An empirical analysis of structuring commercial mortgage-backed securities : Australian evidence
Chikolwa, Bwembya (2007) An empirical analysis of structuring commercial mortgage-backed securities : Australian evidence. In 13th Pacific-Rim Real Estate Society Conference, 21-24 January 2007, Fremantle, WA.
The ultimate goal of structuring Commercial Mortgage-Backed Securities (CMBS) transactions is to obtain a high credit rating as this has an impact on the yield obtainable and the success of the issue. Though bond rating agencies claim that their ratings reflect each agency’s opinion about an issue’s potential default risk and rely heavily on a committee’s analysis of the issuer’s ability and willingness to repay its debt and therefore researchers would not be able to replicate their ratings quantitatively (Kim 2005), we follow previous researchers who gone ahead and replicated bond ratings on the premise that the financial variables extracted from public financial statements, such as financial ratios, contain a large amount of information about a company’s credit risk (Huang et al. 2004). We use artificial neural networks (ANN) and ordinal regression (OR) as alternative methods to predict CMBS ratings. OR results show that rating agencies use only a subset of variables they describe or indicate as important to CMBS rating as some of the variables they use were statistically insignificant. Overall, ANN show superior results to OR in predicting CMBS ratings.
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
Repository Staff Only: item control page