Abstract
Abstract The paper presents a model to model qualitative variables to estimate credit spreads. The main purpose of our study was to price loans and verify whether interest rates depend on credit portfolio weights, applying a reverse engineering process. In particular, loans may be priced from credit portfolio composition applying the Sharpe model (1974) originally devoted to expected returns of asset classes. Our overall percentage of default forecast is higher for the unbalanced sample (around 6% higher) even though we believe the balanced sample is more robust. Using a regression tree we showed how to estimate the probability of default for each rating notch. Monotonicity property of PDs appears to be confirmed for both the samples (unbalanced and balanced) we tested. The final output will be the equilibrium portfolio, which depend upon the bank risk aversion. Key Words: Credit risk; Reverse engineering; Credit spreads; Risk management JEL Classification : G11; G21 Financial Economics Department University of Siena WP 1/2009
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
