| dc.description.abstract | This thesis examines the contribution of applying the KMV-Merton model on Swedish real
estate companies listed at the NASDAQ OMX Nordic Real Estate Index. Comparing the
KMV-Merton model credit rating to frequently applied credit metrics, we find that the model
adequately captures relevant information contained in these metrics. Additionally, the model
proves robust when using long time series. Applying data from the time interval 2007-2014,
we estimate econometric models to decompose significant predictor variables for credit
spread variation at issuance. We obtain data directly from financial statements to assure
statistically useful estimates. A univariate econometric model including the KMV-Merton
default probability explains pooled cross-sectional regularities in credit spreads rather well.
Combining firm financials, macroeconomic predictors and bond characteristics with the pure
structural model, we conclude that a comprehensive hybrid model has improved fit. This
result suggests that the KMV-Merton model is unable to capture all information contained in
financial- and macroeconomic data. In particular, a model including the default probability,
loan-to-value, the 3-month annualized interbank rate, coupon structure and credit rating is
able to explain 80.19% of credit spread variation. Including a time variable enables us to
exclude the existence of spurious time correlations and construct a model that is
unconstrained in the parameters. Overall, the explanatory power achieved aligns with
empirical research. In summary, we conclude that the KMV-Merton model yields significant
statistics for credit risk assessment of Swedish real estate bonds at issuance. However, the
statistic does not prove sufficient, as the comprehensive hybrid outperforms the univariate
model. | nb_NO |
