Antares, a San Francisco-based boutique investment bank specializing in US and European deals, asked the Nicholas Center to build a complex financial model to help them better service clients. The team of second-year students tasked with constructing the model embraced the challenge and set to work making the most user-friendly model possible while ensuring that the model could be employed in all foreseeable circumstances.
The model was a reverse leveraged buyout (LBO) model. The typical LBO model takes the deal purchase price as an input and calculates the sponsor’s internal rate of return (IRR). A reverse LBO model takes the IRR as an input and calculates the purchase price that would be needed to achieve the given IRR. This model also solves for the beginning and ending equity amounts for the sponsor, as well as the entrance and exit EBITDA multiple.
To ensure that the model could be used with all possible scenarios, the team interviewed experts at J.P. Morgan and GE Capital and incorporated the breadth of options for financing deal structures. Anyone who uses the model can input a variety of capital structure assumptions, including management equity and warrants.
While the model’s internal calculations are complex, the team designed it so that users need not be experts at either finance or Excel to use it. In case someone at Antares has questions, the team went a step further and wrote a user manual to consult should there be any confusion about any particular aspect of the model.
While the Nicholas Center team learned more about conditional formatting and different modeling styles, Antares now has a product that enables them to quickly design and share with clients a medley of financing scenarios and the outcomes.