建立台灣一般銀行之金融預警系統

Financial Early Warning System Models of Taiwanese Banks

陳康容(Kang-Rung Chen)

指導教授 ： 黃志祥

國立虎尾科技大學/管理學院/經營管理研究所/碩士(2010年)

摘要

自1980年後，台灣逐漸開放對銀行嚴格的控管，新銀行陸續的成立，銀行業競爭激烈，且政府積極強化金融監理制度及金融改革法案的實施，在面臨金融環境快速的變化，銀行做好風險管理成為重要的課題。
本文以2004年至2008年之33家本國一般銀行為研究對象，利用CAMELS評等原則以評估銀行經營績效之優劣，並採用Logit迴歸分析建立非風險性預警模型及風險性預警模型，期藉此提供監理檢查單位及相關金融機關之參考。
經由實證研究發現：
(1)經由因素分析篩選後之變數，符合CAMELS準則(即資本適足性、資產品質、管理效率、獲利能力、流動性及市場敏感度)，即表示研究中可客觀地評估各銀行之經營績效，供相關機構及投資者參考。
(2)以Logit迴歸分析建立原始樣本模型之預測能力分別為：非風險性模型A為72.73%，風險性模型B為78.79%。而預測樣本模型之預測能力分別為：非風險性模型A為90.91%，風險性模型B為96.97%。
(3)以CAMELS建立之非風險性預警模型具有良好之預測能力，而加入風險性指標後，其預警模型在預測能力及型I誤差上皆較非風險性預警模型來得佳。

關鍵字

預警模型 ； CAMELS ； 風險性指標 ； 因素分析 ； Logit迴歸分析

並列摘要

Since 1980, Taiwan’s government relaxes restrictions of banks gradually, new banks establish induce the competition intense in bank-industry. And government strengthened banking supervision and practiced financial reform bills actively. Therefore, banks to face the sudden changes in the financial environment that management of risk is an important issue.
This article using financial information among 33 domestic banks from first season in 2004 to the fourth season in 2008, using CAMELS ratings to assess the bank operating performance. The early warning model using Logit regression analysis to set up the non-risk model and risk model. That can be reference for financial inspection units and related financial institutions. The Empirical research results indicate as follows：
(1) Select by factor analysis variables that consistent with CAMELS (Capital Adequacy、Asset Quality、Management、Earning、Liquidity、Sensitivity to market risk) that means this article can objectively evaluate the bank performance. Hence, that can reference for the relevant institutions and investors.
(2) Use Logit regression analysis set up original sample models that prediction ability are：non-risk model A is 72.73% and risk model B is 78.79%. Predictive sample models of prediction ability：non-risk model A is 90.91% and risk model B is 96.97%.
(3) The CAMELS of non-risk models has good predictive ability, the model add risk indicators that predictive ability and type I error work better than non-risk models.

並列關鍵字

Financial Early-Warning System models ； CAMELS rating ； risk indicators ； factor analysis ； Logit regression analysis

參考文獻

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