本國銀行危機預警機制之探討

A Study on the Early Warning System of Banking Industry

蕭志強(Jyh-Chyang Shiau)

指導教授 ： 洪振義

朝陽科技大學/管理學院/財務金融系/碩士(2010年)

摘要

2007年下半年爆發美國次級房貸風暴，導致全球經濟大幅衰退，金融監理已成為全球重要的課題。鑒於以往我國金融監理單位係依照CAMELS為架構制定預警模型，為驗證此架構是否仍具預測能力，並探討哪些財務指標對銀行經營具顯著性影響，本研究以2008年底還存在之37家本國商業銀行為研究對象，分別利用2005年至2007年(原始樣本)及2008年(預測樣本)各銀行年底資料進行前後期對照比較，並參採國內外學者及金融監理單位常用的財務變數，依主要成份因素分析法篩選變數後進行Logit迴歸模型分析，結果得知以CAMELS架構建立的模型仍具預測能力，惟在面臨2008年經濟金融環境不穩定的情況下，其預測能力則稍嫌不足。
另外本研究分別於原始樣本及預測樣本中再各自建立二組模型，即模型1(未加入董監事持股狀況因素)，模型2(加入董監事持股狀況因素)，經研究結果得知原始樣本中模型2之預測分類正確率94.6%較較模型1之91.9%為高，且在預測樣本中，模型2之預測分類正確率為89.2%相較模型1之78.4%更大幅提升，顯示加入董監事持股狀況因素除了可有效提升銀行危機預警能力外，在經濟金融環境不穩定的情況下更具明顯作用。

關鍵字

財務預警 ； 董監事持股 ； 金融預警系統 ； CAMELS

並列摘要

By late 2007, the US sub-prime mortgage crisis has led to decline sharply the global economy. Consequently, financial overseeing has become the important issue. Accordingly the commercial banks proceeded with CAMELS as the early warning model in Taiwan, it is important to verify CAMELS whether still has the predictable function, and to discuss which financial indicator has the obvious effect of the commercial banks’conduct.

This research based on 37 domestic commercial banks that conducted well at the end of 2008. It has adopted academic and practical methodology of financial variables to compare with information during the adjacent periods that individually selected primitive sample (2005, 2006, and 2007) and forecast sample (2008). As a result, we empirically evaluated that can predict efficient on Principal Components Factors Method and Logit Regression Analysis by CAMELS construction. However, it cannot apply in the unstable situation such as global financial crisis.

Furthermore, this study individually established two models in the primitive sample and the forecast sample, namely the model 1 (excl. ownership holding), the model 2 (incl. ownership holding). We discover the accuracy of forecast is 94.6% from the model 2 better than 91.9% of the model 1 in the primitive sample. In the model 2 of the forecast sample, its classification accuracy of 89.2% has larger promotion comparing with the model 1 of 78.4%. The results demonstrate that during unstable economy we include ownership holding could reach the possibility to upgrade the commercial banks’ abilities to forewarn financial crisis more efficiently.

並列關鍵字

Early warning system ； Financial warning ； CAMELS ； Ownership holding

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