References
- Altman, E. I. 1968. “Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy.” The Journal of Finance 23: 589–609. doi:10.1111/j.1540-6261.1968.tb00843.x.
- Bellotti, T., and J. Crook. 2009. “Support Vector Machines for Credit Scoring and Discovery of Significant Features.” Expert Systems with Applications: An International Journal 36 (2): 3302–3308. doi:10.1016/j.eswa.2008.01.005.
- Bharath, S. T., and T. Shumway. 2008. “Forecasting Default with the Merton Distance to Default Model.” Review of Financial Studies 21: 1339–1369. doi:10.1093/rfs/hhn044.
- Bohn, J. R. 2000. “A Survey of Contingent-Claims Approaches to Risky Debt Valuation.” The Journal of Risk Finance 1 (3): 53–70. doi:10.1108/eb043448.
- Câmara, A., I. Popova, and B. Simkins. 2012. “A Comparative Study of the Probability of Default for Global Financial Firms.” Journal of Banking & Finance 36 (3): 717–732. doi:10.1016/j.jbankfin.2011.02.019.
- Charitou, A., D. Dionysiou, N. Lambertides, and L. Trigeorgis. 2013. “Alternative Bankruptcy Prediction Models Using Option-Pricing Theory.” Journal of Banking & Finance 37 (7): 2329–2341. doi:10.1016/j.jbankfin.2013.01.020.
- Chen, M.-Y. 2011. “Predicting Corporate Financial Distress Based on Integration of Decision Tree Classification and Logistic Regression.” Expert Systems with Applications 38 (9): 11261–11272. doi:10.1016/j.eswa.2011.02.173.
- Chen, X., X. Wang, and D. D. Wu. 2010. “Credit Risk Measurement and Early Warning of SMEs: An Empirical Study of Listed SMEs in China.” Decision Support Systems 49 (3): 301–310. doi:10.1016/j.dss.2010.03.005.
- Christoffersen, P. F., and F. X. Diebold. 2000. “How Relevant Is Volatility Forecasting for Financial Risk Management?” Review of Economics and Statistics 82 (1): 12–22.
- De Giuli, M. E., D. Fantazzini, and M. A. Maggi. 2008. “A New Approach for Firm Value and Default Probability Estimation beyond Merton Models.” Computational Economics 31 (2): 161–180. doi:10.1007/s10614-007-9112-4.
- De Gooijer, J. G., and R. J. Hyndman. 2006. “25 Years of Time Series Forecasting.” International Journal of Forecasting 22 (3): 443–473. doi:10.1016/j.ijforecast.2006.01.001.
- Desai, V. S., J. N. Crook, and G. A. Overstreet Jr. 1996. “A Comparison of Neural Networks and Linear Scoring Models in the Credit Union Environment.” European Journal of Operational Research 95 (1): 24–37. doi:10.1016/0377-2217(95)00246-4.
- Duffie, D., L. Saita, and K. Wang. 2007. “Multi-Period Corporate Default Prediction with Stochastic Covariates.” Journal of Financial Economics 83 (3): 635–665. doi:10.1016/j.jfineco.2005.10.011.
- Durand, D. 1941. Risk Elements in Consumer Instalment Financing. Cambridge, MA: NBER Books.
- Elliott, R. J., T. K. Siu, and E. S. Fung. 2014. “A Double HMM Approach to Altman Z-Scores and Credit Ratings.” Expert Systems with Applications 41 (4): 1553–1560. doi:10.1016/j.eswa.2013.08.052.
- Gordy, M. B., and J. Marrone. 2012. “Granularity Adjustment for Mark-To-Market Credit Risk Models.” Journal of Banking & Finance 36 (7): 1896–1910. doi:10.1016/j.jbankfin.2012.02.010.
- Grablowsky, B. J., and W. K. Talley. 1981. “Probit and Discriminant Functions for Classifying Credit Applicants: A Comparison.” Journal of Economic Business 33: 254–261.
- Huang, C.-L., M.-C. Chen, and C.-J. Wang. 2007. “Credit Scoring with a Data Mining Approach Based on Support Vector Machines.” Expert Systems with Applications 33 (4): 847–856. doi:10.1016/j.eswa.2006.07.007.
- Joanes, D. N. 1993. “Reject Inference Applied to Logistic Regression for Credit Scoring.” IMA Journal of Management Mathematics 5 (1): 35–43. doi:10.1093/imaman/5.1.35.
- Johnsen, T., and R. W. Melicher. 1994. “Predicting Corporate Bankruptcy and Financial Distress: Information Value Added by Multinomial Logit Models.” Journal of Economics and Business 46 (4): 269–286. doi:10.1016/0148-6195(94)90038-8.
- Ketz, J. E. 2003. Hidden Financial Risk: Understanding Off-Balance Sheet Accounting. Hoboken, NJ: John Wiley & Sons.
- Korkeamäki, T., S. Pöyry, and M. Suo. 2014. “Credit Ratings and Information Asymmetry on the Chinese Syndicated Loan Market.” China Economic Review 31: 1–16. doi:10.1016/j.chieco.2014.08.001.
- Laitinen, E. K. 1999. “Predicting a Corporate Credit Analyst’s Risk Estimate by Logistic and Linear Models.” International Review of Financial Analysis 8 (2): 97–121. doi:10.1016/S1057-5219(99)00012-5.
- Lee, T.-S., -C.-C. Chiu, Y.-C. Chou, and C.-J. Lu. 2006. “Mining the Customer Credit Using Classification and Regression Tree and Multivariate Adaptive Regression Splines.” Computational Statistics & Data Analysis 50 (4): 1113–1130. doi:10.1016/j.csda.2004.11.006.
- Lennox, C. 1999. “Identifying Failing Companies: A Re-Evaluation of the Logit, Probit and DA Approaches.” Journal of Economics and Business 51 (4): 347–364. doi:10.1016/S0148-6195(99)00009-0.
- Martin, D. 1977. “Early Warning of Bank Failure: A Logit Regression Approach.” Journal of Banking & Finance 1 (3): 249–276. doi:10.1016/0378-4266(77)90022-X.
- Merton, R. C. 1974. “On the Pricing of Corporate Debt: The Risk Structure of Interest Rates.” Journal of Finance 29: 449–470.
- Messier, W. F., and J. V. Hansen. 1988. “Inducing Rules for Expert System Development: An Example Using Default and Bankruptcy Data.” Management Science 34 (12): 1403–1415. doi:10.1287/mnsc.34.12.1403.
- Meyer, P. A., and H. Pifer. 1970. “Prediction of Bank Failures.” The Journal of Finance 25 (4): 853–868. doi:10.1111/j.1540-6261.1970.tb00558.x.
- Nikolic, N., N. Zarkic-Joksimovic, D. Stojanovski, and I. Joksimovic. 2013. “The Application of Brute Force Logistic Regression to Corporate Credit Scoring Models: Evidence from Serbian Financial Statements.” Expert Systems with Applications 40 (15): 5932–5944. doi:10.1016/j.eswa.2013.05.022.
- Olmeda, I., and E. Fernandez. 1997. “Hybrid Classifiers for Financial Multicriteria Decision Making: The Case of Bankruptcy Prediction.” Computational Economics 10 (4): 317–335. doi:10.1023/A:1008668718837.
- Poon, S. H., and C. W. Granger. 2003. “Forecasting Volatility in Financial Markets: A Review.” Journal of Economic Literature 41 (2): 478–539. doi:10.1257/.41.2.478.
- Ronn, E. I., and A. K. Verma. 1986. “Pricing Risk‐Adjusted Deposit Insurance: An Option‐Based Model.” The Journal of Finance 41 (4): 871–896. doi:10.1111/j.1540-6261.1986.tb04554.x.
- Schebesch, K. B., and R. Stecking. 2005. “Support Vector Machines for Classifying and Describing Credit Applicants: Detecting Typical and Critical Regions.” Journal of the Operational Research Society 56 (9): 1082–1088. doi:10.1057/palgrave.jors.2602023.
- Su, E.-D., and S.-M. Huang. 2010. “Comparing Firm Failure Predictions between Logit, KMV, and ZPP Models: Evidence from Taiwan’s Electronics Industry.” Asia-Pacific Financial Markets 17 (3): 209–239. doi:10.1007/s10690-010-9113-5.
- Tam, K. Y., and M. Y. Kiang. 1992. “Managerial Applications of the Neural Networks: The Case of Bank Failure Predictions.” Management Science 38 (7): 926–947. doi:10.1287/mnsc.38.7.926.
- Vassalou, M., and Y. Xing. 2004. “Default Risk in Equity Returns.” The Journal of Finance 59 (2): 831–868. doi:10.1111/jofi.2004.59.issue-2.
- Vellido, A., P. J. Lisboa, and J. Vaughan. 1999. “Neural Networks in Business: A Survey of Applications (1992–1998).” Expert Systems with Applications 17 (1): 51–70. doi:10.1016/S0957-4174(99)00016-0.
- Wang, G., and J. Ma. 2011. “Study of Corporate Credit Risk Prediction Based on Integrating Boosting and Random Subspace.” Expert Systems with Applications 38 (11): 13871–13878.
- Westgaard, S., and N. Van der Wijst. 2001. “Default Probabilities in a Corporate Bank Portfolio: A Logistic Model Approach.” European Journal of Operational Research 135 (2): 338–349. doi:10.1016/S0377-2217(01)00045-5.
- Wiginton, J. C. 1980. “A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behavior.” The Journal of Financial and Quantitative Analysis 15 (3): 757–770. doi:10.2307/2330408.
- Youden, W. J. 1950. “Index for Rating Diagnostic Tests.” Cancer 3 (1): 32–35. doi:10.1002/(ISSN)1097-0142.
- Zhang, M., Y. He, and Z.-F. Zhou. 2013. “Study on the Influence Factors of High-Tech Enterprise Credit Risk: Empirical Evidence from China’s Listed Companies.” Procedia Computer Science 17: 901–910. doi:10.1016/j.procs.2013.05.115.
- Zhang, Z., G. Gao, and Y. Shi. 2014. “Credit Risk Evaluation Using Multi-Criteria Optimization Classifier with Kernel, Fuzzification and Penalty Factors.” European Journal of Operational Research 237 (1): 335–348. doi:10.1016/j.ejor.2014.01.044.
- Zhou, Y. A., M. H. Kim, and S. Ma (2012). “Survive or Die? An Empirical Study on Chinese ST Firms.” International Conference of the American Committee for Asian Economic Studies (ACAES), Deakin University, Melbourne, Australia, 1–32.