FEEKG) to identify key risk sources by event association and clarify the path of #riskevents. The FEEKG has a multi-layer structure of "entity-event-risk" and includes a subgraph of about 112,000 entities and 78,500 relationships, an event evolution subgraph, and a dynamic evolution probability subgraph of topic risk events and risk types. The study analyzes the characters and rules of entity correlation, event evolution, and #risktransmission based on FEEKG and provides a new perspective for enterprises and #financialinstitutions to find the root of risks and formulate an effective #riskmanagement decision in time.
top of page
Rechercher
Posts récents
Voir tout“As analysts are primary recipients of these reports, we investigate whether and how analyst forecast properties have changed following...
00
This study proposes a new method for detecting insider trading. The method combines principal component analysis (PCA) with random forest...
00
Cyber risk classifications often fail in out-of-sample forecasting despite their in-sample fit. Dynamic, impact-based classifiers...
30
bottom of page
Comments