基于期望违约率模型的上市公司财务困境预警研究

Abstract

Abstract: According to modern capital structure theory and option theory,designating that the price of assets is less than debt received by listed firms as the indicator of financial distress(FD),the paper designs the Expected Default Frequency(EDF)model using publicly available financial data and the information index of the capital market,i.e.price of the stock.The model can dynamically predict FD in listed firms and overcome the weakness of statistics models.

Key words: expected default frequency, listed firms, financial distress, prediction

CLC Number:

F275

LI Bing-xiang, . The Research of Predicting Financial Distress in Chinese Listed Firms Based on Expected Default Frequency Model[J]. Chinese Journal of Management Science, 2004, (5): 12-16.

References

[1] Altman E I. Edward. Financial ratios, discriminant analysis and the prediction of corporate bankruptcy[J]. The Journal of Finance, 1968,23: 589 - 609.
[2] Eisenbeis R A.Pitfalls in the application discriminant analysis in business and economics[J]. The Journal of Finance,1997,32: 875 - 900.
[3] Eiusenbeis R A.Pitfalls in the application of neural networks:the case of bank failure prediction[M]. Management Sciences, 1992,38 ( 1 ): 926 - 947.
[4] Zavgren, C.V.A logistic Analysis of the Relationship Between Vulnerability to Failure and Certain Financial Variable for American Industrial Firms [D].Working paperno. 796, Krannert Graduate School of Management, Prudue University, 1982.
[5] Tam K Y, Kiang M. Managerial application of neural networks:the case of bank failure prediction[M]. Management Sciences, 1992,38(1) :926 - 947.
[6] Frydman H,Altman E I,Kao Duen- Li. Introducing recursive partitioning for financial classification: the case of financial distress[J]. The Journal of Finance, 1985,40 ( 1 ):269 - 291.
[7] Robert C. Merton. On the Pricing of Corporate Debt: The Risk Structure of Interest Rates [J].Journal of Finance,1974,28: 449 - 470.
[8] Modigliani. F. and Miller, M. H. ,The Cost of Capital, Corporation Finance and the Theory of Investment [J].The American Economic Review, 1958,53: 261 - 297.
[9] 陈小悦.资本结构和企业价值[J].国际财务与会计,1997,1(4) :34.
[10] John C. Hull, Option, futures and other derivatives 3rd [M]. Prentice - Hall International, Inc. 1997:232 - 235.
[11] Scott. J. The Probability of Bankruptcy:A Comparison of Empirical Predictions and Theoretical Model[J]. Journal of Banking and Finance, 1981,5:317 - 344.
[12] Black. F and M. Scholes. The Pricing of Options and Corporate Liabilities[J].Journal of Political Economy, 1973(5- 6) :637 - 654.
[13] 参见中国证券报1998年3月16日"关于上市公司状况异常期间的股票特别处理方式的通知"的第1条.在2000年4月深沪证交所对财务状况异常情况地界定进行了补充说明(详见深圳/上海证券交易所股票上市规则,2000).
[14] 梁世栋,李勇,方兆本.信用风险模型比较分析[J].中国管理科学,2002,10(1):17-22.

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The Research of Predicting Financial Distress in Chinese Listed Firms Based on Expected Default Frequency Model

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