營建業財務危機預測模型之建立

DYNAMIC PREDICTION MODEL FOR FINANCIAL DISTRESS IN CONSTRUCTION INDUSTRY USING DATA MINING

林芳瑩(Fang-Ying Lin)

指導教授 ： 荷世平

國立臺灣大學/工學院/土木工程學研究所/碩士(2004年)

https://doi.org/10.6342/NTU.2004.02373

摘要

本研究以營建業之公司財務作為研究變數，並分別以Bever(1966)之二分類選擇法(Binary Choice)與財務危機前五年作為財務危機定義，進行模型建立；研究方法為CART決策樹(Decision Tree)，目的在於選取財務危機各階段預測之重要變數以進行預測，最後再以模型穩定度與準確性評選營建業財務危機預測之模型。本研究期能提供營建業者自我省察財務狀況之指標，並作為資金提供者之信用評估指標，進而降低營建業財務危機之發生，鞏固營建業與金融體系財務之健全。

關鍵字

營建業 ； 資料採擷 ； 財務危機 ； CART決策樹演算法

並列摘要

The early awareness of a potential financial distress is crucial to firm’s managers for understanding their clients, suppliers and their own firms, and crucial to fund suppliers for assessing the construction firm’s credit worthiness. The purpose of this paper is to develop a dynamic prediction model for financial distress in construction industry using Data Mining. This research expects to provide construction firm managers and creditors an effective index for evaluating the credit risk a construction firm. Results show that the proposed model has higher accuracy and stability for distress prediction and can provide a more effective quantitative framework for evaluating the financial standing of a construction firm.

並列關鍵字

CART ； Construction Industry ； Data Mining ； Financial Distress ； Distress Prediction

參考文獻

1. Beaver, W.H. (1966), “Financial ratios as predictors of failure.” J. of Accounting Research, 4(3), 71-112.

2. Altman, E.I.(1968), “Financial ratios, discriminant analysis and the prediction of corporate bankruptcy”, Journal of Finance, 23, 589-609.

3. Altman, E.I., R.G. Haldeman, and P. Narayanan(1977), “Zeta analysis: A new model to identify bankruptcy risk of corporations”, Journal of Banking &Finance 1, 29-51.

5. Beaver, W.H.(1966),”Financial ratios as predictors of failure”, Journal of Accounting Research 4, 71-111.

7. Black, F. & Scholes M.(1973) “The Pricing of option and corporate liabilities”, Journal of Political Economy, No.81, pp.637-59.