This page provides an overview of the model mechanics and the theory of cash sweeps. The mechanics involve use of cash flow waterfall mechanics including MAX and MIN statements. The analysis demonstrates that the cash sweep reduces the return, but you can avoid this with re-financing. I also discuss why cash sweeps make sense for projects with volatile cash flows but not with cash flows that are more stable.
Cash Sweep Mechanics
The video below illustrates how to compute cash sweeps in a model. Shows how to build a model with structuring as well as cash sweep and covenants. Demonstrates how to build waterfall and evaluate defaults for risk analysis.
Shows how to model many re-financings with cash flow that occur in regular intervals. Demonstrates how the Equity IRR increases with different assumptions with respect to re-financing.
Cash Sweep and Break-Even
Demonstrates how alternative cash sweep structures affect the lowest cash flow that can be accepted before default occurs. Shows the cash sweep is important if sudden declines occur.
Cash Sweep Risk Measurement with Monte Carlo Simulation
Shows how Monte Carlo simulation can be applied to project finance models to evaluate the benefits and costs of different cash flow structures.
Project Finance Model with Commodity Price Risk and Monte Carlo Simulation
The file and video below illustrates how you can incorporate Monte Carlo simulation into a project finance model. The model is set-up to be a model with commodity price risk. Once the project finance model is built, a time series analysis with volatility and mean reversion parameters is added to the model. The Monte Carlo simulation works with a little VBA code that re-calculates the price and by consequence also the cash flow for many simulations. The Monte Carlo simulation can be used to judge the efficacy of various structuring issues including cash flow sweeps and cash flow traps. The model below and the video demonstrates how you can incorporate either scenario analysis and/or Monte Carlo analysis to measure credit risk associated with commodity prices. The file shows that at least in theory, you can use the PLCR and LLCR with Monte Carlo simulation to measure the probability of loss. This can be adjusted for cash sweeps and other features.