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題名 會計資訊與公司治理資訊在預測惡性倒閉事件的相對有用性 其他題名 Predicting Fraudulent Bankrupt---Accounting Informaiton vs. Corporate Governance Information 作者 張清福 貢獻者 國立政治大學會計學系
行政院國家科學委員會關鍵詞 經濟;會計;公司治理;預測惡性倒閉 日期 2008 上傳時間 26-六月-2012 14:57:22 (UTC+8) 摘要 會計資訊在財務危機預警模型的研究中，通常被認為具有一定程度的解釋能力，因此模型中都會將會計資訊作為財務危機預測的解釋變數之一，甚至有的財務危機預警模型完全只有會計資訊而無其他資訊包含其中，最知名的例子就是Altman (1968) 的Z-score 模型，這個模型直到今天仍然廣為使用。然而，有些論者（葉銀華2004）從個案的角度觀察，認為：在有些財務危機案例中，公司的會計資訊並無法提供財務危機的預警訊息，本文稱之為財務危機預警之『會計資訊無用論』。 如果將財務危機案例細分為經營不善型財務危機與惡性倒閉型財務危機，則會計資訊無用論者的論點指的是『會計資訊無法提供投資人惡性倒閉型財務危機的預警訊息』；反之，他們認為『公司治理資訊才能提供投資人惡性倒閉型財務危機的預警訊息』。值得吾人注意的是：這種論點只是經由個案觀察得到的看法，並未經過縝密的思辨與實證研究。 本文擬用會計資訊及公司治理資訊，運用吉布斯抽樣方法，建立離散時間涉險預測模型，來預測惡性倒閉型財務危機。
This study attempts to establish a bankruptcy prediction model for fraudulent financial distress by using Gibbs sampler to identify predictors. I propose to divide financial distress into two categories, fraudulent financial distress and poor-performance financial distress, since they may have different suitable bankruptcy prediction models. In addition, I employ Gibbs sampler, a Bayesian approach, to identify predictors of bankruptcy prediction model for fraudulent financial distress since it provides some advantages over classical methods in identifying predictors for studies with small sample size and relatively huge number of candidate predictors. From time to time, bankruptcy scandals occur in our economic society and cause the society huge costs, such as Procomp (博達) scandal in 2004 and Rebar Group (力霸) scandal in 2006. The former costs the society 5 billion dollars and the latter 7.31 billion dollars. The Rebar Group had avoided watching for 8 years during 1998-2006. Thus a powerful prediction model for bankruptcy scandal, other than for general bankruptcy, is much needed in this circumstance. Up to now, we have several modern credit-risk model such Merton model, KMV model, Creditrisk model and so on. Some models rely on market price information which may be still high before bankrupt for these bankruptcy scandals. On the other hand, some models using accounting information such as Z-score model (Alteman 1968) has been under criticism although it has been popular for decades. 葉銀華 (2002, 2004, 2005) criticize the useless of accounting information in predicting bankruptcy scandals while emphasizing corporate governance information. As an accounting research, I argue that the bankruptcy scandals are usually under way for years before bankruptcy occurs and the accounting information is still useful in predicting bankruptcy. Therefore, for fraudulent bankruptcy financial distress, from accounting perspective, I propose to search for potential useful accounting variables and corporate governance variables to be included in the model in the following procedure: (1) read the court investigation report and identify the accounting variables which may be fraud-affected, (2) use Gibbs sampler to stochastically search for useful variables from huge number of potential ones, (3) build fraudulent bankruptcy prediction model by applying discrete-time survival model and (4) conduct cross-validation.關聯 基礎研究
學術補助
研究期間:9708~ 9807
研究經費:333仟元資料類型 report dc.contributor 國立政治大學會計學系 en_US dc.contributor 行政院國家科學委員會 en_US dc.creator (作者) 張清福 zh_TW dc.date (日期) 2008 en_US dc.date.accessioned 26-六月-2012 14:57:22 (UTC+8) - dc.date.available 26-六月-2012 14:57:22 (UTC+8) - dc.date.issued (上傳時間) 26-六月-2012 14:57:22 (UTC+8) - dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/53234 - dc.description.abstract (摘要) 會計資訊在財務危機預警模型的研究中，通常被認為具有一定程度的解釋能力，因此模型中都會將會計資訊作為財務危機預測的解釋變數之一，甚至有的財務危機預警模型完全只有會計資訊而無其他資訊包含其中，最知名的例子就是Altman (1968) 的Z-score 模型，這個模型直到今天仍然廣為使用。然而，有些論者（葉銀華2004）從個案的角度觀察，認為：在有些財務危機案例中，公司的會計資訊並無法提供財務危機的預警訊息，本文稱之為財務危機預警之『會計資訊無用論』。 如果將財務危機案例細分為經營不善型財務危機與惡性倒閉型財務危機，則會計資訊無用論者的論點指的是『會計資訊無法提供投資人惡性倒閉型財務危機的預警訊息』；反之，他們認為『公司治理資訊才能提供投資人惡性倒閉型財務危機的預警訊息』。值得吾人注意的是：這種論點只是經由個案觀察得到的看法，並未經過縝密的思辨與實證研究。 本文擬用會計資訊及公司治理資訊，運用吉布斯抽樣方法，建立離散時間涉險預測模型，來預測惡性倒閉型財務危機。 en_US dc.description.abstract (摘要) This study attempts to establish a bankruptcy prediction model for fraudulent financial distress by using Gibbs sampler to identify predictors. I propose to divide financial distress into two categories, fraudulent financial distress and poor-performance financial distress, since they may have different suitable bankruptcy prediction models. In addition, I employ Gibbs sampler, a Bayesian approach, to identify predictors of bankruptcy prediction model for fraudulent financial distress since it provides some advantages over classical methods in identifying predictors for studies with small sample size and relatively huge number of candidate predictors. From time to time, bankruptcy scandals occur in our economic society and cause the society huge costs, such as Procomp (博達) scandal in 2004 and Rebar Group (力霸) scandal in 2006. The former costs the society 5 billion dollars and the latter 7.31 billion dollars. The Rebar Group had avoided watching for 8 years during 1998-2006. Thus a powerful prediction model for bankruptcy scandal, other than for general bankruptcy, is much needed in this circumstance. Up to now, we have several modern credit-risk model such Merton model, KMV model, Creditrisk model and so on. Some models rely on market price information which may be still high before bankrupt for these bankruptcy scandals. On the other hand, some models using accounting information such as Z-score model (Alteman 1968) has been under criticism although it has been popular for decades. 葉銀華 (2002, 2004, 2005) criticize the useless of accounting information in predicting bankruptcy scandals while emphasizing corporate governance information. As an accounting research, I argue that the bankruptcy scandals are usually under way for years before bankruptcy occurs and the accounting information is still useful in predicting bankruptcy. Therefore, for fraudulent bankruptcy financial distress, from accounting perspective, I propose to search for potential useful accounting variables and corporate governance variables to be included in the model in the following procedure: (1) read the court investigation report and identify the accounting variables which may be fraud-affected, (2) use Gibbs sampler to stochastically search for useful variables from huge number of potential ones, (3) build fraudulent bankruptcy prediction model by applying discrete-time survival model and (4) conduct cross-validation. en_US dc.language.iso en_US - dc.relation (關聯) 基礎研究 en_US dc.relation (關聯) 學術補助 en_US dc.relation (關聯) 研究期間:9708~ 9807 en_US dc.relation (關聯) 研究經費:333仟元 en_US dc.subject (關鍵詞) 經濟;會計;公司治理;預測惡性倒閉 en_US dc.title (題名) 會計資訊與公司治理資訊在預測惡性倒閉事件的相對有用性 zh_TW dc.title.alternative (其他題名) Predicting Fraudulent Bankrupt---Accounting Informaiton vs. Corporate Governance Information en_US dc.type (資料類型) report en
