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Stochastic modelling and prediction of contractor default risk

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  • Huaming Zhai
  • Jeffrey Russell

Abstract

The purpose of this paper is to describe a systematic framework of stochastic modelling and prediction of financial default risk of construction contractors. Net-worth-to-asset ratio is identified as an index for default process modelling. The default condition is defined as when the ratio becomes negative the first time. A mean-reverting dynamic model for the contractor default process is found by statistical analysis and is justified by using the theory of optimal capital structure. The stochastic modelling of default uses the time to default as the fundamental random variable. A discrete time trinomial Markov chain model is developed to assess default risk in terms of a cumulative default probability function, a default probability function, and the mean and variance of time to default. Practical examples are given to illustrate the stochastic methods. A default discriminant study on a group of contractors and publicly traded companies validates the methods, and indicates a high predictability of events of default and declines of credit rating.

Suggested Citation

  • Huaming Zhai & Jeffrey Russell, 1999. "Stochastic modelling and prediction of contractor default risk," Construction Management and Economics, Taylor & Francis Journals, vol. 17(5), pages 563-576.
    • Handle: RePEc:taf:conmgt:v:17:y:1999:i:5:p:563-576
    DOI: 10.1080/014461999371187
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    Cited by:

    1. Yu Hoe Tang & Stephen Ogunlana, 2003. "Selecting superior performance improvement policies," Construction Management and Economics, Taylor & Francis Journals, vol. 21(3), pages 247-256.
    2. Rodríguez Guevara, David Esteban & Rendón García, Juan Fernando & Trespalacios Carrasquilla, Alfredo & Jiménez Echeverri, Edwin Andrés, 2022. "Modelación de riesgo de crédito de personas naturales. Un caso aplicado a una caja de compensación familiar colombiana [Natural People Credit Risk Modeling. An applied case in a Colombian Family Be," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 33(1), pages 29-48, June.

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