[1]邓敏,韩玉启.基于数据推理和模式识别的财务困境预警模型[J].南京理工大学学报(自然科学版),2009,(06):833-838.
 DENG Min,HAN Yu-qi.Pre-warning Model of Financial Distress Based on Calculus Derivation and Pattern Recognition[J].Journal of Nanjing University of Science and Technology,2009,(06):833-838.
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基于数据推理和模式识别的财务困境预警模型
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
2009年06期
页码:
833-838
栏目:
出版日期:
2009-12-30

文章信息/Info

Title:
Pre-warning Model of Financial Distress Based on Calculus Derivation and Pattern Recognition
作者:
邓敏;韩玉启;
南京理工大学经济管理学院, 江苏南京210094
Author(s):
DENG MinHAN Yu-qi
School of Economics and Management,NUST,Nanjing 210094,China
关键词:
数据推理 模式识别 财务困境 预警模型
Keywords:
calculus derivation pattern recognition financial distress pre-warning models
分类号:
F275
摘要:
通过对比研究,指出了基于统计分析方法的传统财务困境预警模型的缺陷,分析了基于数据演算推理和模式识别的新兴财务困境预警模型的特点。对多个有代表性模型特点的分析表明,新兴的财务困境模型具有容错能力、动态适应性、人工智能和解释能力等特点,更适合目前公司错综复杂的财务状况。该文在分析结果的基础上,提出了财务困境预警问题未来的研究方向。
Abstract:
By contrastive study,the inherent defects of the traditional financial distress pre-warning(FDPW) models based on the traditional statistic analysis method are indicated.The characteristics of the novel models based on calculus derivation and pattern recognition developed recently are analyzed.The results from the analysis on the characteristics of several representative FRPW models show that the novel FDPW models own such characteristics as high fault tolerance ability,dynamic adaptability,artificial intelligence and explanation ability and are more suitable for the complicated financial evolution in modern companies.The future directions about the FRPW are also proposed here.

参考文献/References:

[ 1] AltmanE I. Corporate financial distress[M]. New York, USA: JohnWiley, 1993.
[ 2] WardT J, Foster BP. A note on select a response measure for financialdistress[ J]. JournalofBusiness Finance andAccounting, 1997, 24(6): 869- 879.
[ 3] 周首华,杨济华, 王平. 论财务危机的预警分析F 分数模式[ J]. 会计研究, 1996( 8): 8- 11.
[ 4] 陈静. 上市公司财务恶化预测的实证分析[ J]. 会计研究, 1999(4): 31-38.
[ 5] 张玲. 财务危机预警分析判别模型[ J]. 数量经济技术经济研究, 2000( 3): 49-51.
[ 6] 陈晓, 陈怡鸿. 中国上市公司的财务困境预测[ J]. 中国会计与财务研究, 2000(3): 55-72.
[ 7] 杨保安,季海. BP神经网络在公司财务危机预警之应用[ J]. 预测, 2001, 20(2): 9- 54.
[ 8] 黄继鸿, 姚武, 雷战波. 基于案例推理的企业财务危机智能预警支持系统研究[ J]. 系统工程理论与实践, 2003, 23( 12): 46-52.
[ 9] 曹德芳,夏好琴. 基于股权结构的财务危机预警模型构建[ J]. 南开管理评论, 2005, 8( 6): 85-90.
[ 10] 杨海军,太雷. 基于模糊支持向量机的上市公司财务困境预测[ J]. 管理科学学报, 2009, 12( 3): 102-110.
[ 11] 孙洁,李辉. 企业财务困境的多分类器混合组合预测[ J]. 系统工程理论与实践, 2009, 29(2): 78-86.
[ 12] Odour MD, Sharda R. A neural networkmodel for bankruptcy prediction[ J]. Conference onNeuralNe-t works, 1990, 2( 6): 136-138.
[ 13] Mar-Molinero C, TurnerM, BishopH. Multidimen-sional scaling analysis as a tool to explain company distress: The caseofmarks andspencer PLC[A]. 27
CongresoNacional de Estad?stica e Investigaci?nOp-erativa[ C]. Lleida, Espagne: Universitat deLleida, 2003. 8- 11.
[ 14] Kahya E, TheodossiouP. Predicting corporate finan-cialdistress: A time-seriesCUSUMmethodology[ J]. Review of Quantitative Finance and Accounting, 1999, 13(4): 323- 345.
[ 15] KahyaE, OuandlousAS, TheodossiouP. Serial cor-relation, non-stationary, anddynamic performance of business failurepredictionmodels[ J]. ManagerialF-i nance, 2001, 27( 8): 1- 15.
[ 16] SlowinskiR, ZopudinisC. Applicationof the rough set approachto evaluationof bankruptcy risk[ J]. In-telligent Systems inAccounting, FinanceandManage-ment, 1995, 4( 1): 27- 41.
[ 17] Tay FEH, ShenL. Economic and financial predic-tionusing rough setsmodel[ J]. EuropeanJournal of OperationResearch, 2002, 141( 3): 641- 659.
[ 18] Hunter J, IsachenkovaN. ApanelanalysisofUK in-dustrial company failure[ R]. CambridgeUK: ESRC Centre for Business Research, University of Cam-bridge. 2002. 228.
[ 19] ShinKS, LeeYJ. Agenetic algorithmapplicationin bankruptcy predictionmodeling[ J]. Expert Systems withApplications, 2002, 23( 3): 321-328.
[ 20] Varettto F. Genetic algorithms applications in the a-nalysisof insolvency risk[ J]. Journal of Banking and Finance, 1998, 22(3): 1421-1439.
[ 21] CatanachJAH, PerrySE. Anevaluationof thesurviv-almodel. s contribution to thrift institutiondistress pre-diction[ J]. Journal ofManagerial Issue, 2001, 8( 4): 401-417.
[ 22] Molina CA. Predicting bank failure using a hazard model[ J]. EmergingMarket Review, 2002, 3( 6): 31- 50.
[ 23] HonjoY. Business failure of newfirms: Anempirical analysisusing amultiplicative hazardmodel[ J]. In-ternational Journal of Industrial Organization, 2000, 18( 4): 557-574.
[ 24] ScapensRW, RyanRJ, Flecher L. Explaining corpo-rate failure: Acatastrophe theory approach[ J]. Jour-nalofBusinessFinance andAccounting, 1981, 8( 1): 1-26.
[ 25] Lindsay D H, Campbell A. A chaos approach to bankruptcy prediction[ J]. Journal of AppliedBus-i nessResearch, 1996, 12(4): 1-9.
[ 26] KiviluotoK, BergiusP. Exploring corporate bankrup-t cywithtwo-level sel-f organizingmap[A]. Proceedings of theFifth International Conference onComputational Finance[ C]. Boston, Massachusetts, USA: Kluwer AcademicPublishers, 1998. 373-380.
[ 27] CharitouA, Trigeorgis L. Option-based bankruptcy prediction( working paper) [ Z]. Nicosia, Cyprus: University of Cyprus, 2000.
[ 28] Cheo-lSoo P, IngooH. A case-based reasoning with the feature weights derived by analytic process for bankruptcy prediction[ J]. Expert SystemswithAp-plications, 2002, 23( 3): 255-264.
[ 29] SpanosM, DouniasG, MatsatsinisN, et a.l A fuzzy knowledge-based decision aiding method for the as-sessment of financial risk: The caseof corporatebank-ruptcy prediction[R]. GreteGreece: EuropeanSym-posiumon Intelligent Techniques ( ESIT), Orthodox Academy of Crete, 1999. 1-7.
[ 30] HillNT, Perry SE, AndesS. Evaluating firms inf-i nancial distress: Anevent history analysis[ J]. Jour-nal of AppliedBusiness Research, 1996, 12( sum-mer): 60- 71.
[ 31] GuptaY, RaoR, BagchiP. Linear goalprogramming asanalternative tomultivariate discriminate analysis: Snote[ J]. Journal of BusinessFinance andAccoun-t ing, 1990, 11( autumn): 593-598.
[ 32] MessierWF, Hansen JV. Including rules for expert systemdevelopment: An example using default and bankruptcy data[ J]. Management Science, 1988, 34( 2): 1403- 1415.
[ 33] ZopoudinisC. Amulticriteria decision-making meth-odology for the evaluationof the riskof failure andan application[ J]. Foundations of ControlEngineering, 1987, 12( 1): 45-67.
[ 34] ZopoudinisC, DimitrasAI. Multicriteriadecisionaid methods for the prediction of business failure[M]. Dordrecht, Holland: Kluwer AcademicPublishers, 1998.
[ 35] DoumposM, Zopoudinis C. Amulticriteria discrim-i nationmethodfor the prediction of financial distress: The case ofGreece [ J]. Multina-tionalFinance Jour-na,l 1999, 3( 2): 71- 101.

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备注/Memo

备注/Memo:
基金项目: 南京理工大学科研发展基金( XKF07070)
作者简介: 邓敏( 1968- ), 女,博士生, 高级会计师,主要研究方向: 管理理论与方法, E-mail:dengmin228@sohu. com;
通讯作者:韩玉启( 1945- ), 男,教授, 博士生导师, 主要研究方向:管理理论与方法, E-mail: he-i dihan@mail.njust. edu. cn。
更新日期/Last Update: 2012-11-19