未來研究方向 - 研究限制與未來研究方向 - 運用資料採礦技術及企業評價模式建立投資策略之研究-以台灣上市櫃非金融類公司為例

5.3 研究限制與未來研究方向

5.3.2 未來研究方向

1、本研究分析以『橫斷面分析』為主，可導入以時間序列預測為主的資料採礦技術從『縱斷面分析』，以加強預測之效果。

2、運用資料採礦技術預測評價因子，再套入評價模式，以求出更精確的企業價值。

3、可導入非財務類之『量化』數據分析，以加強預測之效果。

4、建構以季報財務資訊為基礎之資料採礦企業評價模式，補充年報資訊之不足。

六、參考文獻

中文部份：

1. 「TEJ 投資評等專文」，貨幣觀測與信用評等，第 11~17 期

2. 李智霖「利用不同分類模式探討財務危機預警模式之建立」，銘傳大學資訊管理研究所，碩士論文，2005

3. 吳啟銘，企業評價-個案實證分析，初版，智勝文化，2000

4. 林炯垚，企業評價-投資銀行實務，禾豐企業發展文教基金會，1999

5. 俞海琴，葉宜生，「價值投資法於台灣股市適用性之研究-電子產業與非電子產業之配對比較」，風險管理學報，第三卷第一期，5 月，pp.99-121，2001

6. 黃舜德，企業財務分析－企業價值的創造及評估，華泰文化事業，1998 7. 郭敏華，企業分析與評價，3 版，華泰文化事業，2005

8. 「對上市公司財務業務平時及例外管理處理程序」，台灣證券交易所股份有限公司，2007

9. 魏曉琴，「財務危機預警模型之研究-以台灣地區上市公司為例」，國立交通大學財務金融研究所，碩士論文，2004

英文部份：

1. Altman, Edward, “Discriminant analysis and the prediction of corporate bankruptcy”, The Journal of Finance, Vol. 23, No. 4, pp 589-609, 1968.

2. Altman, E.I., Haldeman, R. G. and Narayanan, P, “Zeta Analysis, a NewModel for

Identifying Bankruptcy Risk of Corporation”, Journal of Banking andFinance, Vol. 1, No.

1, pp.29-54., 1977

3. Black, F. and M. Scholes, “The Pricing of Options and Corporate Liabilities,”Journal of Political Economics ,81,pp637-659. , 1973

4. Beaver, William H., “Financial ratios as predictors of failure”, Journal of Accounting Research, pp.71-111, 1966.

5. Brachman, R. and T. Anand, “The Process of Knowledge Discovery in Databases: A Human Centered Approach, in AKDDM”, AAAI/MIT Press, pp.37-58, 1996

6. Berry, M.J.A. and Linoff, G., Data Mining Techniques for Marketing, Sales, and Customer Support, Wiley, New York, 1997.

7. Chan, L. K., Hamao, Y. ＆ Lakonishok, J.,”Fundamentals and stockreturns in japan”,.

Journal of Finance, 46（5）,pp 1739-1764.,1991

8. Chye, K.H. and Grey, C.K.L, “Data mining and customer relationship marketing in the banking industry”., Singapore Management Review, 24(2),pp 1-27., 2002

9. Carven,M.W.,Shavlik,J.W.,”Using neural networks for data mining” Future Generation Computer System,13,pp.221-229, 1997

10. Cabena, P., Hadjnian, Stadler, Verhees, Zanasi, Zanasi , A., “Discovering Data Mining from Concept to implementation”, Prentice Hall PTR. , September,1997

11. Copeland Tom., Tim Koller, and Jack Murrin, VALUATION, Mckinsey & Company, Inc, 1995

12. Chen, Shimin. & Dodd, James L., “Economic value added：An empirical examination of a new corporate performance measure”, Journal of Managerial Issues, pp.318-333.,1997 13. Copeland,T.,Koller, and J.,Murrin,Valuation：Measuring and Managing the Value of

Companies, John Wiley and Sons, Inc.,2000

14. Fisher Kenneth L., Super Stock, Homewood, I11. Dow Jones-Irwin,1984

15. Fama, E. F. ＆ French, K. R..,”The cross-section of expected stockreturns”,. Journal of Finance, 47（2）,pp 427-465.,1992

16. Fayyad, U M., Piatetsky-Shapiro, G. and Smyth, P., “The KDD Process for Extracting Useful Knowledge from Volumes of Data”, Communications of theACM, Vol. 39, pp.

27-34., 1996

17. Fayyad, U.M., Piatetsky-Shapiro,G. and P. Smyth, “From data mining to knowledge discovery: an overview, in: U.M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, R.

Uthurusamy (Eds)”, Advances in Knowledge Discovery and Data Mining, MIT Press, Massachusetts,Chap. 1. 1996,

18. Frawley,W., Piatetsky-S.G., and Matheus,C.,”Knowledge discovery in databases: an overview”, AI Magazine,Fall,213-228. ,1991

19. .Frawly, W. J., Paitetsky S. G. and Matheus, C.J.,”Knowledge Discovery in database: An Overview, Knowledge Discovery in Database”, California AAAI/MIT Press, 1-30.,1991 20. Han, J., Data Mining in J. Urban and P. Dasgupta (eds.), “Encyclopedia of Distributed

Computing”, Kluwer Academic Publishers., 1999

21. Han , J. and Kamber, M.,”Data Mining: Concepts and Techniques”, Hardcover Ed:

Morgan Kaufmann, 2001.

22. Lieber, Ronald. B.,“Who are the real wealth creators?” ,Fortune, Vol.134(Dec), pp.73-78., 1996

23. Lev B. and Thiagarajan S.R. Autumn. “Fundamental Information Analysis.” Journal of Accounting Research., 1993

24. Michael C J. “Agency cost of free flow, corporate finance, and takeovers[J]”. American Economic Review.,pp70-75. , 1986

25. Martin, Daniel. “Early Warning of Banking Failure”, Journal of Banking and Finance, pp 249-276., 1977

26. Norton Greenfeld,”Data Mining”, UNIX Review, Vol. 14, No. 5, pp.9-14, 1996 27. Ohlson, James A., “Financial ratios and the probabilistic prediction of bankruptcy”,

Journal of Accounting Research, Vol. 18, No. 1, 1980.

28. Palepu, K.G.,Bernard, V.L. and Healy,P.M., “Business Analysis and Valuation,”

2nd,South Western College Publish , 2000.

29. Pyle,D.Data Preparation for Data Mining., San Fransisco:Morgan KaufMann.,1999 30. Reilly Robert F.and Schweihs Robert P., “Valuationof accounting practices”, The Ohio

Capital Journal. ,1990

31. Rosenberg, B., Reid, K. ＆ Lanstein, R..,”Persuasive evidence of marketinefficiency”, Journal of Portfolio Management, 11（3）,pp 9-16. ,1985

32. Reinschmidt.J.,Gottschalk,H., Kim, & Zwietering,D.”Intelligent Miner for Data:Enhance Your Business Intelligence”.,North Carlina: IBM International Technical Support

Organization., 1999

33. Reinschmidt J., Bhattacharya R., Harris P., & Karanasos A., “Mining Relational and Nonrelational Data with IBM Intelligent Miner for Data”, Appendix B,189~193., 1998.

34. Rygielski, C., Wang, J.-C., Yen, D.C., “Data mining techniques for customer relationship management”., Technology in Society ,.24(4),pp 483-502., 2002

35. Thearling, K., “Increasing customer value by integrating data mining and campaign management software”, Direct Marketing Magazine., February ,1999

網站資料：

http://www.crisp-dm.org/index.htm.,2003

附件 1 相關分析總表

全部案例負報酬案例正報酬案例 NOPLAT 0.044 0.040 0.029 0.080 0.053 0.033 -0.019 -0.005 -0.004 ROS 0.043 0.040 0.040 0.046 0.031 0.037 0.025 0.055 0.048 營業利益率％ 0.041 0.035 0.033 0.043 0.028 0.038 0.013 0.020 -0.003 現金股利率 0.041 0.050 0.048 0.202 0.137 0.110 -0.081 -0.037 -0.035 每人營業利益（千元） 0.128 0.101 0.087 0.187 0.116 0.086 0.057 0.037 0.039

全部案例負報酬案例正報酬案例公司市值 0.022 0.012 -0.003 0.065 0.013 -0.017 -0.038 -0.027 -0.023 業外收支率％ 0.022 0.029 0.013 0.158 0.102 0.054 0.006 0.018 0.001 應收帳款週轉率(次) 0.022 0.025 0.019 0.039 0.005 0.020 -0.007 0.013 0.004 營收 0.021 0.012 0.001 0.067 0.037 0.008 -0.039 -0.032 -0.028 非附息負債總額 0.020 0.014 0.002 0.052 0.021 -0.001 -0.033 -0.023 -0.020 速動比率％ 0.019 0.003 0.002 0.090 0.024 0.014 -0.028 -0.031 -0.023 利息保障倍數 0.006 0.006 0.006 0.024 0.003 -0.010 -0.014 -0.004 0.005 長期資金適合率(A)％ 0.004 0.003 0.003 -0.013 -0.010 -0.013 -0.005 -0.001 0.005 稅率(B)％ 0.003 -0.013 -0.025 -0.009 -0.002 0.001 -0.003 -0.025 -0.042

全部案例負報酬案例正報酬案例存貨週轉率(次) 0.001 -0.004 0.002 0.019 -0.003 -0.008 -0.021 -0.020 -0.006 投入資本 -0.001 -0.006 -0.010 0.054 0.023 0.005 -0.058 -0.046 -0.039 應收帳款收現天數(天) -0.024 -0.027 -0.029 -0.049 -0.035 -0.016 -0.010 -0.017 -0.031 存貨應收帳款／淨值 -0.024 -0.021 -0.014 -0.143 -0.091 -0.041 0.055 0.044 0.033 應付帳款付現天數(天) -0.027 -0.023 -0.009 -0.083 -0.038 -0.011 -0.009 -0.012 0.000 權益資金成本 -0.028 -0.049 -0.042 -0.054 -0.025 -0.078 -0.016 -0.061 -0.013 或有負債/淨值 -0.031 -0.033 -0.036 -0.055 -0.040 -0.032 -0.001 -0.014 -0.030 研究發展費用率％ -0.032 -0.021 -0.021 -0.056 -0.025 -0.044 0.021 0.020 0.037 平均銷售天數(天) -0.040 -0.039 -0.016 -0.083 -0.051 -0.001 -0.006 -0.019 -0.013 淨營業週期(天) -0.043 -0.043 -0.023 -0.084 -0.054 -0.003 -0.008 -0.023 -0.025 總負債/總淨值％ -0.044 -0.050 -0.028 -0.139 -0.101 -0.054 0.019 -0.004 0.020 借款依存度％ -0.059 -0.064 -0.049 -0.165 -0.119 -0.058 0.055 0.010 -0.004 營業費用率％ -0.061 -0.058 -0.040 -0.113 -0.072 -0.039 -0.023 -0.032 -0.019 用人費用率％ -0.062 -0.041 -0.019 -0.054 -0.029 -0.001 -0.054 -0.024 -0.011 負債比率％ -0.063 -0.046 -0.032 -0.190 -0.113 -0.055 0.041 0.041 0.028

附件 2 個股分析總表

等距

在文檔中運用資料採礦技術及企業評價模式建立投資策略之研究-以台灣上市櫃非金融類公司為例 (頁 73-123)