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This study investigates the dynamics of financial contagion within the European banking sector, focusing on Erste Bank International (EBS) and its interactions with Raiffeisen Bank International (RBI), OTP Bank (OTP), crude oil prices (CL) and Bitcoin (BTC) over the period 2015–2023, using daily price data collected from Yahoo Finance. Utilizing the Autoregressive Distributed Lag (ARDL) model and error correction mechanisms, we explore both short-term impacts and long-term relationships among these variables. Data were extracted from Yahoo Finance, ensuring a comprehensive overview of market coverage. The results show strong interdependencies, while CL, RBI, and OTP significantly influencing EBS stock in the short term. BTC’s impact, while present, is more complex, reflecting the evolving role of digital assets. The error correction model confirms a solid adjustment toward long-term equilibrium. Residuals are centered around zero, with Jarque-Bera test indicating normality, supporting the model’s robustness. The low standard deviation further reflects consistency. This research contributes to understanding financial contagion mechanisms, highlighting how traditional market indicators and emerging digital assets influence stock performance within the banking sector. It offers valuable insights for investors, policymakers, and regulators aiming to better understand and manage the complexity of today’s interconnected financial systems.

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ARDL Insights into Financial Contagion: Assessing the Impact of Crude Oil and Bitcoin on European Banks

  • 会议论文

  • 发表日期：

    2026年

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  • Ștefan Ionescu,
  • Ionuț Nica,
  • Daniel Magueta,
  • Camelia Delcea

摘要

This study investigates the dynamics of financial contagion within the European banking sector, focusing on Erste Bank International (EBS) and its interactions with Raiffeisen Bank International (RBI), OTP Bank (OTP), crude oil prices (CL) and Bitcoin (BTC) over the period 2015–2023, using daily price data collected from Yahoo Finance. Utilizing the Autoregressive Distributed Lag (ARDL) model and error correction mechanisms, we explore both short-term impacts and long-term relationships among these variables. Data were extracted from Yahoo Finance, ensuring a comprehensive overview of market coverage. The results show strong interdependencies, while CL, RBI, and OTP significantly influencing EBS stock in the short term. BTC’s impact, while present, is more complex, reflecting the evolving role of digital assets. The error correction model confirms a solid adjustment toward long-term equilibrium. Residuals are centered around zero, with Jarque-Bera test indicating normality, supporting the model’s robustness. The low standard deviation further reflects consistency. This research contributes to understanding financial contagion mechanisms, highlighting how traditional market indicators and emerging digital assets influence stock performance within the banking sector. It offers valuable insights for investors, policymakers, and regulators aiming to better understand and manage the complexity of today’s interconnected financial systems.