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Measuring Value‐at‐Risk in Project Finance Transactions

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  • Stefano Gatti
  • Alvaro Rigamonti
  • Francesco Saita
  • Mauro Senati

Abstract

Despite the remarkable importance of project finance in international financial markets, no quantitative models to measure and quantify the risk associated with a deal for the project's lenders have been developed yet. The topic has recently become crucial, since the New Basle Capital Accord gives banks a choice of whether to adopt simpler (but possibly higher) standard capital requirements or to develop internal rating models for project finance transactions. The paper proposes how Monte Carlo simulations may be used to derive a Value‐at‐Risk estimate for project finance deals and discusses the critical issues that must be considered when developing such a model.

Suggested Citation

  • Stefano Gatti & Alvaro Rigamonti & Francesco Saita & Mauro Senati, 2007. "Measuring Value‐at‐Risk in Project Finance Transactions," European Financial Management, European Financial Management Association, vol. 13(1), pages 135-158, January.
  • Handle: RePEc:bla:eufman:v:13:y:2007:i:1:p:135-158
    DOI: 10.1111/j.1468-036X.2006.00288.x
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    Cited by:

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    2. Miranda Sarmento, J. & Renneboog, L.D.R., 2014. "Public-Private Partnerships : Risk Allocation and Value for Money," Other publications TiSEM b9218010-a357-4c0a-805a-7, Tilburg University, School of Economics and Management.
    3. Borgonovo, E. & Gatti, S. & Peccati, L., 2010. "What drives value creation in investment projects? An application of sensitivity analysis to project finance transactions," European Journal of Operational Research, Elsevier, vol. 205(1), pages 227-236, August.
    4. Farkas, Walter & Fringuellotti, Fulvia & Tunaru, Radu, 2020. "A cost-benefit analysis of capital requirements adjusted for model risk," Journal of Corporate Finance, Elsevier, vol. 65(C).
    5. Firouzi, Afshin & Meshkani, Ali, 2021. "Risk-based optimization of the debt service schedule in renewable energy project finance," Utilities Policy, Elsevier, vol. 70(C).
    6. Weber, Florian & Schmid, Thomas & Pietz, Matthäus & Kaserer, Christoph, 2010. "Simulation-based valuation of project finance: does model complexity really matter?," CEFS Working Paper Series 2010-03, Technische Universität München (TUM), Center for Entrepreneurial and Financial Studies (CEFS).
    7. Bonetti, Veronica & Caselli, Stefano & Gatti, Stefano, 2010. "Offtaking agreements and how they impact the cost of funding for project finance deals: A clinical case study of the Quezon Power Ltd Co," Review of Financial Economics, Elsevier, vol. 19(2), pages 60-71, April.
    8. Borgonovo, Emanuele & Gatti, Stefano, 2013. "Risk analysis with contractual default. Does covenant breach matter?," European Journal of Operational Research, Elsevier, vol. 230(2), pages 431-443.
    9. Zapata Quimbayo, Carlos Andrés, 2020. "Probabilidad de incumplimiento en inversiones de infraestructura: análisis a partir de modelos estructurales de riesgo de crédito || Probability of default in infrastructure projects: analysis from st," 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. 30(1), pages 327-345, December.
    10. Antonella Lomoro & Giorgio Mossa & Roberta Pellegrino & Luigi Ranieri, 2020. "Optimizing Risk Allocation in Public-Private Partnership Projects by Project Finance Contracts. The Case of Put-or-Pay Contract for Stranded Posidonia Disposal in the Municipality of Bari," Sustainability, MDPI, vol. 12(3), pages 1-18, January.
    11. Agnes Csiszarik-Kocsir, 2017. "How to finance renewable energy projects – facts and trends," Proceedings of FIKUSZ 2017, in: Monika Fodor (ed.), Proceedings of FIKUSZ '17, pages 44-56, Óbuda University, Keleti Faculty of Business and Management.
    12. Veronica Bonetti & Stefano Caselli & Stefano Gatti, 2010. "Offtaking agreements and how they impact the cost of funding for project finance deals," Review of Financial Economics, John Wiley & Sons, vol. 19(2), pages 60-71, April.
    13. Yonggu Kim & Eul-Bum Lee, 2018. "A Probabilistic Alternative Approach to Optimal Project Profitability Based on the Value-at-Risk," Sustainability, MDPI, vol. 10(3), pages 1-24, March.
    14. Valerio Buscaino & Stefano Caselli & Francesco Corielli & Stefano Gatti, 2012. "Project Finance Collateralised Debt Obligations: an Empirical Analysis of Spread Determinants," European Financial Management, European Financial Management Association, vol. 18(5), pages 950-969, November.
    15. F. Acebes & J. M. González-Varona & A. López-Paredes & J. Pajares, 2024. "Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    16. Wei Sun & Svetlozar Rachev & Frank J. Fabozzi, 2009. "A New Approach for Using Lévy Processes for Determining High‐Frequency Value‐at‐Risk Predictions," European Financial Management, European Financial Management Association, vol. 15(2), pages 340-361, March.
    17. A. Garcia-Bernabeu & F. Mayor-Vitoria & F. Mas-Verdu, 2015. "Project Finance Recent Applications and Future Trends: The State of the Art," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 14(2), pages 159-178, December.

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