In the wake of the ongoing global financial crisis, interdependencies among banks have come into focus in trying to assess systemic risk. To date, such analysis has largely been based on numerical data. By contrast, this study attempts to gain further insight into bank interconnections by tapping into financial discussion. Co-occurrences of bank names are turned into a network, which can be visualized and analyzed quantitatively, in order to illustrate characteristics of individual banks and the network as a whole. The approach also highlights temporal dynamics of the network, e.g. how global shifts in network structure coincide with severe crisis episodes. The usage of textual data holds an additional advantage in the possibility of gaining a more qualitative understanding of an observed interrelation, through its context. We illustrate our approach using a case study on Finnish banks and financial institutions, based on discussion in 3.9M online posts spanning 9 years.
From text to bank interrelation maps
Published 2013 in IEEE Conference on Computational Intelligence for Financial Engineering & Economics
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- Publication year
2013
- Venue
IEEE Conference on Computational Intelligence for Financial Engineering & Economics
- Publication date
2013-06-17
- Fields of study
Physics, Business, Economics, Computer Science
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Semantic Scholar
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