Finding hidden links: Projection networks
Preface
Acknowledgements
An introduction to financial networks
Creating and describing networks
Identifying important nodes: Centrality metrics
Uncovering latent structure: Clustering and community detection
Finding hidden links: Projection networks
Estimating unknown links: Network reconstruction
Fast insights: Visualising networks
Financial cartography: Network layouts
Brass tacks: Complexity reduction
Financial stability and systemic risk
Design and simulation of financial market infrastructures
Monitoring and stress testing financial market infrastructures
Financial crime and conduct risk
Financial markets
References
A projection network is a particular type of network created from a bipartite network. A bipartite network, first introduced in Chapter 2, is one in which nodes can be categorised into two groups or partitions such that links only exist between the groups and never within either group. Examples of bipartite networks that have been analysed in the literature include: films and actors, where a link exists between an actor and a film they were in (see Newman, Strogatz and Watts, 2001; Tumminello et al, 2011); scientific papers and their authors (see Newman, 2001(a, b); Barabási et al, 2002); human genes and diseases (Goh et al, 2007); and the shareholder structure in Chinese companies (Pan et al, 2018). In finance, the two groups of nodes might represent investors and companies, with links representing investments: investors only invest in companies, so links only exist between the two groups. The corresponding projection network consists only of investors, and links exist between investors that invest in at least one common company (or, alternatively, the projection network could exist only of companies, in which case links would exist between companies that share at least one
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