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<p>This study examines the structure and dynamics of financial networks in an emerging market context by constructing Granger causality-based linkages among ten Turkish sectoral equity indices and four macroeconomic variables over the period May 2015 to May 2025 (2,487 trading days). The analysis aims to identify key sources of systemic vulnerability and characterize transmission mechanisms within the financial system. The findings indicate that the resulting macroeconomically driven network structure differs markedly from those documented in advanced economies. The model demonstrates strong predictive performance, achieving 94–96% accuracy in capturing transmission dynamics during the August 2018 financial crisis. A temporal analysis across seven subperiods reveals a consistent pattern of crisis-induced network densification, with interconnectedness increasing by 19–31% during periods of financial stress. The findings suggest that systemic risk in emerging markets is primarily propagated through aggregate macroeconomic channels. These results provide a quantitative basis for the design of macroprudential policy tools, including network-based capital buffers and early warning systems. Policy implications emphasize the importance of exchange rate stabilization and improvements in sovereign creditworthiness, alongside the implementation of dynamic capital buffers that internalize systemic externalities, the monitoring of network-based risk indicators, and enhanced coordination across monetary, fiscal, and prudential policy frameworks.</p>

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Systemic risk architecture in emerging markets: network perturbation analysis and temporal dynamics of Turkish financial interconnectedness

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月17日

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  • Larissa M. Batrancea,
  • Mehmet Ali Balcı,
  • Ömer Akgüller,
  • Felipe de Jesús Bello Gómez

摘要

This study examines the structure and dynamics of financial networks in an emerging market context by constructing Granger causality-based linkages among ten Turkish sectoral equity indices and four macroeconomic variables over the period May 2015 to May 2025 (2,487 trading days). The analysis aims to identify key sources of systemic vulnerability and characterize transmission mechanisms within the financial system. The findings indicate that the resulting macroeconomically driven network structure differs markedly from those documented in advanced economies. The model demonstrates strong predictive performance, achieving 94–96% accuracy in capturing transmission dynamics during the August 2018 financial crisis. A temporal analysis across seven subperiods reveals a consistent pattern of crisis-induced network densification, with interconnectedness increasing by 19–31% during periods of financial stress. The findings suggest that systemic risk in emerging markets is primarily propagated through aggregate macroeconomic channels. These results provide a quantitative basis for the design of macroprudential policy tools, including network-based capital buffers and early warning systems. Policy implications emphasize the importance of exchange rate stabilization and improvements in sovereign creditworthiness, alongside the implementation of dynamic capital buffers that internalize systemic externalities, the monitoring of network-based risk indicators, and enhanced coordination across monetary, fiscal, and prudential policy frameworks.