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|標題:||Constructing the Warning Prediction Models of Corporations|
|關鍵字:||Warning Prediction Models|
Financial Ratio Analysis Corporate Governance
Data mining Neuro-Fuzzy Expert System
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|摘要:||This thesis consists of three essays related to the problems a company may encounter: financial distress, litigation, and fraud. These three issues have been discussed for a long time in financial and accounting field. Due to its importance for both the academia and practice, three new tries are made in hope to provide new insights into this area in this thesis.
In the first part, instead of constructing a warning system to predict the possibility of financial distress, association analysis is adopted to explore how the financial ratios are deteriorated, and how the relationships among the financial ratios are changed before the financial distress. Different from most of the other studies related to financial distress to predict the financial distress based on the cross sectional data, this research is trying to provide some guidelines for a corporation to avoid a financial distress from a longitudinal point of view.
In the second part, a litigation warning model is constructed based on the governance factors by using neuron fuzzy which is a hybrid technique combining the functionality of fuzzy logic and the learning ability of neural network. In this paper, a comparison is made between the traditional statistical technique, logic, and the proposed technique, neuro fuzzy. In addition to providing a litigation warning model with higher accuracy, the proposed neuron fuzzy model can also provide the auditor the knowledge about the relationship among the variables obtained from the past data.
In the third part, a comparison is made between the prediction results based on the different categorization of the risk factors according to SAS No. 82 and SAS No. 99. With the empirical results, this research is trying to show what the difference is between these two statements, which has not been discussed in the past. These results can be referred to before a new statement is advanced in the future.|
本篇論文包含三篇以遭遇財務危機、起訴或舞弊問題公司為議題的文章。由於這些議題在財務和會計領域已經討論甚久，且對於學術與實務應用都相當的重要，因此本篇論文希望藉由嘗試不同的探討方式提供新的觀點在這些議題上。 在第一部份，本文利用關聯分析方法建構預測財務危機的預警系統，藉以探索財務危機發生前，其財務比率構面相互間之關聯性。本文與其他研究不同之處在於過去研究係利用橫斷面資料預測財務危機，而本文嘗試由長期性觀點提出避免遭受財務危機之方針予企業。 在第二部份，本文運用結合具有模糊邏輯功能與類神經網路運算能力的類神經模糊工具，建構以公司治理觀點的訴訟預警模式。本文以傳統羅吉斯模式作為類神經模糊比較基礎，結果發現類神經模糊模式除了有較佳的預測準確性之外，亦能提供較多變數間關係的資訊予審計人員。 在第三部份，本文比較舞弊風險要素在SAS No.82與SAS No.99不同分類下的預測結果。並嘗試藉由實證結果來闡訴過去研究未曾探討的公報間優劣之比較，此結果將有助於未來新公報擬訂時之參酌。
|Appears in Collections:||企業管理學系所|
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