{"title":"The Validity of Multinomial Logistic Regression and Artificial Neural Network in Predicting Sukuk Rating: Evidence from Indonesian Stock Exchange","authors":"M. L. Nurhakim, Z. Kisman, F. Syihab","doi":"10.1142/s0219091520500320","DOIUrl":null,"url":null,"abstract":"The Sukuk (shariah bond) market is developing in Indonesia and potentially will capture the global market in the future. It is an attractive investment product and a hot current issue in the capital market. Especially, the problem of predicting an accurate and trustworthy rating. As the Sukuk market developed, the issue of Sukuk rating emerged. As ordinary investors will have difficulty predicting their ratings going forward, this research will provide solutions to the problems above. The objective of this study is to determine the Indonesian Sukuk rating determinants and comparing the Sukuk rating predictive model. This research uses Artificial Neural Network (ANN) and Multinomial Logistic Regression (MLR) as the predictive analysis model. Data in this study are collected by purposive sampling and employing Sukuk rated by PEFINDO, an Indonesian rating agency. Findings in this study are debt, profitability and firm size significantly affecting Sukuk","PeriodicalId":45653,"journal":{"name":"Review of Pacific Basin Financial Markets and Policies","volume":"1 1","pages":"2050032"},"PeriodicalIF":0.3000,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Pacific Basin Financial Markets and Policies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0219091520500320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 1
Abstract
The Sukuk (shariah bond) market is developing in Indonesia and potentially will capture the global market in the future. It is an attractive investment product and a hot current issue in the capital market. Especially, the problem of predicting an accurate and trustworthy rating. As the Sukuk market developed, the issue of Sukuk rating emerged. As ordinary investors will have difficulty predicting their ratings going forward, this research will provide solutions to the problems above. The objective of this study is to determine the Indonesian Sukuk rating determinants and comparing the Sukuk rating predictive model. This research uses Artificial Neural Network (ANN) and Multinomial Logistic Regression (MLR) as the predictive analysis model. Data in this study are collected by purposive sampling and employing Sukuk rated by PEFINDO, an Indonesian rating agency. Findings in this study are debt, profitability and firm size significantly affecting Sukuk
期刊介绍:
This journal concentrates on global interdisciplinary research in finance, economics and accounting. The major topics include: 1. Business, economic and financial relations among the Pacific rim countries. 2. Financial markets and industries. 3. Options and futures markets of the United States and other Pacific rim countries. 4. International accounting issues related to U.S. companies investing in Pacific rim countries. 5. The issue of and strategy for developing Tokyo, Taipei, Shanghai, Sydney, Seoul, Hong Kong, Singapore, Kuala Lumpur, Bangkok, Jakarta, and Manila as international or regional financial centers. 6. Global monetary and foreign exchange policy, and 7. Other high quality interdisciplinary research in global accounting, business, economics and finance.