Using public information to predict corporate default rates in Taiwan.
博士 === 國立東華大學 === 企業管理學系 === 102 === Corporate defaults are often affected by many factors that are roughly divided into the two types: internal factors and external factors. Internal factors can be measured precisely with firm-specific financial statistics while external factors contain qualitative...
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| Format: | Others |
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2014
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| Online Access: | http://ndltd.ncl.edu.tw/handle/67666827391546524174 |
| Summary: | 博士 === 國立東華大學 === 企業管理學系 === 102 === Corporate defaults are often affected by many factors that are roughly divided into the two types: internal factors and external factors. Internal factors can be measured precisely with firm-specific financial statistics while external factors contain qualitative data, like related news. There are considerable number of timely information from news which affects the default probability of corporates. Efficiently extracting the information contained in the news is the main focus of this study.
We proposes to use Empirical Bayes and Bayesian network to extract the information contained within news and then to estimate its impact on the default probability of corporates. Empirical analysis finds that the news information has a significant impact on the corporate default rate prediction. Adding the news variable does improve the forecast precision and prove its usefulness.
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