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The predictive accuracy of Sukuk ratings; Multinomial Logistic and Neural Network inferences

Author

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  • Arundina, Tika
  • Azmi Omar, Mohd.
  • Kartiwi, Mira

Abstract

The development of Sukuk market as the alternative to the existing conventional bond market has risen the issue of rating the Sukuk issuance. These credit ratings fulfill a key function of information transmission in capital market. Moreover, Basel Committee for Banking Supervision has now instituted capital charges for credit risk based on credit ratings. Basel II framework allowed the bank to establish capital adequacy requirements based on ratings provided by external credit rating agencies or determine rating of its investment internally for more advance approach. For these reasons, ratings are considered important by issuers, investors, and regulators alike. This study provides an empirical foundation for the investors to estimate the ratings assigned using the approach from several rating agencies and past researches on bond ratings. It tries to compare the accuracy of two logistic models; Multinomial Logistic Regression and Neural Network to create a model of rating probability from several financial variables.

Suggested Citation

  • Arundina, Tika & Azmi Omar, Mohd. & Kartiwi, Mira, 2015. "The predictive accuracy of Sukuk ratings; Multinomial Logistic and Neural Network inferences," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 273-292.
    • Handle: RePEc:eee:pacfin:v:34:y:2015:i:c:p:273-292
    DOI: 10.1016/j.pacfin.2015.03.002
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Naifar, Nader & Hammoudeh, Shawkat & Al dohaiman, Mohamed S., 2016. "Dependence structure between sukuk (Islamic bonds) and stock market conditions: An empirical analysis with Archimedean copulas," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 148-165.
    2. Paltrinieri, Andrea & Hassan, Mohammad Kabir & Bahoo, Salman & Khan, Ashraf, 2023. "A bibliometric review of sukuk literature," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 897-918.
    3. Runchi Zhang & Zhiyi Qiu, 2020. "Optimizing hyper-parameters of neural networks with swarm intelligence: A novel framework for credit scoring," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-35, June.
    4. Ghlamallah, Ezzedine & Alexakis, Christos & Dowling, Michael & Piepenbrink, Anke, 2021. "The topics of Islamic economics and finance research," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 145-160.
    5. Jaspreet Kaur & Madhu Vij & Ajay Kumar Chauhan, 2023. "Signals influencing corporate credit ratings—a systematic literature review," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 50(1), pages 91-114, March.
    6. Yuanxin Liu & FengYun Li & Xinhua Yu & Jiahai Yuan & Dong Zhou, 2018. "Assessing the Credit Risk of Corporate Bonds Based on Factor Analysis and Logistic Regress Analysis Techniques: Evidence from New Energy Enterprises in China," Sustainability, MDPI, vol. 10(5), pages 1-21, May.
    7. Ullah, Ayat & Arshad, Muhammad & Kächele, Harald & Zeb, Alam & Mahmood, Nasir & Müller, Klaus, 2020. "Socio-economic analysis of farmers facing asymmetric information in inputs markets: evidence from the rainfed zone of Pakistan," Technology in Society, Elsevier, vol. 63(C).
    8. Ibrahim, Mansor H., 2015. "Issues in Islamic banking and finance: Islamic banks, Shari’ah-compliant investment and sukuk," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 185-191.
    9. Azmat, Saad & Skully, Michael & Brown, Kym, 2017. "The (little) difference that makes all the difference between Islamic and conventional bonds," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 46-59.
    10. Asutay, Mehmet & Hakim, Amira, 2018. "Exploring international economic integration through sukuk market connectivity: A network perspective," Research in International Business and Finance, Elsevier, vol. 46(C), pages 77-94.
    11. Muhammad Safdar Sial & Jacob Cherian & Abdelrhman Meero & Asma Salman & Abdul Aziz Abdul Rahman & Sarminah Samad & Constantin Viorel Negrut, 2022. "Determining Financial Uncertainty through the Dynamics of Sukuk Bonds and Prices in Emerging Market Indices," Risks, MDPI, vol. 10(3), pages 1-13, March.
    12. Juan Carlos Reboredo & Nader Naifar, 2017. "Do Islamic Bond (Sukuk) Prices Reflect Financial and Policy Uncertainty? A Quantile Regression Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(7), pages 1535-1546, July.

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    More about this item

    Keywords

    Sukuk; Ratings; Multinomial Logistic; Neural Network;
    All these keywords.

    JEL classification:

    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G - Financial Economics
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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