Determinant of sukuk ratings : the Malaysian case

Abstract

With the development of sukuk market as the Islamic alternatives of the existing bond market, the issue of how to assign a rating to the sukuk issuance rises. These credit ratings fulfil a key function of information transmission in capital market. Issuers seek ratings for a number of reasons, including to improve the trust of their business counterparties or because they wish to sell securities to investors with preferences over ratings. Many investors rely on ratings in their investment decisions. For these reasons, ratings are considered important by issuers and investors alike. This study tries to provide an empirical foundation for the investors to estimate the ratings assign. Using approaches from several rating agencies, past researches on bond ratings, and financial distress prediction and bankruptcy prediction model, this study is trying to build a new model on determining the sukuk ratings. It used Ordered Logistic Regression and Multinomial Lo git Regression to create a model of rating probability from several theoretical variables, ie. firm size, leverage, fixed payment coverage, profitability, liquidity, and existence of guarantor. The result shows 70% for Ordered Logistic and 78.3% for Multinomial Logistic of all valid cases are correctly classified into their original rating classes. About the misclassification cost Type I and Type II error, it is also found that Ordered Logistic prediction is having more both Type I and Type II error compare to Multinomial Logistic prediction. Therefore, we conclude that Multinomial Logistic model is more powerful than Ordered Logistic model using the samples we have.