Comovements in government bond markets: A minimum spanning tree analysis

Gilmore, Claire G.; Lucey, Brian M.; Boscia, Marian W.

doi:10.1016/j.physa.2010.06.057

Cited by 60 publications

(48 citation statements)

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“…Most of these authors stress its usefulness for characterizing financial markets by means of identifying their underlying structure, taxonomy or hierarchy. For instance, such characterization of financial markets has allowed for (i) identifying different types of asset clusters (Naylor et al [5]; Mantegna [17]); (ii) finding assets' exposure to common risk factors (Marsh et al [24]; Mantegna [4]); detecting predominant assets (Naylor et al [5]); (iv) identifying central and peripheral issuers (Marsh et al [24]); and measuring financial integration (Gilmore et al [8]). Moreover, some authors have also emphasized its usefulness to overcome the empirical problem of noise in -historical -correlation matrices (Naylor et al [5]; Bonanno et al [12]).…”

Section: Analysis Of the Resulting Mstmentioning

confidence: 99%

“…After Mantegna several authors have followed a similar approach to extract the topology of foreign exchange markets (Naylor et al [5]); (Mizuno et al [6]), interest rates (Aste and Di Matteo [7]), government bonds (Gilmore et al [8]) commodities (Gilmore et al [9]) international trade (Maeng et al [10]) and stock markets (Kullmann et al [11]; Bonanno et al [12,13]; Eryigit and Eryigit [14]; Onnela et al [15]; Mantegna and Stanley [16]; Mantegna [17]). …”

Section: Correlation As a Measure Of Distancementioning

confidence: 99%

“…8 5 Let d (i,j) be the distance between points i and j, an Euclidean distance fulfills three axioms:…”

Section: Correlation As a Measure Of Distancementioning

confidence: 99%

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Extracting the sovereigns’ CDS market hierarchy: A correlation-filtering approach

León

Leiton

Pérez

2014

Physica A: Statistical Mechanics and its Applications

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h i g h l i g h t s• The hierarchical structure of sovereign CDS cross correlations is examined. • The importance of geographical and credit rating clustering is confirmed.• Eigenvector centrality agrees with sovereigns' positions in the minimal spanning tree. • The main regional sovereign benchmarks are identified.• The most (and least) financial contagion-prone sovereigns are identified. a b s t r a c tThis paper employs correlation-into-distance mapping techniques and a minimal spanning tree-based correlation-filtering methodology on 36 sovereign CDS spread time-series in order to identify the sovereigns' informational hierarchy. The resulting hierarchy (i) concurs with sovereigns' eigenvector centrality; (ii) confirms the importance of geographical and credit rating clustering; (iii) identifies Russia, Turkey and Brazil as regional benchmarks; (iv) reveals the idiosyncratic nature of Japan and United States; (v) confirms that a small set of common factors affects the system; (vi) suggests that lower-medium grade rated sovereigns are the most influential, but also the most prone to contagion; and (vii) suggests the existence of a ''Latin American common factor''.

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Section: Analysis Of the Resulting Mstmentioning

confidence: 99%

Section: Correlation As a Measure Of Distancementioning

confidence: 99%

See 1 more Smart Citation

Extracting the sovereigns’ CDS market hierarchy: A correlation-filtering approach

León

Leiton

Pérez

2014

Physica A: Statistical Mechanics and its Applications

View full text Add to dashboard Cite

show abstract

“…For example, Dias (2012) studies 10Y 3 daily data from 2007 to 2010 of 19 countries and compares the results with the previous study by Gilmore et al (2010), who use monthly data from 1993 to 2008. Dias (2012) shows that sovereign bonds market is shattered into smaller groups (Eurozone Core vs Eurozone Periphery) and the comovement decreased.…”

Section: Literature Reviewmentioning

confidence: 98%

“…A part of the integration was harmonization of sovereign debt markets which resulted in a high degree of co-movement between yields of sovereign bonds (Laopodis, 2008;Gilmore et al, 2010;Missio, 2013). After the fall of Lehman Brothers the financial and banking crisis spread through the whole world and theories of risk management were shaken.…”

Section: Introductionmentioning

confidence: 99%