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Bank solvency evaluation with a Markov model


  • Juan Reboredo


This paper provides an empirical model for a probabilistic evaluation of bank solvency that includes heterogeneity and past solvency. Bank solvency positions are obtained from the value of a stochastic recursive profit function. Transition probabilities among bank solvency positions are determined by portfolio decisions, and draw the probabilistic evolution over time of bank solvency. Thus, the bank activity is characterized as a Markov decision process whose transition matrix is obtained from a Markov Chain model with a quadratic conditional variance. The empirical implementation for Spanish banks indicates that both heterogeneity and past solvency are important to evaluate bank solvency.

Suggested Citation

  • Juan Reboredo, 2002. "Bank solvency evaluation with a Markov model," Applied Financial Economics, Taylor & Francis Journals, vol. 12(5), pages 337-345.
  • Handle: RePEc:taf:apfiec:v:12:y:2002:i:5:p:337-345
    DOI: 10.1080/09603100110090145

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