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Combining Bond Rating Forecasts Using Logit
Author(s) -
Kamstra Mark,
Kennedy Peter,
Suan TeckKin
Publication year - 2001
Publication title -
financial review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.621
H-Index - 47
eISSN - 1540-6288
pISSN - 0732-8516
DOI - 10.1111/j.1540-6288.2001.tb00011.x
Subject(s) - econometrics , competitor analysis , logit , logistic regression , bond , bond credit rating , yield (engineering) , ordered logit , statistics , economics , actuarial science , mathematics , finance , materials science , management , metallurgy , credit reference , credit risk
Companies sometimes use statistical analysis to anticipate their bond ratings or a change in the rating. However, different statistical models can yield different ratings forecasts, and there is no clear rule for which model is preferable. We use several forecasting methods to predict bond ratings in the transportation and industrial sectors listed by Moody's bond rating service. A variant of the ordered‐logit regression‐combining method of Kamstra and Kennedy 1998 yields statistically significant, quantitatively meaningful improvements over its competitors, with very little computational cost.