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|c 5.00 USD
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|z 9781475536706
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|a 1018-5941
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|a BD-DhAAL
|c BD-DhAAL
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|a Craig, Ben.
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|a Spatial Dependence and Data-Driven Networks of International Banks /
|c Ben Craig, Martin Saldias.
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|a Washington, D.C. :
|b International Monetary Fund,
|c 2016.
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|a 1 online resource (34 pages)
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|a IMF Working Papers
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|a <strong>Off-Campus Access:</strong> No User ID or Password Required
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|a <strong>On-Campus Access:</strong> No User ID or Password Required
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|a Electronic access restricted to authorized BRAC University faculty, staff and students
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|a This paper computes data-driven correlation networks based on the stock returns of international banks and conducts a comprehensive analysis of their topological properties. We first apply spatial-dependence methods to filter the effects of strong common factors and a thresholding procedure to select the significant bilateral correlations. The analysis of topological characteristics of the resulting correlation networks shows many common features that have been documented in the recent literature but were obtained with private information on banks' exposures, including rich and hierarchical structures, based on but not limited to geographical proximity, small world features, regional homophily, and a core-periphery structure.
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|a Mode of access: Internet
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|a Saldias, Martin.
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|a IMF Working Papers; Working Paper ;
|v No. 2016/184
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| 856 |
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|z Full text available on IMF
|u http://elibrary.imf.org/view/journals/001/2016/184/001.2016.issue-184-en.xml
|z IMF e-Library
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