Determinants of commercial mortgage-backed securities credit ratings: Australian evidence
Using artificial neural networks (ANN) and ordinal regression (OR) as alternative methods to predict Commercial Mortgage-backed Securities (CMBS) credit ratings, we examine the role that various financial and industry-based variables have on CMBS credit ratings issued by Standard and Poor’s from 199...
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| Format: | Journal Article |
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Vilnius Jediminas Technical University, Lithuanian Academy of Sciences and Napier University
2008
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| Online Access: | http://hdl.handle.net/20.500.11937/48145 |
| Summary: | Using artificial neural networks (ANN) and ordinal regression (OR) as alternative methods to predict Commercial Mortgage-backed Securities (CMBS) credit ratings, we examine the role that various financial and industry-based variables have on CMBS credit ratings issued by Standard and Poor’s from 1999–2005. Our OR results show that rating agencies use only a subset of variables they describe or indicate as important to CMBS credit rating as some of the variables they use were statistically insignificant. Overall, ANN show superior results to OR in predicting CMBS credit ratings. |
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