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Network Topology of Dynamic Credit Default Swap Curves of Energy Firms and the Role of Oil Shocks

Elie Bouri and Syed Jawad Hussain Shahzad

Year: 2022
Volume: Volume 43
Number: Special issue
DOI: 10.5547/01956574.43.SI1.ebou
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Abstract:
Using network analysis on the connectedness of default factors in a credit default swap (CDS) dataset of U.S. and European energy firms, we provide the first evidence of differences in the shape and dynamics of the interconnectedness of the level, slope, and curvature, representing long-, short- and middle-term default factors, respectively. The interconnectedness of the three default factors increases during the European sovereign debt crisis (ESDC), whereas only the interconnectedness of the level factor increases during the oil price crash, and the interconnectedness of both level and slope factors spikes during COVID19. European firms contribute more to the transmission of long-term and short-term default risk from early 2011 till the beginning of the 2014–2105 oil price crash; afterwards, U.S. firms are major default transmitters despite some periods of parity with European firms. The impacts of oil demand and supply shocks on the various interconnectedness are quantile-dependent and more pronounced in the long term for the credit risk of the energy firms.



Systemic Risk in the Global Energy Sector: Structure, Determinants and Portfolio Management Implications

Syed Jawad Hussain Shahzad, Román Ferrer, Elie Bouri

Year: 2023
Volume: Volume 44
Number: Number 6
DOI: 10.5547/01956574.44.6.ssha
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Abstract:
We examine the dynamics of tail dependence across returns of 105 global energy firms from 26 countries covering the regions of America, Asia Pacific and Europe. A partial correlation-based approach is used to quantify the dependence structure and level of systemic risk under relatively stable and extremely bearish and bullish market conditions. The dependence network of energy stock returns is constructed based on the novel triangulated maximally filtered graph (TMFG). The results reveal a high degree of tail dependence and role played by geographical proximity. The strongest links are found under extreme bearish market conditions. American and European energy firms are more interconnected and contribute more to systemic risk than Asian-Pacific companies. The dependence intensifies during periods of market turmoil, especially during the COVID-19 pandemic. A higher instability in the dependence structure is observed during extremely bearish market circumstances. A simple portfolio trading strategy based on the dependence ranking of energy firms outperforms a naïve equally-weighted buy-and-hold portfolio strategy.





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