Spatial Dependence and Data-Driven Networks of International Banks /
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 selec...
| প্রধান লেখক: | |
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| অন্যান্য লেখক: | |
| বিন্যাস: | পত্রিকা |
| ভাষা: | English |
| প্রকাশিত: |
Washington, D.C. :
International Monetary Fund,
2016.
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| মালা: | IMF Working Papers; Working Paper ;
No. 2016/184 |
| অনলাইন ব্যবহার করুন: | Full text available on IMF |
| সংক্ষিপ্ত: | 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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| উপাদানের বিবরণ: | <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required |
| দৈহিক বর্ননা: | 1 online resource (34 pages) |
| বিন্যাস: | Mode of access: Internet |
| আইএসএসএন: | 1018-5941 |
| প্রবেশাধিকার: | Electronic access restricted to authorized BRAC University faculty, staff and students |