基于多状态Markov模型的企业财务困境预测研究
Research on Financial Distress Prediction Based on Multi-State Markov Model
DOI: 10.12677/FIN.2018.84018, PDF,  被引量    国家科技经费支持
作者: 何 军：南京优速网络科技有限公司，江苏 南京；王新燕, 胡小平*：东南大学，经济管理学院，江苏 南京
关键词: 多状态Markov；财务困境；预测；Multi-State Markov； Financial Distress； Prediction
摘要: 本文基于多状态Markov模型，研究了涉农上市公司财务困境预测问题。首先，构建了多状态Markov模型。然后，基于得到的多状态Markov模型，又构建了以财务困境影响因素为协变量的指数模型。最后，利用得到的模型对上市公司财务困境从转移概率和停留时间两个方面进行了预测。研究结果表明，多状态Markov模型能够很好地应用于财务困境的预测，能够提示财务困境的演化过程。
Abstract: Based on the multi-state Markov model, the financial distress prediction problem of listed com-panies is studied. First, a multi-state Markov model is constructed. Then, based on the multi-state Markov model, we construct an exponential model with covariables of financial distress factors. Finally, the financial dilemma of listed companies is forecasted from the two aspects of transition probability and residence time. The results show that the multi-state Markov model can be applied to the prediction of financial distress and can reveal the evolution of financial distress.
文章引用：何军, 王新燕, 胡小平. 基于多状态Markov模型的企业财务困境预测研究[J]. 金融, 2018, 8(4): 154-160. https://doi.org/10.12677/FIN.2018.84018

参考文献

[1] Beaver, W.H. (1966) Financial Ratios as Predictors of Failure. Journal of Accounting Research, 4, 71-111. [Google Scholar] [CrossRef] 
[2] Altman, E.I. (1968) Financial Ratios Discriminant Analysis and the Prediction of Bankruptcy. Journal of Finance, No. 23, 589-609. [Google Scholar] [CrossRef] 
[3] Lau, A.H.-L. (1997) The Effects of Reducing Demand Uncertainty in a Manufacturer-Retailer Channel for Single-Period Products. Computers & OR (COR), 29, 1583-1602.
[4] Morris, A. (1997) Genetical Gorithms Applications in the Analysis of Insolvency Risk. Journal of Banking and Finance, No. 22, 1401-1409.
[5] Altman, E.I., Iwanicz-Drozdowska, M., Laitinen, E.K., et al. (2016) Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman’s Z-Score Model. Journal of International Financial Man-agement & Accounting, 28, 131-171. [Google Scholar] [CrossRef] 
[6] Liao, Q. and Mehdian, S. (2016) Measuring Financial Distress and Predicting Corporate Bankruptcy: An Index Approach. Review of Economic and Business Studies, 9, 33-51. [Google Scholar] [CrossRef] 
[7] 杨青龙, 田晓春, 胡佩媛. 基于LASSO方法的企业财务困境预测[J]. 统计与决策, 2016(23): 170-173.
[8] 蔡玉兰, 钱崇秀, 董雪杰. 财务报表信息对企业财务困境的预测能力[J]. 预测, 2016(5): 48-54.
[9] 邹清明, 黄钟亿. 基于比例优势模型的上市公司财务困境预测研究[J]. 数理统计与管理, 2016(3): 536-549.
[10] Serri, M., Caldarelli, G. and Cimini, G. (2016) How the Interbank Market Becomes Systemically Dangerous: An Agent-Based Network Model of Financial Distress Propagation. arXiv Preprint arXiv: 1611.04311.
[11] 李丽君, 刘杰, 孙世敏. 供应链视角下企业财务困境传递及控制问题研究[J]. 中国管理科学, 2016(6): 46-51.
[12] Bhaskar, L.S., Krishnan, G.V. and Yu, W. (2017) Debt Covenant Vi-olations, Firm Financial Distress, and Auditor Actions. Contemporary Accounting Research, 34, 186-215. [Google Scholar] [CrossRef] 
[13] Megginson, W.L., Meles, A., Sampagnaro, G., et al. (2016) Financial Distress Risk in Initial Public Offerings: How Much Do Venture Capitalists Matter? Journal of Corporate Finance, 26, 1-52.
[14] 孙宝文, 牛超群, 赵宣凯, 荆文君. 财务困境识别: 中国P2P平台的风险特征研究[J]. 中央财经大学学报, 2016(7): 32-43 + 55.
[15] Ross, B. (2000) Financial Ratios and Different Failure Processes. Journal of Business Finance, No. 3, 18-24.

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