Interest rates hierarchical structure
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DOI: 10.1016/j.physa.2005.02.063
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References listed on IDEAS
- Pagan, A.R. & Hall, A.D. & Martin, V., 1995. "Modelling the Term Structure," Papers 284, Australian National University - Department of Economics.
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Cited by:
- Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
- Nicolo Musmeci & Tomaso Aste & Tiziana Di Matteo, 2014. "Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methods," Papers 1406.0496, arXiv.org, revised Jan 2015.
- Kanevski, M. & Maignan, M. & Pozdnoukhov, A. & Timonin, V., 2008. "Interest rates mapping," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3897-3903.
- Xie Chi & Zhou Yingying & Wang Gangjin & Yan Xinguo, 2017. "Investigating the Disparities of China’s Insurance Market Based on Minimum Spanning Tree from the Viewpoint of Geography and Enterprise," Journal of Systems Science and Information, De Gruyter, vol. 5(3), pages 216-228, June.
- Pang, Raymond Ka-Kay & Granados, Oscar M. & Chhajer, Harsh & Legara, Erika Fille T., 2021. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
- Tabak, Benjamin M. & Luduvice, André Victor D. & Cajueiro, Daniel O., 2011.
"Modeling default probabilities: The case of Brazil,"
Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(4), pages 513-534, October.
- Benjamin M. Tabak & Daniel O. Cajueiro & A. Luduvice, 2011. "Modeling Default Probabilities: the case of Brazil," Working Papers Series 232, Central Bank of Brazil, Research Department.
- Musmeci, Nicoló & Aste, Tomaso & Di Matteo, T., 2015. "Relation between financial market structure and the real economy: comparison between clustering methods," LSE Research Online Documents on Economics 61644, London School of Economics and Political Science, LSE Library.
- Aste, T. & Di Matteo, T., 2006. "Dynamical networks from correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 156-161.
- Sensoy, Ahmet & Tabak, Benjamin M., 2014.
"Dynamic spanning trees in stock market networks: The case of Asia-Pacific,"
Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 387-402.
- Ahmet Sensoy & Benjamin M. Tabak, 2014. "Dynamic spanning trees in stock market networks: The case of Asia-Pacific," Working Papers Series 351, Central Bank of Brazil, Research Department.
- Lee, Junghoon & Youn, Janghyuk & Chang, Woojin, 2012. "Intraday volatility and network topological properties in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1354-1360.
- Raymond Ka-Kay Pang & Oscar Granados & Harsh Chhajer & Erika Fille Legara, 2020. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Papers 2009.13390, arXiv.org, revised Feb 2021.
- Nicol'o Musmeci & Tomaso Aste & Tiziana Di Matteo, 2014. "Risk diversification: a study of persistence with a filtered correlation-network approach," Papers 1410.5621, arXiv.org.
- Nicoló Musmeci & Tomaso Aste & T Di Matteo, 2015. "Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methods," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-24, March.
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Keywords
Interest rates; Data clustering; Correlations; Econophysics;All these keywords.
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