Leveraged Buyout – Debt Equity Ratio

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Leveraged Buyout – Debt Equity Ratio


Published on Feb 16, 2016

In this tutorial, you’ll learn how to determine the proper debt level to use in a leveraged buyout case study given by a private equity firm – all from using Google and free information you can find online.

Leveraged Buyout  Table of Contents:

2:35 Step 1: Find Comparable Deals and Estimate the Purchase Multiple and Debt / EBITDA

9:45 Step 2: Test Your Assumptions in Excel

16:21 Step 3: Tweak Your Assumptions as Necessary

18:21 Recap and Summary

Lesson Outline:

Question that came in the other day…

“Help! I just got a case study from a private equity firm I’m interviewing with.”

“I have to pick a consumer/retail company, download its filings, complete a leveraged buyout model for the company, and recommend for or against the deal.”

“How can I determine how much debt to use in the deal? They didn’t give me any instructions!”

You can figure this out simply in most cases without wasting a ton of time sifting through company’s filings. Here’s the 3-step process:

Step 1: Estimate the purchase multiple, purchase price, and Debt / EBITDA by looking at comparable buyout deals (NOT publicly traded companies, as they almost always have lower debt levels).

Step 2: Test your assumptions in Excel and see if the company can manage that much debt.

Step 3: Go back and tweak your assumptions as necessary.

The purchase price and Debt / EBITDA are very closely linked – for example, you can’t assume 6x Debt / EBITDA if you’re paying only 5x EV / EBITDA for the entire company.

For most public companies, you need to assume at least a 20-30% share price premium, and then make sure the implied EV / EBITDA multiple is in-line with those of other recent deals in the market.

Let’s say you pick Bed, Bath & Beyond [BBBY] for your LBO candidate.

To find 2-3 comparable LBO deals, you can do Google searches for terms like:

“consumer retail” “leveraged buyouts” [This Year or Last Year] consumer leveraged buyouts
retail leveraged buyouts

In this case, we find 3 relevant deals: the buyouts of Petco (10x EV / EBITDA and 6x Debt / EBITDA), Life Time Fitness (11x EV / EBITDA and 5.5x Debt / EBITDA), and Belk (7x EV / EBITDA and 5-6x Debt / EBITDA).

So our deal will likely be done at 8-10x EV / EBITDA with 5-6x Debt / EBITDA.

BBBY’s share price has fallen by ~50% in the past year, so we think a 50%, 75%, or even 100% premium would be more reasonable than the standard 20-30%, and would imply a purchase multiple of 6.5x – 8.5x instead.

But can the company support that much debt?

To answer this question, you can create a simple Excel model with revenue growth, EBITDA margins, Cash Flow from Operations as a % of EBITDA, and CapEx as the key drivers.

The after-tax interest will also be subtracted from CFO – CapEx to determine debt repayment capacity.

Then you can evaluate debt repayment, Debt / EBITDA, and EBITDA / Interest over time to see if the debt level is too low, too high, or just about right.

Focus on the downside cases – What happens if revenue, EBITDA, cash flow, etc. decline? Margins and growth HAVE declined historically for BBBY!

Ideally, Debt / EBITDA should decline over time and EBITDA / Interest should rise as the company repays debt.

So if Debt / EBITDA rises instead, or EBITDA / Interest falls, you’ll have to assume a lower debt level.

In this deal, we run into trouble when revenue declines or when we pay closer to a 100% premium for the company because Debt / EBITDA approaches 8x in some later years.

Even if revenue growth stays positive and the premium is only 75%, the credit stats and ratios still don’t look “great.”

So we’d say that 5-6x Debt / EBITDA is a stretch, and 4-5x is more feasible. At a 75% premium, this might be 60% debt (4.5x) and at a 100% premium it might be 50% debt (4.2x).

Once you’ve come up with baseline estimates for these figures, you would continue to build the model, come up with something more complex, and then ultimately make your investment recommendation on the company and present it.

But you can save a lot of time and finish case studies more efficiently if you know how to find and confirm simple figures like these before you do anything more complex.

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