Combining Bond Rating Forecasts Using Logit

Abstract

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.

The Effect of Leverage, Liquidity, Profitability, Coverage, Growth, and Firm Size With Auditor’s Reputation As A Moderating To Bond Rating of Banking Firm

“…Profitability which proxied through the Net Profit Margin (NPM) has sig 0.000 <0.05 and indicates that profitability affect the bond ratings. These results are consistent with research conducted by Kamstra et al, (2001), Kim and Gu (2004), Magreta andNurmayanti (2009), Amalia (2012), Melani and Kananlua (2013), Septyawanti (2013), as well as Sunarjanto and Tulasi (2013).…”

“…Therefore, the high level of liquidity is affect to the better bond rating. Kamstra et al, (2001), Kim and Gu (2004), Magreta andNurmayanti (2009), Amalia (2012), Melani and Kananlua (2013), Septyawanti (2013), and Sunarjanto and Tulasi (2013) revealed that profitability is affect to the bond rating. If the firm's income become higher, then the firm's ability to pay all its liabilities become higher so the deafult risk become lower and the bond rating getting better too.…”

“…The external auditors which included in the members of big four are Price water house Coopers, Deloite Touce & Tomatsu, Ernst & Young, and KPMG (Klynveld, Peat, Marwick, Goerdeler). Kamstra et al, (2001) revealed that leverage is affect to the bond rating. According to Burton et al, (in Magreta & Nurmayanti, 2009), if the leverage become higher, then the firm's failure risk become higher too and if the leverage is lower, then the usage of debt to finance the firm's activities is lower.…”

“…A bond Issuers firm which have high growth from year to year will have greater possibility to obtaining a good bond ratings than the bond issuers firm which have a low growth. Kamstra et al, (2001), Kim and Gu (2004), and Melani and Kananlua (2013) revealed that firm size is affect to the bond rating, where a bigger firm size, then the firm's ability to pay its liabilities become higher so the default risk become lower. The low default risk, then the bond rating which obtained is higher too.…”

A note comparing support vector machines and ordered choice models’ predictions of international banks’ ratings

“…but also provide information about their future financial positions. There has been extensive research in predicting bond ratings using multi-variate discriminant analysis, ordered choice models, non-parametric techniques and combined methods' forecasts to predict bond ratings -see, Altman and Saunders, (1998), Kamstra et al (2001) and Kim (2005). Thus, we employ financial variables, in addition to country risk (which we model using country specific dummy variables), as determinants of bank ratings in our modelling.…”