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A Non-Performing Loans (NPLs) Portfolio Pricing Model Based on Recovery Performance: The Case of Greece

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  • Alexandra Z. Marouli

    (Laboratory of Industrial and Energy Economy, National Technical University of Athens, 15780 Athens, Greece)

  • Eugenia N. Giannini

    (Laboratory of Law and Technical Legislation, National Technical University of Athens, 15780 Athens, Greece)

  • Yannis D. Caloghirou

    (Laboratory of Industrial and Energy Economy, National Technical University of Athens, 15780 Athens, Greece)

Abstract

In this paper, a method was proposed for pricing NPL portfolios, which is currently a crucial point in the portfolio transactions between the banks and NPL servicers. The method was based on a simple mathematical model which simulated the collection process of the NPL portfolios considering the debtors’ behavioral response to various legal measures (phone calls, extrajudicial notices, court orders, and foreclosures). The model considered the recovery distribution over time and was applied successfully to the case of Greece. The model was also used to predict recovery, cost, and profit future cash flows, and to optimize the collection strategies related to the activation periods of different measures. A sensitivity analysis was also conducted to reveal the most significant factors affecting the collection process.

Suggested Citation

  • Alexandra Z. Marouli & Eugenia N. Giannini & Yannis D. Caloghirou, 2023. "A Non-Performing Loans (NPLs) Portfolio Pricing Model Based on Recovery Performance: The Case of Greece," Risks, MDPI, vol. 11(5), pages 1-17, May.
  • Handle: RePEc:gam:jrisks:v:11:y:2023:i:5:p:96-:d:1150066
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    References listed on IDEAS

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    1. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    2. Hui Ye & Anthony Bellotti, 2019. "Modelling Recovery Rates for Non-Performing Loans," Risks, MDPI, vol. 7(1), pages 1-17, February.
    3. Claudia Girardone & Philip Molyneux & Edward Gardener, 2004. "Analysing the determinants of bank efficiency: the case of Italian banks," Applied Economics, Taylor & Francis Journals, vol. 36(3), pages 215-227.
    4. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    5. Eftychia Nikolaidou & Sofoklis Vogiazas, 2014. "Credit Risk Determinants for the Bulgarian Banking System," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 20(1), pages 87-102, February.
    6. Florian Manz & Birgit Müller & Dirk Schiereck, 2020. "The pricing of European non-performing real estate loan portfolios: evidence on stock market evaluation of complex asset sales," Journal of Business Economics, Springer, vol. 90(7), pages 1087-1120, August.
    7. Schiereck, D. & Manz, F. & Müller, B., 2020. "The pricing of European non-performing real estate loan portfolios – Evidence on stock market evaluation of complex asset sales," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124734, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
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