Articlegreen2006

Bond rating using support vector machine

Lijuan Cao · Lim Kian Guan · Zhang Jingqing

44 citations0/0 files storedIntelligent Data Analysis

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Financial Distress and Bankruptcy Prediction Data Mining and Machine Learning Applications Credit Risk and Financial Regulations

Abstract

This paper deals with the application of support vector machine (SVM) for bond rating. The three commonly used methods for solving multi-class classification problems in SVM, “one-against-all”, “one-against-one”, and directed acyclic graph SVM (DAGSV

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1973A MULTIVARIATE ANALYSIS OF INDUSTRIAL BOND RATINGS 1985CLASSIFICATION MODELS AND BOND RATINGS 1997Predicting Bond Ratings Using Neural Networks: A Comparison with Logistic Regression 1997Ordinal Pairwise Partitioning (OPP) Approach to Neural Networks Training in Bond rating 1988PREDICTING INDUSTRIAL BOND RATINGS WITH A PROBIT MODEL AND FUNDS FLOW COMPONENTS

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2009Improving option price forecasts with neural networks and support vector regressions 2015The predictive accuracy of Sukuk ratings; Multinomial Logistic and Neural Network inferences 2013Empirical research on corporate credit-ratings: A literature review

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