Predicting a bank's credit rating change using ratios and news
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This book integrated published financial news with accounting ratios to measure the viability of increasing the discriminatory power of a credit rating model. The aim was the utilization of information in news articles to create additional predictors of credit rating changes. Modal sentiment in news articles were integrated with calculated financial ratios from the published financial statements. The integrated data points were then analyzed in Eviews resulting in a model which was then used in determining credit rating. The model was found to be stable and having a good discriminatory power. ...
This book integrated published financial news with accounting ratios to measure the viability of increasing the discriminatory power of a credit rating model. The aim was the utilization of information in news articles to create additional predictors of credit rating changes. Modal sentiment in news articles were integrated with calculated financial ratios from the published financial statements. The integrated data points were then analyzed in Eviews resulting in a model which was then used in determining credit rating. The model was found to be stable and having a good discriminatory power. Credit ratings of sample banks were then determined as at 31 December 2013. The output from the model was found to be almost the same as ratings assigned by GCR and RBZ. Data points from outside the sample were used to validate capability of the model in measuring ratings of banks outside the sample.
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