臺灣博碩士論文加值系統

企業發生財務危機的主要原因可歸為財務結構不良與經營效率不彰兩大類，因此本文除了考量到財務變數、公司治理變數之外，並使用隨機邊界法來衡量企業的技術效率值與成本效率值作為經營變數，且加入支援向量機模型來與傳統研究常用之Logit模型與類神經網絡模型針對2000年1月到2010年12月符合財務危機定義加上配對樣本共264家上市公司進行預測與差別比較，並特別使用多重分類支援向量機模型來區分不同類型之財務危機。
最後實證結果顯示，危機公司與正常公司在經營效率之間確實存在差距，且加入不同經營績效變數對預測財務危機能力皆有所不同；在各衡量變數下，以Logit模型以及SVM這兩種模型較具有預測能力。另比較在四種不同衡量變數之下(包含兩種經營效率值)，也顯示出預測財務危機發生的前兩季最為準確；最後由多重分類支援向量機模型搭配財務、公司治理、成本效率混和變數皆能完全有效分類正常、重整、紓困、跳票擠兌與繼續經營疑慮這五種財務危機類型。

The main cause of financial distressed of enterprise could be the malfunction of financial structure and management inefficiency. Therefore, besides considering financial variable and corporate governance variable, the study also use stochastic frontier approach to measure the techical efficiency and cost efficiency of enterprise for efficiency variable. In addition to adopt Logit model and Neural Network model, the study also adds in support vector machines. These models are used to focus on 264 listed companies which match the definition of financial distressed to proceed prediction and different comparison on January to December, 2000. The multi-class support vector machines is also specially used to class the different types of financial crises.
The experiment results reveal that the distressed companies and normal operation companies do exist differences in management efficiency. Adding different efficiency variable to predict the ability of financial distressed also lead to different results. Comparing to different measuring models, Logit models and SVM models are the best prediction method. Furthermore, comparing the four different measure variable, including two management efficient value, these also show the financial distressed are best predicted in the first two quarters. Last, with the use of multi-class support vector machines, financial, corporate governance and cost efficiency mixed variable are able to categorize five financial distressed models efficently, these are normal, restructure、bailout、Bounced check and run, and going-concern opinion.

目　　錄
中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
表目錄 v
圖目錄 vi
第一章 緒論 1
1.1 研究動機 1
1.2 研究目的 3
1.3 論文架構 3
第二章 文獻探討 5
2.1 企業財務危機定義 5
2.2 財務危機預警模式 7
2.3 經營績效與財務危機之關聯性 32
第三章 研究方法 34
3.1 研究設計與架構 34
3.2 研究期間與樣本資料來源 36
3.3 實證變數之定義 36
3.4 各變數之操作型定義 44
3.5 研究方法 44
第四章 實證結果與分析 60
4.1 樣本處理 60
4.2 變數篩選 65
4.3 Logit迴歸、倒傳遞類神經與支援向量機之實證結果比較 69
4.4 多重分類支援向量機之實證結果 101
第五章 結論與建議 104
5.1 結論 104
5.2 後續研究建議 108
附　　錄 116

參考文獻
書籍
[1] Foster. G, Financial statement analysis, 2nd Edition, Prentice-Hall International
Editions，1986.
[2] V. N. Vapnik, The Nature of Statistical Learning Theory, Springer-Verlag, New
York, ISBN 0-387-94559-8，1995.
期刊論文
[3] 林基煌，「財務危機之預防與管理」，今日會計，第74期，1999，第2-9頁。
[4] 林淑萍、黃劭彥、蔡昆霖， 「企業危機預警模式之研究---
DEA-DA、Logit迴歸與類神經網路之應用」，會計與公司治理，第四卷，第1期，2007，第35-56頁。
[5] 高淑珍、張海清、顏旭良，「台灣高科技產業之核心資源、資源配置策略
與經營績效之關聯性分析」，台北科技大學學報，第三十五之一期，2001，
第261-280頁。
[6] 張大成、周麗娟、黃筱雯，「經營效率與企業危機相關性研究」，信用資訊
月刊，第四卷，第二期，2008，第1-2頁。
[7] 鄭文英、蘇恩德、李勝榮、何慧清，「財務危機預警模式建構影響因素與
預測能力之整合分析」，中華管理評論國際學報，第11眷，第2期，2008，
第1-19頁。
[8] Altman. E. I, Financial Ratios, "Discriminant Analysis, and the Prediction of
Corporate Bankruptcy, "Journal of Finance, Vol. 23, No.4, 1968, pp.589-609.
[9] Altman. E. I. and Haldeman. R. and Narayanan. P, " ZETATM analysis: A new
model to identify bankruptcy risk of corporations, "Journal of Banking and
Finance, 1(1) , 1977, pp.29-54.
[10] Arindam. B. and Sanjiv. J, "An analysis of second time around bankruptcies
using a split-population duration model, "Journal of Empirical Finance, 8,
2001, pp.201–218.
[11] Baldwin. C. and Scott. M, "The resolution of claims in financial distress: the
case of Massey Ferguson, " Journal of Finance, Vol. 38, 1983, pp.505-516.
[12] Balcaen. S. and Ooghe. H, "35 years of studies on business failure: An
overview of the classic statistical methodologies and their related problems,
"The British Accounting Review, 38(1), 2006, pp.63-93.
[13] Beaver. W. H, "Financial ratios as predictors of failure. Journal of Accounting
Research, " 4(3) , 1996, pp.71-111.
[14] Bettese. G. E. and Coelli. T. J, "Frontier Production Functions, Technical
Efficiency and Panel Data: With Application to Paddy Farmers in India," The
Journal of Productivity Analysis, 3 , 1992, pp.153-169.
[15] Blum. M, "Failing company discriminant analysis, " Journal of Accounting
Research, l2(1), 1974, pp.1-25.
[16] Bongini. P. and Laeven. L. and Majnoni. G, "How Good Is the Market at
Assessing Bank Fragility? A Horse Race between Different Indicators, "
Journal of Banking and Finance, 26, 5, 2002, pp.1011-1028.
[17] Cebenoyan. A. S. and E. S. Cooperman. and C. A. Register , "Firm
Efficiency and The Regulatory Closure of S&Ls: An Empirical Investigation, " The Review of Economics and Statistics, 1993, pp.540-545.
[18] Cipollini. A. and Kapetanios. G, "Forecasting financial crises and contagion in
Asia using dynamic factor analysis, " Journal of Empirical Finance, 16, 2009,
pp.188–200.
[19] Coats. P. K. and Fant. L. F, "A Neural Network Approach to Forecasting
Financial Distress, " Journal of Business Forecasting (10), 1991, pp.9-12.
[20] Collins. R. A. and Green. R. D, "Statistical Method for Bankruptcy
Forecasting, " Journal of Economics and Business, Vol.34, No.4, 1982,
pp.349-354.
[21] Cybinski. P, Description, "explanation, prediction – the evolution of
bankruptcy studies?, " Managerial Finance, 27(4), 2001, pp.29-44.
[22] Daniel. H. and Bernd. Kempa. and Christian. Pierdzioch, "Economic and
financial crises and the predictability of U.S. stock returns, " Journal of
Empirical Finance, 15, 2008, pp.468–480.
[23] Deakin. E, " A discriminate analysis of prediction of business failure, "
Journal of Accounting Research, 1972, pp.167-169.
[24] Gentry. J. A. and Newbold. P. and Whitford. D. T, "Funds Flow Components,
Financial Rations, and Bankruptcy, " Journal of Business Finance &Accounting, Vol.14, No.4, 1987, pp.595-606.
[25] Harry. D. and Linda. D, "Dividend Policy and Financial Distress: An Empirical Investigation of Troubled NYSE Firms, " The Journal of finance , 45, 1990, pp.1415-1431.
[26] Hopwood. W. and Mckeown. J. C. and Mutchler. J. F, "A Reexamination of Auditor versus Model Accuracy Within the Context of the Going-Concern Opinion Decision, " Contemporary Accounting Research, Vol. 10, 1994, pp.409-431.
[27] Hsin. H. C, "The Timescale Effects of Corporate Governance
Measure on Predicting Financial Distress, " Review of Pacific Basin Financial Markets and Policies, Vol. 11, No. 1, 2008, pp.35–46.
[28] Huang. C. J. and J. T. Liu, "Estimation of Non-Neutral Stochastic Frontier Production Function, " Journal of Productivity Analysis, 5, 1994, pp.171-180.
[29] Huang. Hui. and Zhao. Jin. Jing, "Relationship between Corporate
Governance and Financial Distress: An Empirical Study of Distressed Companies in China, " International Journal of Management, Vol. 25, No. 3, 2008, pp.654-664.
[30] Ilia. D. D, "Is the Risk of Bankruptcy a Systematic Risk?, " The Journal of
finance, Vol. LIII, NO. 3, 1998, pp.1131-1147.
[31] Jozef. M. Z. and Benjamin. P. F. and Terry. J. Ward. and Robert, M. Barker, "Neural Networks Versus Logit Regression Models For Predicting Financial Distress Response Variables, " Journal of Applied Business Research, Vo1. 15, No1, 1999, pp.21-29.
[32] Kuruppu. N. and Laswad. F. and Oyelere. P, "The efficacy of liquidation and
bankruptcy prediction models for assessing going concern, " Managerial
Auditing Journal, 18(6/7), 2003, pp.577-590.
[33] Lu. Yang. Cheng. and Chang. Shu. Lien, "Corporate Governance and Quality
of Financial Information on the Prediction Power of Financial Distress of
Listed Companies in Taiwan, " International Research Journal of Finance &
Economics, 2009, pp.114-135.
[34] Matthias. K, Economic Distress, "Financial Distress, and Dynamic Liquidation, " The Journal of finance, Vol. LVII, NO. 1, FEB, 2002, pp.135-168.
[35] Mensah. Y. M, "An examination of the stationary of multivariate bankruptcy
prediction models: A methodological study, " Journal of Accounting Research
22(1), 1984, pp.380-395.
[36] Ming-Yuan. L. L. and Peter. M, "A hybrid bankruptcy prediction model with
dynamic loadings on accounting-ratio-based and market-based information: A
binary quantile regression approach, " Journal of Empirical Finance , 17 ,
2010, pp.818–833.
[37] Muller. G. H. and Steyn-Bruwer. B. W. and Hamman W. D, "Predicting
financial distress of companies listed on the JSE – A comparison of techniques, " S.Afr.J.Bus.Manage, 40(1), 2009, pp.21-31.
[38] Odom. M. D. and Sharda. R, "A Neural Network Model for Bankruptcy
Prediciton," IEEE/INNS, vol. 2, 1990, pp.163-168.
[39] Ohlson. J. A, "Financial Ratios and the Probabilistic Prediction of Bankruptcy, " Journal of Accounting Research, Vol.18, 1980, pp.109-131.
[40] Patrick. L. B. and Linda. L. G. and Jaeho. J. and Chuanhou. Y, "A comparison
of neural network, statistical methods, and variable choice for life insurers'
financial distress prediction, " The Journal of Risk and Insurance, Vol. 73, No.
3, 2006, pp.397-419.
[41] Platt. H. D. and Platt. M. B, "Development of a class of stable predictive
variables: The case of bankruptcy prediction, " Journal of Business Finance &
Accounting, 17(1), 1980, pp.31-51.
[42] Ran. B. and Robert. A. H, "Classifying Financial Distress in the Life Insurance
Industry, " The Journal of Operation Research, Vol.2, 1990, pp.429-444.
[43] Rose. P. S. and Andrews. W. T. and Giroux. G. A, "Predicting business failure:
A macroeconomic perspective, " Journal of Accounting, Auditing & Finance,
6(1), 1982, pp.20-31.
[44] Sandeep. D. and Anthony. S. and Anand. S, "Financial Distress and Bank
Lending Relationships, " The Journal of finance, Vol. LVII, NO. 1, FEB, 2003, pp.375-399.
[45] Steyn-Bruwer. B.W. and Hamman. W. D, "Company failure in South Africa:
Classification and prediction by means of Recursive partitioning, " South
African Journal of Business Management, 34(4), 2006, pp.1-12.
[46] Stijn. C. and Simeon. D. and Leora. K, "Resolution of corporate distress in
East Asia, " Journal of Empirical Finance, 10, 2003, pp.199– 216.
[47] Zmijewski. M. E, "Financial Ratio and the Probabilistic Prediction of
Bankruptcy, " Journal of Accounting Research, Vol. 22, 1984, pp.59-86.
會議論文
[48] A. Shigeo, "Analysis of Multiclass Support Vector Machines,"Internation Conference on Computational Intelligence for Modeling Control and Automation, 2003, pp385-396
學位論文
[49] 吳智鴻，結合基因演算法最佳化「支持向量機」參數-財務危機上之應用，
博士論文，台北大學企業管理研究所，台北，2003。
[50] 洪光宏，以經營效率觀點建立台灣資訊電子業財務危機預警模型，碩士論
文，逢甲大學會計學系，台中，2006。
[51] 徐明宜，技術效率與廠商規模－台灣電子產業之實證分析，碩士論文，中
央大學產業經濟研究所，桃園，1998。
[52] 徐銘甫，整合財務比率與資料包絡分析法於企業危機診斷模式之建構－約
略集合、支援向量機與決策樹之應用，碩士論文，中國文化大學會計研究
所，台北，2007。
[53] 陳明賢，財務危機預測之計量分析研究，碩士論文，政治大學管理科學研
究所，台北，1986。
[54] 陳肇榮，運用財務比率預測企業財務危機之實證研究，博士論文，國立政
治大學企業管理研究，台北，1983。
[55] 陳建賓，加入公司治理指標的企業財務危機預測研究：Logistic模型的應
用，碩士論文，淡江大學財務金融學系，台北，2004。
[56] 陳蘊如，財務危機預警制度之研究，碩士論文，國立政治大學會計研究，
台北，1991。
[57] 黃小玉，銀行放款信用評估模式之研究-最佳模式之選擇，碩士論文，淡江
大學管理科學研究所，台北，1988。
[58] 黃文隆，財務危機預警模型之建立與驗證，碩士論文，東吳大學商管研究
所，台北，1993。
[59] 黃建華，加入公司治理變數建構台灣上市上櫃公司之財務危機預警模型，
碩士論文，東吳大學國際貿易學系碩士班國際貿易金融組，台北，2006。
[60] 游聲裕，我國電腦及周邊產業企業經營績效剖析，碩士論文，成功大學企
業管理學研究所，台南，2000。
[61] 葉鴻祥，台灣上市資訊電子產業危機預警之研究:DEA與Logit模型之應
用，碩士論文，南華大學財務管理研究所，嘉義，2006。
[62] 楊浚泓，考慮財務操作與合併報表後之財務危機預警模式，碩士論文，國
立中央大學財務管理研究所，桃園，2001。
[63] 劉易昌，支援向量機於財務預測上之應用，碩士論文，靜宜大學資訊管理
學，台中，2004。
[64] 蔡秋田，運用類神經網絡預測上市公司營運困難之研究，碩士論文，國立
成功大學會計研究所，台南，1995。
[65] 潘玉葉，臺灣股票上市公司財務危機預警分析，碩士論文，淡江大學管理
科學研究所，台北，1990。
[66] 蘇莉萍，市場導向與生產效率－台灣製造業的實證研究，碩士論文，台灣
大學經濟學研究所，台北，1994。
[67] 蘇錦暉，企業危機的形成與預警模式之建立，碩士論文，國立中山大學管
理學院高階經營碩士學程在職專班，高雄，2009。
[68] 嚴玲敏，應用類神經網路建構一套財務危機預警系統，碩士論文，逢甲大.
學資訊電機工程碩士在職專班，台中，2007。
網路資料
[69] Wikipedia, 2008, Financial distress. [online] URL:
http://encyclopedia.thefreedictionary.com/Financial+distress Accessed 29 January .