Determinants of Australian Listed Property Trust Bond Ratings

Author/s: Bwembya Chikolwa

Date Published: 1/01/2008

Published in: Volume 14 - 2008 Issue 2 (pages 123 - 149)


Using artificial neural networks (ANN) and ordinal regression (OR) as alternative methods to predict LPT bond ratings, we examine the role that various financial and industry-based variables have on Listed Property Trust (LPT) bond ratings issued by Standard and Poor’s from 1999-2006. Our study shows that both OR and ANN provide robust alternatives to rating LPT bonds and that there are no significant differences in results between the full models of the two methods. OR results show that of the financial variables used in our models, debt coverage and financial leverage ratios have the most profound effect on LPT bond ratings. Further, ANN results show that 73.0% of LPT bond rating is attributable to financial variables and 27.0% to industry-based variables, with the office LPT sector accounting for 2.6%, retail LPT sector 10.9% and stapled management structure 13.5%.

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Artificial Neural Networks - Bond Rating - Listed Property Trusts - Ordinal Regression


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