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Using credit scoring method for probability of non-financial companies default estimation at industry level

Author

Listed:
  • Ioan TRENCA
  • Annamaria BENYOVSZKI

    (Babes-Bolyai University Cluj-Napoca)

Abstract

The aim of this paper is to examine the determinants of probability of default for Romanian non-financial companies and to estimate the probability of default with credit scoring models. We develop six separate default models (for the following sectors: agriculture, trade, construction, industry, transport, storage and communication) for two time horizons: 1 year and 2 years.

Suggested Citation

  • Ioan TRENCA & Annamaria BENYOVSZKI, 2009. "Using credit scoring method for probability of non-financial companies default estimation at industry level," Finante - provocarile viitorului (Finance - Challenges of the Future), University of Craiova, Faculty of Economics and Business Administration, vol. 1(9), pages 45-58, May.
    • Handle: RePEc:aio:fpvfcf:v:1:y:2009:i:9:p:45-58
    as

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    File URL: http://feaa.ucv.ro/FPV/009-06.pdf
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    References listed on IDEAS

    as
    1. Altman, Edward I., 2005. "An emerging market credit scoring system for corporate bonds," Emerging Markets Review, Elsevier, vol. 6(4), pages 311-323, December.
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    More about this item

    Keywords

    credit scoring; probability of default; scoring models;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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