News-induced Dynamic Networks for Market Signaling: Understanding Impact of News on Firm Equity Value

2020 ◽  
Author(s):  
Kun Chen ◽  
Xin Li ◽  
Peng Luo ◽  
J. Leon Zhao
Keyword(s):  
Dynamic Networks ◽  
Equity Value ◽  
Market Signaling

News-Induced Dynamic Networks for Market Signaling: Understanding the Impact of News on Firm Equity Value

2021 ◽  
Author(s):  
Kun Chen ◽  
Xin Li ◽  
Peng Luo ◽  
J. Leon Zhao
Keyword(s):  
Portfolio Management ◽  
Dynamic Networks ◽  
Equity Value ◽  
Research Opportunity ◽  
Automatic Methods ◽  
Rich Information ◽  
Business Events ◽  
Additional Value ◽  
The Impact ◽  
Market Signaling

Public news provides rich information about firm operations and market dynamics. Learning about firm interactions from news is commonly done by human investors but has not been realized by automatic methods, leading to a research opportunity in market signaling via dynamic firm relations. This study proposes a new text-mining approach to extract cobenefit/counter-benefit networks based on firms’ mutual or conflicting interests in business events. It reveals that the extracted dynamic networks provide additional value in predicting firm equity value over current adopted supply chain and coindustry networks, after controlling for market activities and other traditional indicators from news, such as volume, sentiment, and comentions. In practice, such cobenefit/counter-benefit networks provide good buy and sell signals, which enrich known indicators and support more complex trading strategies in investment and portfolio management. The analysis and visualization of the extracted cobenefit/counter-benefit networks are also useful in understanding the structure of the economy and assessing firm/industry changes in a timelier fashion.

Mathematics of networks

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Random Walks ◽  
Adjacency Matrix ◽  
Graph Partitioning ◽  
Dynamic Networks ◽  
Graph Laplacian ◽  
Network Visualization ◽  
Final Part ◽  
Bipartite Networks ◽  
Component Structure ◽  
Basic Properties

An introduction to the mathematical tools used in the study of networks. Topics discussed include: the adjacency matrix; weighted, directed, acyclic, and bipartite networks; multilayer and dynamic networks; trees; planar networks. Some basic properties of networks are then discussed, including degrees, density and sparsity, paths on networks, component structure, and connectivity and cut sets. The final part of the chapter focuses on the graph Laplacian and its applications to network visualization, graph partitioning, the theory of random walks, and other problems.

Routing in Large-scale Dynamic Networks

2020 ◽  
Vol 20 (4) ◽  
pp. 1-24
Author(s):  
Weichao Gao ◽  
James Nguyen ◽  
Yalong Wu ◽  
William G. Hatcher ◽  
Wei Yu
Keyword(s):  
Large Scale ◽  
Dynamic Networks
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