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A semiparametric method for predicting bankruptcy

Author

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  • Ruey-Ching Hwang
  • K. F. Cheng
  • Jack C. Lee

    (Graduate Institute of Finance, National Chiao Tung University, Hsinchu, Taiwan)

Abstract

Bankruptcy prediction methods based on a semiparametric logit model are proposed for simple random (prospective) and case-control (choice-based; retrospective) data. The unknown parameters and prediction probabilities in the model are estimated by the local likelihood approach, and the resulting estimators are analyzed through their asymptotic biases and variances. The semiparametric bankruptcy prediction methods using these two types of data are shown to be essentially equivalent. Thus our proposed prediction model can be directly applied to data sampled from the two important designs. One real data example and simulations confirm that our prediction method is more powerful than alternatives, in the sense of yielding smaller out-of-sample error rates. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Ruey-Ching Hwang & K. F. Cheng & Jack C. Lee, 2007. "A semiparametric method for predicting bankruptcy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(5), pages 317-342.
  • Handle: RePEc:jof:jforec:v:26:y:2007:i:5:p:317-342
    DOI: 10.1002/for.1027
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    References listed on IDEAS

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    2. Grice, John Stephen & Dugan, Michael T, 2001. "The Limitations of Bankruptcy Prediction Models: Some Cautions for the Researcher," Review of Quantitative Finance and Accounting, Springer, vol. 17(2), pages 151-166, September.
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    5. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    6. Thomas E. McKee, 2003. "Rough sets bankruptcy prediction models versus auditor signalling rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(8), pages 569-586.
    7. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
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    Cited by:

    1. repec:eee:touman:v:33:y:2012:i:3:p:622-634 is not listed on IDEAS
    2. Situm Mario, 2014. "Inability of Gearing-Ratio as Predictor for Early Warning Systems," Business Systems Research, De Gruyter Open, vol. 5(2), pages 23-45, September.
    3. El Kalak, Izidin & Hudson, Robert, 2016. "The effect of size on the failure probabilities of SMEs: An empirical study on the US market using discrete hazard model," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 135-145.
    4. Wolfgang Härdle & Yuh-Jye Lee & Dorothea Schäfer & Yi-Ren Yeh, 2009. "Variable selection and oversampling in the use of smooth support vector machines for predicting the default risk of companies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(6), pages 512-534.
    5. Harada, Nobuyuki & Kageyama, Noriyuki, 2011. "Bankruptcy dynamics in Japan," Japan and the World Economy, Elsevier, vol. 23(2), pages 119-128, March.
    6. repec:spr:schmbr:v:18:y:2017:i:3:d:10.1007_s41464-017-0034-y is not listed on IDEAS
    7. Hwang, Ruey-Ching & Chung, Huimin & Chu, C.K., 2010. "Predicting issuer credit ratings using a semiparametric method," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 120-137, January.
    8. repec:kap:compec:v:50:y:2017:i:1:d:10.1007_s10614-016-9581-4 is not listed on IDEAS
    9. Ruey-Ching Hwang & Huimin Chung & C. K. Chu, 2016. "A Two-Stage Probit Model for Predicting Recovery Rates," Journal of Financial Services Research, Springer;Western Finance Association, vol. 50(3), pages 311-339, December.
    10. Hwang, Ruey-Ching, 2012. "A varying-coefficient default model," International Journal of Forecasting, Elsevier, vol. 28(3), pages 675-688.
    11. Jairaj Gupta & Andros Gregoriou & Jerome Healy, 2015. "Forecasting bankruptcy for SMEs using hazard function: To what extent does size matter?," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 845-869, November.

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