| Summary: | 碩士 === 東吳大學 === 財務工程與精算數學系 === 98 === In response to implementation of Basel II, the capital adequacy ratio of banks must correspond with risky assets and minimum capital requirements. Therefore, they will adjust structure of loans and asset allocation. In particular, along with meager profit time oncoming, it can not be ignored that the high NPL ratio will affect the bank's profits seriously. Therefore, banks should draw up more precise measurement of credit risk to distinguish classification of risks, to further improve the quality of credit granting and resource allocation. The purpose of this study is to use multiple indicators to construct prediction model for enterprise financial crisis . However, the banks could reference the results to assess risk and interest rate pricing and approval of credit granting. In addition, they could be used to strengthen credit risk management and improve to identification of risk and degree.
In this research, we selected 41 crisis enterprises in Taiwan electronic industry which experienced seriously financial distress during the period of 2001 to 2009 and included the period between the previous year to the previous three year prior to the company experienced financial distress. To apply 1：1 matched pairs sample method, for comparing purposes, this investigation chooses another 41 non-distress enterprises in the same industry which also have the similar size as the matching samples of crisis enterprises. Through the four dimensions of the indicators to explore, above all, using financial ratios variables combine with Factor Analysis Approach. The second part is to calculate three kinds of the efficiency values by Data Envelopment Analysis. Next, KMV model is used to estimate Expected Default Frequency. Finally, the last dimension is added Taiwan Corporate Credit Risk Index as a measure of credit rating. Moreover, go through testing and the research process to extract indicators which is more significantly different from others. This study considers multifaceted dimensions and integrates with multiple indicators to construct logistic model and predict enterprise financial crisis.
The empirical results show that: Forecast distress enterprise in the electronics industry by making use of financial crisis prediction model, the accuracy rate prediction is approximately between 80.49% to 92.68%. A clear indication that the model of the electronics industry has a financial early warning capability. In particular, the accuracy which is close to crisis point could be better. Furthermore, explanation of variations in the previous year rise to 80% and be higher than in the other years. Besides, explanatory power of all financial crisis prediction models are also more than 50% yearly and increasing year by year. The prediction and fitness ability of model for enterprise financial crisis is more effective.
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