Simulation-Based Valuation of Project Finance - Does Model Complexity Really Matter?

Abstract

This paper analyzes the impact of model complexity on the valuation of a project financed power plant along two dimensions: The NPV distribution and the expected cumulative default probability of the project. Model complexity is separated into forecast and simulation complexity. Thereby, we aim to identify elements of model complexity that are crucial for the valuation result.

For this purpose we develop a project finance valuation tool, which generates cash flow distributions on the basis of a Monte Carlo simulation. This model is applied for in a case study, i.e. a project financed gas power plant.

The analysis reveals, among others, the following results: First, risk-neutral valuation should be used for determining the cost of capital. Second, we demonstrate that 10,000 iterations in the Monte Carlo simulation are sufficient to obtain stable results. Third, the choice of the volatility forecasting mode affects the simulation results significantly. Fourth, we find a significant impact of correlation versus no correlation but do not find a strong impact of sophisticated correlation forecasting techniques versus constant correlation.

Keywords: Project Finance, Investment Valuation, Stochastic Modeling, Monte Carlo Simulation, Forecasting, Model Complexity

JEL Classification: C63, Q40