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Credit Default Swaps networks and systemic risk

Overview of attention for article published in Scientific Reports, November 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)

Mentioned by

29 tweeters
1 Google+ user

Readers on

74 Mendeley
Credit Default Swaps networks and systemic risk
Published in
Scientific Reports, November 2014
DOI 10.1038/srep06822
Pubmed ID

Michelangelo Puliga, Guido Caldarelli, Stefano Battiston


Credit Default Swaps (CDS) spreads should reflect default risk of the underlying corporate debt. Actually, it has been recognized that CDS spread time series did not anticipate but only followed the increasing risk of default before the financial crisis. In principle, the network of correlations among CDS spread time series could at least display some form of structural change to be used as an early warning of systemic risk. Here we study a set of 176 CDS time series of financial institutions from 2002 to 2011. Networks are constructed in various ways, some of which display structural change at the onset of the credit crisis of 2008, but never before. By taking these networks as a proxy of interdependencies among financial institutions, we run stress-test based on Group DebtRank. Systemic risk before 2008 increases only when incorporating a macroeconomic indicator reflecting the potential losses of financial assets associated with house prices in the US. This approach indicates a promising way to detect systemic instabilities.

Twitter Demographics

The data shown below were collected from the profiles of 29 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 3 4%
Belgium 2 3%
Netherlands 1 1%
United Kingdom 1 1%
Mexico 1 1%
Switzerland 1 1%
Unknown 65 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 31%
Researcher 17 23%
Student > Master 9 12%
Student > Doctoral Student 4 5%
Other 4 5%
Other 14 19%
Unknown 3 4%
Readers by discipline Count As %
Economics, Econometrics and Finance 30 41%
Physics and Astronomy 9 12%
Mathematics 6 8%
Business, Management and Accounting 5 7%
Computer Science 5 7%
Other 12 16%
Unknown 7 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 November 2014.
All research outputs
of 15,383,183 outputs
Outputs from Scientific Reports
of 79,601 outputs
Outputs of similar age
of 234,611 outputs
Outputs of similar age from Scientific Reports
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Altmetric has tracked 15,383,183 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 79,601 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.9. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 234,611 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them