This study proposes to employ a mean-reverting model to evaluate the real options embedded in international railway construction projects. The application of mean-reverting models has usually had the difficulty of defining suitable mean-reverting variables for evaluating railway construction projects. The innovative aspect in this research is the formation and calibration of the mean-reverting models we have proposed, in which underlying variables related to the present value of a railway project normalized by either the length of a railway track or the construction time are assumed to follow stochastic mean-reversion processes. Through an example, we show that this assumption enabled us to have evaluated the abandonment option embedded in the construction project by calibrating the parameters with Euler's estimation and maximum likelihood estimation.
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