A financial crisis is recognized as a breakdown of the credit markets that lead to various problems because a financial crisis has a lot of side effects that do not affect only the financial markets but affect to economic side also in the social side. In the last decade, according to the various problems of the financial crisis, many researchers attempted to forecast the risk of a financial crisis by employing the hard information recorded as numbers such as the annual report, which is the old information that may not be accurate. Therefore, I realized combining hard and soft information to predict more accuracy because soft information is communicated as text. Besides, most soft information is the current or new information such as opinion, idea, and future-plans that will make my forecast more reliable.
This research focuses on the Taiwan electron component industry in 2018 by collecting the data from the Taiwan Economic Journal (TEG) in the MD&A section. The reason for choosing the electron component industry in this research is because this industry collects some of Taiwan's largest companies. After getting the data, I applied the Rotation Forest model (AI technique) to evaluate the financial crisis and used the confusion matrix to estimate the accuracy of the outcome.
