Comparing structural credit models and their applicability to banks
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- Master Thesis 
Throughout this thesis we have presented a narrow overview of the research field of structural credit models and their applicability to banks. We have focused on two of the newer contributions to the field by Nagel and Purnanandam (2019)(NP) and Atreya, Mjøs and Persson (2019)(AMP), and provided a thorough, but not exhaustive, comparison and evaluation of these models. We have found that the different approaches of the two models provide logical results for both risk-neutral probability of default (RNPD)1 and credit spreads2, each displaying strengths and weaknesses compared to the banking industry. Both models account for the crucial characteristic of banks in that the value of their loans, and therefore their assets, have a naturally capped upside. Accordingly, both models rely on the use of a standard Brownian motion to describe the uncertainty of borrower asset values, and then value the banks claim on these through their respective loans. In our comparison we find that the NP model provides somewhat higher estimates for both RNPD and credit spread relative to the AMP model for different borrower risk parameters. We then discuss various characteristics and assumptions of both models as explanatory for the observed deviation between the models. We also discuss whether each of these characteristics appear realistic in light of the banking industry. Lastly, we touch upon additional common deviations from the banking industry of structural credit models like the ones we compare. Here we point to the complexity of loan types, debt structure, bank income sources and bank’s borrowers as difficult elements to incorporate in detail. Nonetheless, we argue that the models in focus presents reasonable simplifications of the complex banking industry.