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The Assessment of Default Probability for the Project Finance Transactions

Author

Listed:
  • Karminsky, A.

    (National Research University Higher School of Economics, Moscow, Russia)

  • Morgunov, A.

    (National Research University Higher School of Economics, Moscow, Russia)

  • Bogdanov, P.

    (Moscow State Institute of International Relations (University), Moscow, Russia)

Abstract

The article reviewed approaches to the development of internal rating models in project finance. Empirical research was based on the collected sample of data on various investment projects, including financial, industrial and regional indicators. The model estimating the probability of default for the project finance transactions (within the framework of internal ratings based (IRB) approach) and using an econometric model of binary choice was developed. On the basis of the developed model the decision making algorithm on project participation was formulated. New results of this research lies in the use of Russian statistics when adapting the proposed approach for project finance transactions.

Suggested Citation

  • Karminsky, A. & Morgunov, A. & Bogdanov, P., 2015. "The Assessment of Default Probability for the Project Finance Transactions," Journal of the New Economic Association, New Economic Association, vol. 26(2), pages 99-122.
    • Handle: RePEc:nea:journl:y:2015:i:26:p:99-122
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    References listed on IDEAS

    as
    1. Karminsky, A. & Kostrov, A., 2013. "Modeling the Default Probabilities of Russian Banks: Extended Abillities," Journal of the New Economic Association, New Economic Association, vol. 17(1), pages 64-86.
    2. Boeing Singh Laishram & Satyanaranaya Kalidindi, 2009. "Desirability rating analysis for debt financing of public-private partnership road projects," Construction Management and Economics, Taylor & Francis Journals, vol. 27(9), pages 823-837.
    3. Anatoly Peresetsky & Alexandr Karminsky & Sergei Golovan, 2011. "Probability of default models of Russian banks," Economic Change and Restructuring, Springer, vol. 44(4), pages 297-334, November.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Alexander M. Karminsky & Ella Khromova, 2018. "Increase of banks’ credit risks forecasting power by the usage of the set of alternative models," Russian Journal of Economics, ARPHA Platform, vol. 4(2), pages 155-174, June.

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    More about this item

    Keywords

    default; logistic regression; normalization; discriminatory power;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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