DETERMINANT OF SUKUK RATINGS
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. This study tries to provide an empirical foundation for the investors to estimate the ratings assign. Using approach from several rating agencies, past researches on bond ratings, financial distress prediction and bankruptcy prediction models, this study is trying to innovate a new model on determining the sukuk ratings. It used Multinomial Logit regression to create a model of rating probability from several theoretical variables, ie. firm size, leverage, profitability, fixed payment coverage, reputation and existence of guarantor. The result shows 80% of all valid cases are correctly classified into their original rating classes.
JEL Classification: C35, E43, P43
Keywords: Sukuk, rating.
Downloads
References
Chanchara. Nongnit, Pamela Davy, Michael McCrae and Gary Tian, 2007, Firms in financial distress, a survival model analysis. Working paper series Wollongong University. November.
Chaveesuk R. Srivaree-ratana C., and Smith E. 1979. Alternative neural network approaches to corporate bond rating, Journal of Engineering Valuation and Cost Analysis September.
Erkki K.Latinen, 2007 , Survival Analysis and Financial Distress Prediction: Finnish Evidence. Emerald Backfiles.
Gruszczynski, Merek. Financial distress of companies in Poland. IAER, nov 2004 vol.10 no.4
Gujarati, D.N. 1995. Basic Econometrics. 3rd ed. New York: McGraw-Hill, Inc.
Hadju, Otto and Miklos Virag, 1996, Hungrian model for predicting financial bankruptcy.
Horrigan, J.O. 1966. The determination of long-term credit standing with financial ratios. Empirical Research in Accounting: Selected studies: 44-62.
Kamstra, M. et.al. 2001. Combining bong rating forecast using logit. The Financial Review 37, 75-96.
Kaplan, R.S. and Urwitz, 1979. Statistical models pf bond ratings: A methodology inquiry, Journal of Business 52, 231-261.
Karbhari, Yusuf and Zulkarnain Muhamad Sori, 2004, Prediction of Corporate Financial Distress: Evidence from Malaysian Listed Firm During The Asian Financial Crisis. Working paper series University Putra Malaysia.
Kim, K., and Han I. 2001. The cluster-indexing method for case base reasoning using selforganizing maps and learning vector quantization for bond ratingcases, Expert System with Applications, 21, 147-156.
LeClere, Marc J, 2002, Time-Dependent and Time-Invariant covariates within a proportional hazards model: A financial distress application. Working paper series Valparaiso university. August.
Li, Dairui and Jia Liu, 2009, Determinants of Financial Distress of ST and PT Companies: A Panel Analysis of Chinese Listed Companies. February
Methodology for Shari»a Quality Rating. Islamic International Rating Agency, May 2006. www.iira.com
Multinomial Logistic Regression: Complete Problems. Data Analysis and Computer II. www.google.com
Rating Agency Malaysia Bhd. 2009. Islamic-Debt Securities http://www.ram.com.my
Ugurlu, Mine and Hakan Aksoy.nPrediction of corporate financial distress in an emerging market: The case of Turkey. Cross Cultural Management Journal vol.13 No.4, 2006
Buletin Ekonomi Moneter dan Perbankan / Bulletin of Monetary Economics and Banking is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
