Assessing systemic risk in Morocco’s banking sector: Conditional value-at-risk approach

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Type of the article: Research Article

Abstract
Systemic risk in the banking sector poses a major threat to financial stability, particularly in concentrated markets such as Morocco, where the failure of one institution may trigger widespread disruptions. Understanding the extent to which individual banks contribute to systemic risk and generate spillover effects is essential for sustaining financial system resilience. This study aims to assess the systemic risk contributions and spillover potential of six listed Moroccan banks, Attijariwafa Bank (ATW), Bank of Africa (BOA), Banque Marocaine pour le Commerce et l’Industrie (BCI), Banque Centrale Populaire (BCP), Crédit Immobilier et Hôtelier (CIH), and Crédit du Maroc (CDM), by applying the Conditional Value-at-Risk (CoVaR) methodology. The analysis uses daily return data covering the period from January 4, 2010 to January 10, 2025. Value-at-Risk (VaR) estimates at 99% and 95% confidence levels show that the three largest banks, ATW, BCP, and BOA, are the least individually risky banks under normal market conditions, suggesting greater stability. In contrast, the smallest banks, CDM, BCI, and CIH, exhibit higher individual risk exposure. CoVaR and ΔCoVaR (marginal CoVaR) results indicate that ATW, BCP, and BOA are the primary contributors to systemic risk, with a higher potential for spillover during times of distress, while the remaining banks are less systemically significant. These findings highlight the need for enhanced macroprudential oversight and regular stress testing for larger institutions, alongside improved internal risk controls for smaller banks. The study emphasizes the importance of data-driven regulatory strategies in mitigating systemic vulnerabilities and strengthening the long-term stability of Morocco’s banking sector.

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    • Figure 1. Graphical representations of the six banks and the banking index
    • Figure 2. Value-at-Risk of the six Moroccan banks at (1 – α = 99%) and (1 – α = 95%)
    • Figure 3. ΔCoVaR for the six banks at (1 – α = 99%) and (1 – α = 95%) confidence levels
    • Table 1. Augmented Dickey-Fuller applied to the prices
    • Table 2. Augmented Dickey-Fuller applied to the algebraic returns
    • Table 3. Value-at-Risk VaR1–α (in %) at confidence levels (1 – α = 99%), 95%, 50%
    • Table 4. CoVaR and ΔCoVaR at the (1 – α = 99%) confidence level
    • Table 5. CoVaR and ΔCoVaR at the (1 – α = 95%) confidence level
    • Conceptualization
      Soufiane Benbachir, Mohamed Beraich
    • Data curation
      Soufiane Benbachir, Mohamed Beraich
    • Formal Analysis
      Soufiane Benbachir, Mohamed Beraich
    • Investigation
      Soufiane Benbachir, Mohamed Beraich
    • Methodology
      Soufiane Benbachir, Mohamed Beraich
    • Project administration
      Soufiane Benbachir, Mohamed Beraich
    • Resources
      Soufiane Benbachir, Mohamed Beraich
    • Software
      Soufiane Benbachir, Mohamed Beraich
    • Supervision
      Soufiane Benbachir, Mohamed Beraich
    • Validation
      Soufiane Benbachir, Mohamed Beraich
    • Visualization
      Soufiane Benbachir, Mohamed Beraich
    • Writing – original draft
      Soufiane Benbachir
    • Writing – review & editing
      Soufiane Benbachir