Objective Tram projects are characterized by large investment scale, long operation cycles, and slow recovery of social capital, often facing challenges such as financing difficulties and constrained capital exit channels. Asset securitization is an effective approach to address the poor liquidity of existing assets and attract social capital. To reasonably evaluate the value of underlying assets and ensure the successful issuance of securitization products, it is necessary to investigate the pricing mechanism of tram public-private partnership (PPP) projects in the process of the asset securitization, aiming to provide practical references and quantitative bases for activating the existing assets in the public transport sector.

Method Based on a PPP tram project in City A, a securitization product totaling 670 million yuan is designed according to practical demands. A binomial tree model is employed to construct the interest rate tree for this project from the end of 2019 to the end of 2023, simulating the uncertainty of interest rate fluctuations. On this basis, the option-adjusted spread (OAS) model is applied, and the trial-and-error method is introduced to deduce the pricing of embedded-option bonds. In pricing testing, due to the lack of secondary market data for the case project, a benchmark bond with similar risk characteristics is introduced to calibrate the model using its publicly available market parameters. The key indicator reflecting the project risk premium, namely the option-adjusted spread, is derived inversely via the trial-and-error method.

Result & Conclusion The interest rate tree indicates that the uncertainty of interest rate fluctuations increases over time. By continuously adjusting the spread on the benchmark interest rate tree, the theoretical price of the embedded-option bond is ultimately aligned with the assumed market price of 94.96 yuan. The calculation results show that the option-adjusted spread matching the project is 330 basis points. The accuracy of this calculated value is verified using the planning and solving function in Microsoft Excel.