Quadrant categorization of spillover determinants of sovereign risk of BRICIT nations: a Bayesian approach
Abstract This study investigates the determinants that drive the volatility of the credit default swaps (CDS) of BRICIT (Brazil, Russia, India, China, Indonesia, and Turkey) nations as a proxy measure for sovereign risk. On the existence of cointegration, an unrestricted error correction model integ...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-01-01
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| Series: | Financial Innovation |
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| Online Access: | https://doi.org/10.1186/s40854-024-00699-z |
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| author | Pawan Kumar Vipul Kumar Singh |
| author_facet | Pawan Kumar Vipul Kumar Singh |
| author_sort | Pawan Kumar |
| collection | DOAJ |
| description | Abstract This study investigates the determinants that drive the volatility of the credit default swaps (CDS) of BRICIT (Brazil, Russia, India, China, Indonesia, and Turkey) nations as a proxy measure for sovereign risk. On the existence of cointegration, an unrestricted error correction model integrated with the autoregressive distributed lag (ARDL) model is applied to measure the short-run and long-run dynamics empirically. The study utilizes the Bayesian global vector autoregression methodology for cross-border spillover estimation. The study also suggests a strategy for policymakers for quadrant categorization to mitigate risk arising from cross-border spillover. The result of ARDL indicates that the global macroeconomic variables affect the BRICIT CDS more than domestic macroeconomic determinants, with Indian CDS being the most sensitive to Fed tapering. Notably, China’s CDS is the most sensitive to shocks, with the CDS volatility primarily driven by China’s geopolitical risk. Russian CDS is more sensitive to real effective exchange rates due to severe ruble depreciation than crude oil, despite Russia being a major oil exporter. The quadrant categorization indicates that the Indonesian stock market index is most interconnected with BRICIT CDS, while the Turkish long-term interest rates send the highest intensity spillover across BRICIT nations. |
| format | Article |
| id | doaj-art-dd9e967a5b1e4ba6b5367767a569e20f |
| institution | Kabale University |
| issn | 2199-4730 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Financial Innovation |
| spelling | doaj-art-dd9e967a5b1e4ba6b5367767a569e20f2025-01-26T12:48:40ZengSpringerOpenFinancial Innovation2199-47302025-01-0111112210.1186/s40854-024-00699-zQuadrant categorization of spillover determinants of sovereign risk of BRICIT nations: a Bayesian approachPawan Kumar0Vipul Kumar Singh1Dublin City UniversityIndian Institute of Management, Mumbai (IIM Mumbai)Abstract This study investigates the determinants that drive the volatility of the credit default swaps (CDS) of BRICIT (Brazil, Russia, India, China, Indonesia, and Turkey) nations as a proxy measure for sovereign risk. On the existence of cointegration, an unrestricted error correction model integrated with the autoregressive distributed lag (ARDL) model is applied to measure the short-run and long-run dynamics empirically. The study utilizes the Bayesian global vector autoregression methodology for cross-border spillover estimation. The study also suggests a strategy for policymakers for quadrant categorization to mitigate risk arising from cross-border spillover. The result of ARDL indicates that the global macroeconomic variables affect the BRICIT CDS more than domestic macroeconomic determinants, with Indian CDS being the most sensitive to Fed tapering. Notably, China’s CDS is the most sensitive to shocks, with the CDS volatility primarily driven by China’s geopolitical risk. Russian CDS is more sensitive to real effective exchange rates due to severe ruble depreciation than crude oil, despite Russia being a major oil exporter. The quadrant categorization indicates that the Indonesian stock market index is most interconnected with BRICIT CDS, while the Turkish long-term interest rates send the highest intensity spillover across BRICIT nations.https://doi.org/10.1186/s40854-024-00699-zBayesian global vector autoregression (B-GVAR)BRICIT (Brazil, Russia, India, China, Indonesia and Turkey)Credit default swaps (CDS)Sovereign riskSpillover |
| spellingShingle | Pawan Kumar Vipul Kumar Singh Quadrant categorization of spillover determinants of sovereign risk of BRICIT nations: a Bayesian approach Financial Innovation Bayesian global vector autoregression (B-GVAR) BRICIT (Brazil, Russia, India, China, Indonesia and Turkey) Credit default swaps (CDS) Sovereign risk Spillover |
| title | Quadrant categorization of spillover determinants of sovereign risk of BRICIT nations: a Bayesian approach |
| title_full | Quadrant categorization of spillover determinants of sovereign risk of BRICIT nations: a Bayesian approach |
| title_fullStr | Quadrant categorization of spillover determinants of sovereign risk of BRICIT nations: a Bayesian approach |
| title_full_unstemmed | Quadrant categorization of spillover determinants of sovereign risk of BRICIT nations: a Bayesian approach |
| title_short | Quadrant categorization of spillover determinants of sovereign risk of BRICIT nations: a Bayesian approach |
| title_sort | quadrant categorization of spillover determinants of sovereign risk of bricit nations a bayesian approach |
| topic | Bayesian global vector autoregression (B-GVAR) BRICIT (Brazil, Russia, India, China, Indonesia and Turkey) Credit default swaps (CDS) Sovereign risk Spillover |
| url | https://doi.org/10.1186/s40854-024-00699-z |
| work_keys_str_mv | AT pawankumar quadrantcategorizationofspilloverdeterminantsofsovereignriskofbricitnationsabayesianapproach AT vipulkumarsingh quadrantcategorizationofspilloverdeterminantsofsovereignriskofbricitnationsabayesianapproach |