Abstract
In this paper we propose a methodology that can assist in the design of the quantitative aspects of a process of securitization to finance toll roads. Our goal is to provide the process with a series of mechanisms to streamline it, and to optimize the overall result of securitization for both the originator and for the bondholders. While we choose to apply it to toll roads, we believe that with simple adjustments, the proposed methodology can be extended to many securitization processes, and especially those related to infrastructure funding. We define the objective functions to be optimized to obtain the optimum volume of cash flows to securitize for each investment period. After defining the goals consistent with the demands of the highway investor (maximizing results and minimizing the investment recovery time), we can conceptualize the problem of determining the optimal level of funding through securitization. It is a bi-objective programme, in which the company aims to maximize the surplus generated by the project and simultaneously to maximize liquidity. We define, develop and justify the constraints related to the problem and once the bi-objective optimization problem has been set, we approach the resolution of the optimization problem. We opt for multiobjective fuzzy programming to resolve this programme.
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Sardá, S., Molina, M.C. (2015). Optimization of Securitized Cash Flows for Toll Roads. In: Gil-Aluja, J., Terceño-Gómez, A., Ferrer-Comalat, J., Merigó-Lindahl, J., Linares-Mustarós, S. (eds) Scientific Methods for the Treatment of Uncertainty in Social Sciences. Advances in Intelligent Systems and Computing, vol 377. Springer, Cham. https://doi.org/10.1007/978-3-319-19704-3_32
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DOI: https://doi.org/10.1007/978-3-319-19704-3_32
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