Comparing structural credit models and their applicability to banks

2019

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.