Investment Analysis of Low-Carbon Yard Cranes: Integrating Monte Carlo Simulation and Jump Diffusion Processes with a Hybrid American–European Real Options Approach

In order to realize green and low-carbon transformation, some ports have explored the path of sustainable equipment upgrading by adjusting the energy structure of yard cranes in recent years. However, there are multiple uncertainties in the investment process of hydrogen-powered yard cranes, and the existing valuation methods fail to effectively deal with these dynamic changes and lack scientifically sound decision support tools. To address this problem, this study constructs a multi-factor real options model that integrates the dynamic uncertainties of hydrogen price, carbon price, and technology maturity. In this study, a geometric Brownian motion is used for hydrogen price simulation, a Markov chain model with jump diffusion term and stochastic volatility is used for carbon price simulation, and a learning curve method is used to quantify the evolution of technology maturity. Aiming at the long investment cycle of ports, a hybrid option strategy of “American and European” is designed, and the timing and scale of investment are dynamically optimized by Monte Carlo simulation and least squares regression. Based on the empirical analysis of Qingdao Port, the results show that the optimal investment plan for hydrogen-powered yard cranes project under the framework of a multi-factor option model is to use an American-type option to maintain moderate flexibility in the early stage, and to use a European-type option to lock in the return in the later stage. The study provides decision support for the green development of ports and enhances economic returns and carbon emission reduction benefits.